Sleep deficiency and motor vehicle crash risk in the general population: a prospective cohort study

Sleep Problems and Sleep Quality in the General Adult Population Living in South Tyrol (Italy): A Cross-Sectional Survey Study

It remains unclear how sleep health has developed in the general population after the COVID-19 pandemic. This study aimed to (1) investigate the prevalence of sleep problems and poor sleep quality and (2) explore the associated sociodemographic and health-related factors in South Tyrol, Italy. A cross-sectional, population-based survey was conducted with a stratified probabilistic sample of 4000 adults aged ≥ 18 years. Sleep quality was assessed using the brief version of the Pittsburgh Sleep Quality Index. Descriptive and logistic regression analyses were performed to analyze the data. A total of 2090 adults (53%) completed the survey. Poor sleep quality was reported by 17.8%, with 28.2% of participants reporting insufficient sleep duration (i.e., six hours or less), 12.7% having problems staying asleep (i.e., waking up to 3-4 times a week and unable to fall asleep again), and 8.7% having problems falling asleep (i.e., >30 min). Sleep problems and poor sleep quality were associated with sociodemographic and health-related factors, including gender, age, mother tongue, chronic disease, and sleep hygiene. Notably, Italian-speaking participants reported poorer sleep quality and greater difficulty staying asleep compared to German-speaking participants, highlighting potential sociocultural influences on sleep health. This study contributes to understanding the unique sleep health challenges in a multilingual region, highlighting the role of sociocultural factors in sleep quality differences between language groups.

The relationship between obesity and obstructive sleep apnea in four community-based cohorts: an individual participant data meta-analysis of 12,860 adults

Background

Obesity is a well-established risk factor for obstructive sleep apnea (OSA). We assessed the reciprocal prevalence of obesity and OSA and how it varies by age and sex.

Methods

Following a systematic review through March 27, 2025, the final sample included four community-based cohort studies in the US and Switzerland. OSA severity was quantified using the apnea-hypopnea index (AHI, all apneas plus hypopneas with ≥4% oxygen desaturation/hour). Random effects individual participant data (IPD) meta-analyses estimated prevalences. Logistic regression compared odds of OSA across weight groups.

Findings

Among 12,860 adults (mean ± SD age: 66.6 ± 7.3 years), 7222 (56.2%) had OSA (AHI ≥5 events/h) and 3309 (25.7%) had obesity (BMI ≥30 kg/m2). IPD meta-analysis showed 31.5% [95% CI: 16.8-48.5] of individuals with OSA had obesity and 44.4% [36.5-52.5] had overweight status (25 ≤ BMI < 30). Among subgroups of individuals with obesity and overweight, 74.3% [63.8-83.5] and 59.8% [46.5-75.7] had any OSA, respectively. Obesity was higher in females than males with OSA, and in younger (<65 years) vs. older individuals. Odds ratios for OSA in subgroups of individuals with overweight and obesity compared to BMI <25 kg/m2 were 2.18 [1.73-2.76] and 4.84 [3.09-6.00], respectively.

Interpretation

Our analyses show that most adults with OSA do not have obesity, with 44.4% having overweight and 23.5% having normal weight or underweight. Obesity was more prevalent among females compared to males and in younger individuals (<65 years) compared to older individuals with OSA. Recognizing OSA is not exclusive to obesity highlights the need for personalized treatment plans.

Funding

American Academy of Sleep Medicine, National Heart, Lung, and Blood Institute, and Apnimed.

Molecular basis identification and hypnotic drug interactions for cognitive impairment related to sleep deprivation

Chronic sleep deprivation can lead to cognitive impairment which makes it difficult to think, focus, and make comprehensive decisions. This in turn leads to the progression and increased risk of several diseases. This study aimed to explore potential drug targets and biomarkers underlying the increased disease risk due to sleep deprivation, including stress responses, immune dysfunction, and metabolic dysregulation. Four datasets namely GSE40562, GSE98566, GSE98582 for sleep deprivation, and GSE26576 normal brain cells were utilized to understand the molecular basis and potential drug targets associated with sleep deprivation. The GEO2R tool, Robust rank aggregations, and Venny were used to retrieve the common DEGs. Functional gene and pathway analyses were carried out via GO and the KEGG analyses. The STRING and CytoHuba plugins were utilized to identify the protein-protein interactions (PPIs) as well as the hub genes in the main PPI subnetworks following the drug interaction of the hub genes and GEPIA-based survival analysis of the DEGs. A total of 160 common DEGs were retrieved from all four datasets. Among them, 65 were down-regulated and 95 were up-regulated. TOP2A, AURKB, NEFL, CDC42, ASPM, GAP43, PVALB, NUF2, CALM1, TPR, KIF5B, KIF15, TROAP, NDC80, PBK, MKI67, SST, AHSP, ALAS2, and NEFH were retrieved as hub genes. While based on drug interaction, survival analysis and gene expression profile eight hub gene named TOP2A, AURKB, PVALB, CALM1, KIF5B, PBK, MKI67, and SST were found to be potential drug candidates and significantly correlated with infiltration levels of CD8 + T cells, B cells, macrophages, CD4 + T cells, neutrophils, and dendritic cells. These genes might play a role in sleep disorders via various pathways associated with neurodegeneration and diseases, potentially serving as biomarkers to support treatment and diagnosis.

Prevalence and factors associated with road traffic crashes among truck drivers in Southeast Iran

Road traffic injuries are the second leading cause of death in Iran. The study investigated the prevalence and the influencing factors of Road traffic crashes (RTCs) among truck drivers in southeast Iran. In this cross-sectional study, 592 truck drivers were recruited using a multi-stage sampling method from November 2022 to February 2023. Data was collected through a researcher-administered questionnaire that included the crashes, individual characteristics, driving characteristics, work patterns, sleep and fatigue-related factors, workload, driving styles, and personality traits. Simple and multiple logistic regressions were used to assess the association between risk factors and crash involvement in the 3 last years. The surveyed drivers had a mean age of 37.4 ± 8.9 years, with an average driving history of 13.7 ±  7.6 years. Among the respondents, 28.4% reported involvement in crashes over the last 3 years, with 12.1% reporting one, 10% reporting two, and 6.3% experiencing three or more crashes. A significant portion of the crashes (42.5%) occurred between midnight and 6:00 a.m. In their lifetime, 24.2% of participants reported at least one sleep-related crash, 40.5% reported at least one fatigue-related crash, and 6.9% reported at least one crash resulting in a fatality. The odds of RTCs were higher among truck drivers who used drugs (OR = 2.03, 95% CI, 1.36-3.04), used mobile devices for texting (OR = 2.88, 95% CI, 1.56-5.30), neglected seat belt usage (OR = 1.81, 95% CI, 1.10-2.99), had accumulated traffic fines in the last year (OR =  8.18, 95% CI, 3.82-17.52, OR =  11.39, 95% CI, 5.42-23.92, OR =  17.78, 95% CI, 7.50-42.17, for 1-2, 3-6, and > 6 traffic fines, respectively), consumed sleeping pills (OR = 2.52, 95% CI, 1.19-5.35), engaged sleep driving (OR = 11.30, 95% CI, 7.18-17.80), extended their driving hours without a break (OR =  3.02, 95% CI, 1.55-5.87, for consecutive driving hours before taking a break ≥ 8), experienced fatigue while driving (OR =  1.98, 95% CI, 1.24-3.17, for sometimes experienced fatigue while driving), faced high visual demands (OR = 1.23, 95% CI, 1.02-1.50), exhibited a careless driving style (OR = 0.95, 95% CI, 0.91- 0.99), and had higher levels of neuroticism (OR = 1.05, 95% CI, 1.01-1.10). The study sheds light on the significant prevalence of road traffic crashes among truck drivers. The findings underscore a constellation of factors amplifying crash risks within this occupational group. These outcomes emphasize the multifaceted nature of road safety issues within the trucking industry, indicating the need for targeted interventions and preventive measures to enhance driver safety and reduce the incidence of road traffic crashes among truck drivers.

Focusing on sleep health for all, not just sleep disorders

Sleep is increasingly recognized as a critical pillar of overall health, yet public health efforts have traditionally focused on treating sleep disorders rather than promoting sleep health for all. This article argues that the time has come to shift the emphasis from a disorder-centric approach to one that prioritizes sleep health for everyone. Sleep health extends beyond the absence of disorders and involves achieving optimal sleep quality, duration, and consistency. Poor sleep is linked to numerous health problems, including cardiovascular disease, type 2 diabetes, mental health disorders, and impaired cognitive function. Focusing on sleep health can help prevent these conditions and reduce healthcare costs. Moreover, addressing sleep health disparities, particularly among lower-income populations, shift workers, and racial and ethnic minorities, is crucial for achieving health equity. This article outlines strategies such as public awareness campaigns, workplace policies, school-based interventions, and policy advocacy to promote sleep health. By fostering a sleep-healthy society, we can improve individual and public health outcomes, enhance productivity, and reduce the economic burden associated with poor sleep. Ultimately, a comprehensive approach to sleep health offers significant benefits that extend beyond the treatment of sleep disorders, promoting a healthier and more equitable society.

A meta-analytic investigation of the effect of sleep deprivation on inhibitory control

Sleep deprivation may have a deleterious effect on inhibitory control; however, this effect is not consistent across studies. To arrive at an overall estimate of the relationship between sleep deprivation and inhibitory control, this report used meta-analysis to summarise the magnitude of the effects of sleep deprivation on inhibitory control as measured by the Go/No-Go and Stop Signal Tasks. These are two widely used tasks in the literature. A systematic search of four databases (APAPsycINFO, Medline, CINAHL and Embase) from their inception to November 2023 identified 24 studies involving 712 healthy individuals. Separate random-effects models were used to estimate the effect size of sleep deprivation on performance in these tasks. The meta-analysis revealed a moderate negative effect of sleep deprivation on inhibitory control in both the Go/No-Go and Stop Signal Tasks. Given the importance of inhibitory control in everyday behaviour, future research should investigate the neural and neurophysiological mechanisms underlying this relationship and explore its impact in clinical populations.

Mapping the Neural Basis of Wake Onset Regularity and Its Effects on Sleep Quality and Positive Affect

The regularity of sleep-wake cycles is a defining characteristic of normative sleep patterns that are typically associated with proper circadian rhythmicity. The previous literature indicates that consistent patterns of sleep and wake are associated with improved sleep quality and cognitive functioning. Conversely, sleep irregularity has been associated with reduced well-being and inefficiency in resting-state neural networks. This study investigated the relationship between specific sleep regularity measures and outcomes, including emotional affect, sleep quality, and resting-state functional connectivity. We found that variability in wake onset predicted poorer sleep quality and reduced positive affect. Furthermore, sleep regularity measures were associated with altered functional connectivity between the posterior cingulate cortex and regions involved in emotional processing. We propose that alterations in default mode network (DMN) connectivity linked to sleep irregularity reflect disruptions in emotional processing and sleep quality.

Seeking professional help for sleep-related complaints

Introduction

Sleep-related complaints affect a significant proportion of the adult population in many societies. Despite the prevalence of symptoms and potential secondary and comorbid conditions, the utilization of professional help is quite low. The underlying reasons for this phenomenon have yet to be adequately investigated. To address this gap, we expand the conventional explanatory models to encompass the perceived cause as an explanatory factor. This is aimed to contribute to a better understanding of the help-seeking behavior and to create the basis for possible measures.

Materials and methods

The empirical basis of the study is a quantitative data set collected in Germany in 2015 comprising 3,000 individuals between the ages of 40 and 75. Of these individuals, 761 reported experiencing sleep-related complaints. In our logistic regression, the binary dependent variable is whether professional help has already been sought. In addition to the factors included in the behavioral model of health service use, we utilize the perceived cause as a predictor, categorizing the variable as follows: exclusively mental, partially mental, and not mental.

Results

Our analysis shows that individuals who attributed their sleep disturbances solely to their psyche were significantly less likely to seek professional help (AME: -0.158**). These differences remain significant after controlling for the severity of the complaints, their duration, and other covariates (AME: -0.117**). The data also suggest that this group is more likely to seek self-help through medication.

Discussion

The results indicate the importance of focusing healthcare systems and public health policy on sleep-related complaints and their management. The aim is not only to alleviate sleep complaints, but also to reduce the risk of secondary diseases and to identify possible comorbidities. Additionally, it is a factor in reducing safety risks for the general public. Therefore, various measures should be implemented, including destigmatizing, improving health literacy, a more comprehensive offer of cognitive-behavioral therapy (CBT-I), and a more thorough examinations by physicians.

Insomnia and sleep duration for kidney function: Mendelian randomization study

OBJECTIVES

Extensive researches highlight the detrimental impact of sleep disorders such as insomnia and insufficient sleep duration on kidney function. However, establishing a clear causal relationship between insomnia, sleep duration, and kidney function remains challenging. This study aims to estimate this relationship using Mendelian randomization (MR).

METHODS

Independent genetic variants strongly associated with insomnia (N = 462,341) and sleep duration (N = 460,099) were selected as instrumental variables from corresponding genome-wide association studies (GWAS). Kidney function parameters, including serum creatinine, estimated glomerular filtration rate by cystatin C (eGFRcys), acute renal failure (ARF), chronic renal failure (CRF), kidney injury molecule-1, neutrophil gelatinase associated lipocalin, microalbuminuria, cystatin C, and β2 microglobulin, were derived from GWAS databases. A two-sample MR study was conducted to assess the causal relationship between sleep disorders and kidney function, and multivariable MR was used to identify potential mediators. The inverse-variance weighted was used as the primary estimate.

RESULTS

MR analysis found robust evidence indicating that insomnia and short sleep duration were associated with an increased risk of elevated serum creatinine, regardless of adjusting for obesity. Causal links between sleep duration and eGFRcys or cystatin C were also identified. While genetically predicted insomnia and sleep duration were found to potentially impact ARF, CRF, microalbuminuria, and β2 microglobulin, the p-values in multivariable MR analysis became nonsignificant. No pleiotropy was detected.

CONCLUSIONS

This study demonstrates a causal impact of insomnia on the risk of elevated serum creatinine and a positive effect of sleep duration on serum creatinine, eGFRcys, and cystatin C. Our findings also suggest their potential indirect effects on ARF, CRF, microalbuminuria, and β2 microglobulin mediated by obesity.

Correlates of multidimensional sleep in premenopausal women: The BioCycle study

Purpose

To identify sleep dimensions (characteristics) that co-occur in premenopausal women. The second aim was to examine associations between multiple dimensions of sleep and a set of demographic, lifestyle, and health correlates. The overarching goal was to uncover patterns of poor-sleep correlates that might inform interventions to improve sleep health of women in this age group.

Methods

The BioCycle Study included 259 healthy women aged 18-44y recruited between 2005 and 2007 from Western New York. Participants reported sleep data through daily diaries and questionnaires that were used to create five sleep health dimensions (duration, variability, timing, latency, and continuity). We used multivariate analysis - canonical correlation methods - to identify links among dimensions of sleep health and patterns of demographic, psychological, and occupational correlates.

Results

Two distinct combinations of sleep dimensions were identified. The first - primarily determined by low variability in nightly sleep duration, low variability in bedtime (timing), greater nocturnal awakening, and less sleep onset latency - was distinguished from the second - primarily determined by sleep duration.The first combination of sleep dimensions was associated with older age and higher parity, fewer depressive symptoms, and higher stress level. The second combination of sleep dimensions was associated with perception of longer sleep duration as optimal, lower parity, not engaging in shift work, older age, lower stress level, higher prevalence of depressive symptoms, and White race.

Conclusion

Among premenopausal women, we demonstrated distinct patterns of sleep dimensions that co-occur and vary by demographic, health, and lifestyle correlates. These findings shed light on the correlates of sleep health vulnerabilities among young women.

Sleep Deficiency: Epidemiology and Effects

Adequate sleep is an important pillar of physical and mental health. Sleep deficiency, resulting from short sleep or suboptimal sleep quality, is highly prevalent in modern society. Occupation, social demands, psychiatric disorders, physical disorders, and sleep disorders are some of the contributing factors to sleep deficiency. Some populations are at increased risk of sleep deficiency based on ethnicity, age, marital status, sex, and hospitalization. Sleep deficiency influences cognition, alertness, mood, behavior, diabetes, cardiovascular health, renal function, immune system, and respiratory physiology. This review summarizes the epidemiology and effects of sleep deficiency.

An exploration into the sleep of workers on block-calving, pasture-based dairy farms

The benefits of sufficient and high-quality sleep for people are well documented. Insufficient sleep increases the risk of accidents, injuries, and negative health implications for people. This is especially relevant for farmers because they work with large animals and machinery. Dairy farming often requires early start times and long days, particularly over the high-workload calving period in block-calving, pasture-based systems. However, there is little published data quantifying the sleep quantity and quality of farmers over this period. In this study, the sleep patterns of workers (n = 33) on 10 New Zealand dairy farms were measured for 90 d over the spring calving period using a sleep measuring device (Oura ring, Oura Health Ltd., Oulu, Finland). Total sleep time (TST) averaged 6 h 15 min, lower than the required 7 to 9 h for optimal wellbeing and cognitive functioning. The TST decreased over the calving period and was significantly correlated with both sleep start and wake times. Factors such as work start time, farm location, and role on farm influenced sleep quantity and quality. Further research is required to better understand sleep and its effect on dairy farmers, over both the calving period and the remaining months of the year.

Guidelines for the assessment and management of residual sleepiness in obstructive apnea-hypopnea syndrome: Endorsed by the French Sleep Research and Medicine Society (SFRMS) and the French Speaking Society of Respiratory Diseases (SPLF)

Excessive daytime sleepiness (EDS) is frequent among patients with obstructive sleep apnea hypopnea syndrome (OSAHS) and can persist despite the optimal correction of respiratory events (apnea, hypopnea and respiratory efforts), using continuous positive airway pressure (CPAP) or mandibular advancement device. Symptoms like apathy and fatigue may be mistaken for EDS. In addition, EDS has multi-factorial origin, which makes its evaluation complex. The marketing authorization [Autorisation de Mise sur le Marché (AMM)] for two wake-promoting agents (solriamfetol and pitolisant) raises several practical issues for clinicians. This consensus paper presents recommendations of good clinical practice to identify and evaluate EDS in this context, and to manage and follow-up the patients. It was conducted under the mandate of the French Societies for sleep medicine and for pneumology [Société Française de Recherche et de Médecine du Sommeil (SFRMS) and Société de Pneumologie de Langue Française (SPLF)]. A management algorithm is suggested, as well as a list of conditions during which the patient should be referred to a sleep center or a sleep specialist. The benefit/risk balance of a wake-promoting drug in residual EDS in OSAHS patients must be regularly reevaluated, especially in elderly patients with increased cardiovascular and psychiatric disorders risks. This consensus is based on the scientific knowledge at the time of the publication and may be revised according to their evolution.

Sleep and periodontal health

Sleep is fundamental for health and well-being. An adequate amount and quality of sleep is a cardinal component of a healthy lifestyle at the basis of the prevention of many non-communicable chronic diseases. Recent evidence suggests that sleep disorders, particularly obstructive sleep apnea, represent an emerging risk factor for periodontal health. This review article provides a critical appraisal of the existing literature concerning the association between sleep duration, sleep quality, sleep disorders in general, and obstructive sleep apnea with periodontal diseases, including gingivitis and periodontitis. The putative mechanisms underlying these associations are described as well as the potential clinical implications for diagnosis and treatment.

Detection of Sleep Apnea Using Wearable AI: Systematic Review and Meta-Analysis

BACKGROUND

Early detection of sleep apnea, the health condition where airflow either ceases or decreases episodically during sleep, is crucial to initiate timely interventions and avoid complications. Wearable artificial intelligence (AI), the integration of AI algorithms into wearable devices to collect and analyze data to offer various functionalities and insights, can efficiently detect sleep apnea due to its convenience, accessibility, affordability, objectivity, and real-time monitoring capabilities, thereby addressing the limitations of traditional approaches such as polysomnography.

OBJECTIVE

The objective of this systematic review was to examine the effectiveness of wearable AI in detecting sleep apnea, its type, and its severity.

METHODS

Our search was conducted in 6 electronic databases. This review included English research articles evaluating wearable AI's performance in identifying sleep apnea, distinguishing its type, and gauging its severity. Two researchers independently conducted study selection, extracted data, and assessed the risk of bias using an adapted Quality Assessment of Studies of Diagnostic Accuracy-Revised tool. We used both narrative and statistical techniques for evidence synthesis.

RESULTS

Among 615 studies, 38 (6.2%) met the eligibility criteria for this review. The pooled mean accuracy, sensitivity, and specificity of wearable AI in detecting apnea events in respiration (apnea and nonapnea events) were 0.893, 0.793, and 0.947, respectively. The pooled mean accuracy of wearable AI in differentiating types of apnea events in respiration (normal, obstructive sleep apnea, central sleep apnea, mixed apnea, and hypopnea) was 0.815. The pooled mean accuracy, sensitivity, and specificity of wearable AI in detecting sleep apnea were 0.869, 0.938, and 0.752, respectively. The pooled mean accuracy of wearable AI in identifying the severity level of sleep apnea (normal, mild, moderate, and severe) and estimating the severity score (Apnea-Hypopnea Index) was 0.651 and 0.877, respectively. Subgroup analyses found different moderators of wearable AI performance for different outcomes, such as the type of algorithm, type of data, type of sleep apnea, and placement of wearable devices.

CONCLUSIONS

Wearable AI shows potential in identifying and classifying sleep apnea, but its current performance is suboptimal for routine clinical use. We recommend concurrent use with traditional assessments until improved evidence supports its reliability. Certified commercial wearables are needed for effectively detecting sleep apnea, predicting its occurrence, and delivering proactive interventions. Researchers should conduct further studies on detecting central sleep apnea, prioritize deep learning algorithms, incorporate self-reported and nonwearable data, evaluate performance across different device placements, and provide detailed findings for effective meta-analyses.

Respiratory muscle training for obstructive sleep apnea: Systematic review and meta-analysis

Obstructive sleep apnea is the most common sleep disorder. This review aims to evaluate the effectiveness and safety of respiratory muscle training in the treatment of patients with obstructive sleep apnea. The study protocol was registered in Prospero Platform (CRD42018096980). We performed searches in the main databases: Medical Literature Analysis and Retrieval System Online (MEDLINE) via Pubmed; Excerpta Medica dataBASE (Embase) via Elsevier; Cochrane Central Register of Controlled Trials (CENTRAL) via Cochrane Library; Latin American and Caribbean Literature on Health Sciences (LILACS) through the Portal of the Virtual Health Library and Physiotherapy Evidence Database (PEDro) for all randomised-controlled trials published before July 2022. The randomised-controlled trials were assessed for risk of bias and certainty of evidence. Thirteen randomised-controlled trials were included. All studies had an overall high risk of bias. Inspiratory muscle training probably improves systolic blood pressure and sleepiness when compared with sham. However, inspiratory muscle training probably does not improve diastolic blood pressure and maximum expiratory pressure, and may not be superior to sham for apnea-hypopnea index, forced expiratory volume in 1 s, forced vital capacity, sleep quality and quality of life. In addition, it is uncertain whether there is any effect of inspiratory muscle training on maximum inspiratory pressure and physical capacity. Inspiratory muscle training may also improve maximum inspiratory pressure and maximum expiratory pressure compared with oropharyngeal exercises. However, it may not be superior for apnea-hypopnea index, sleep quality, sleepiness, quality of life and functional capacity. When associated with physical exercise, inspiratory muscle training may not be superior to physical exercise alone for maximum inspiratory pressure, maximum expiratory pressure, systolic and diastolic blood pressure, and functional capacity. At the same time, when associated with cardiac rehabilitation exercises, inspiratory muscle training may reduce apnea-hypopnea index, improve inspiratory muscle strength, sleepiness and sleep quality compared with cardiac rehabilitation alone. However, it may not be superior for improving quality of life. Regarding expiratory muscle training, it may improve expiratory muscle strength and sleep quality, but not sleepiness when compared with sham. The evidence on the effects of expiratory muscle training in apnea-hypopnea index is very uncertain.

Sleep and Ultramarathon: Exploring Patterns, Strategies, and Repercussions of 1,154 Mountain Ultramarathons Finishers

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.

CONCLUSION

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.

The effects of insufficient sleep and adequate sleep on cognitive function in healthy adults

STUDY OBJECTIVES

Although sleep affects a range of waking behaviors, the majority of studies have focused on sleep loss with relatively little attention on sustained periods of adequate sleep. The goal of this study was to use an experimental design to examine the effect of both of these sleep patterns on cognitive performance in healthy adults.

METHODS

This study used a randomized crossover design. Participants who regularly slept 7-9 hours/night completed two 6-week intervention conditions, adequate sleep (maintenance of habitual bed/wake times) and insufficient sleep (reduction in sleep of 1.5 hours relative to adequate sleep), separated by a 2-6weeks (median=43days) washout period. Cognitive functioning was evaluated at baseline and endpoint of each intervention using the NIH Toolbox Cognition Battery. General linear models contrasted scores following each condition to the baseline of the first condition; the baseline of the second condition was included to evaluate practice effects.

RESULTS

Sixty-five participants (age 35.9 ± 4.9years, 89% women, 52% non-White race/ethnicity) completed study procedures. There was improvement in performance on the List Sorting Working Memory task after the adequate sleep condition that exceeded practice effects. Cognitive performance after insufficient sleep did not reach the level expected with practice and did not differ from baseline. A similar pattern was found on the Flanker Inhibitory Control and Attention task.

CONCLUSIONS

These findings contribute to our understanding of the complex interplay between sleep and cognition and demonstrate that consistent, stable sleep of at least 7 hours/night improves working memory and response inhibition in healthy adults.

CLINICAL TRIAL REGISTRATION

The manuscript reports on data from two clinical trials: Impact of Sleep Restriction on Performance in Adults (URL: https://clinicaltrials.gov/ct2/show/NCT02960776, ID Number: NCT02960776) and Impact of Sleep Restriction in Women (URL: https://clinicaltrials.gov/ct2/show/NCT02835261, ID Number: NCT02835261).

Sleepiness and the transition from wakefulness to sleep

The transition from wakefulness to sleep is a progressive process that is reflected in the gradual loss of responsiveness, an alteration of cognitive functions, and a drastic shift in brain dynamics. These changes do not occur all at once. The sleep onset period (SOP) refers here to this period of transition between wakefulness and sleep. For example, although transitions of brain activity at sleep onset can occur within seconds in a given brain region, these changes occur at different time points across the brain, resulting in a SOP that can last several minutes. Likewise, the transition to sleep impacts cognitive and behavioral levels in a graded and staged fashion. It is often accompanied and preceded by a sensation of drowsiness and the subjective feeling of a need for sleep, also associated with specific physiological and behavioral signatures. To better characterize fluctuations in vigilance and the SOP, a multidimensional approach is thus warranted. Such a multidimensional approach could mitigate important limitations in the current classification of sleep, leading ultimately to better diagnoses and treatments of individuals with sleep and/or vigilance disorders. These insights could also be translated in real-life settings to either facilitate sleep onset in individuals with sleep difficulties or, on the contrary, prevent or control inappropriate sleep onsets.

How Pediatric Sleep Disordered Breathing Impacts Parental Fatigue

OBJECTIVE

Previous research has indicated that sleep disordered breathing (SDB) can lead to a decreased quality of life in children and their families as compared to children who do not have SDB. The purpose of this study was to examine fatigue levels in parents who had young children who were impacted by sleep symptoms as determined by the OSA-18 scale.

STUDY DESIGN

Survey.

SETTING

Three pediatric otolaryngology clinics associated with a tertiary care children's hospital in Buffalo, NY.

METHODS

Fatigue levels for parents of children with OSA-18 ≥ 60 were assessed using the Fatigue Severity Scale and the Chalder Fatigue Scale. Consecutive parents with at least one child between the ages of 1 and 10 were recruited. Parents scored their youngest child on the OSA-18 scale.

RESULTS

Of the 261 respondents included, 37 parents had a child with an OSA-18 score ≥60. The majority, 211 (82.1%), of participants reported 2 caregivers in the household while 30 (11.7%) had 1 caregiver in the household. Parents of children with OSA-18 ≥60 had a significantly higher mean fatigue score, 16.5 ± 5.8, compared to their counterparts, 11.9 ± 5.2, on the Chalder Fatigue Scale (P < .001). Similar results were reported for the total score on the Fatigue Severity Scale, 34.7 ± 10.8 compared to 28.9 ± 12.0 (P = .004).

CONCLUSION

Parents of children with OSA-18 score ≥60 are significantly more fatigued than parents of children with lower scores. Recognition of this is important for the health care community as it impacts not just the child with OSA but also their family.

An Efficient Group Federated Learning Framework for Large-Scale EEG-Based Driver Drowsiness Detection

To avoid traffic accidents, monitoring the driver's electroencephalogram (EEG) signals to assess drowsiness is an effective solution. However, aggregating the personal data of these drivers may lead to insufficient data usage and pose a risk of privacy breaches. To address these issues, a framework called Group Federated Learning (Group-FL) for large-scale driver drowsiness detection is proposed, which can efficiently utilize diverse client data while protecting privacy. First, by arranging the clients into different levels of groups and gradually aggregating their model parameters from low-level groups to high-level groups, communication and time costs are reduced. In addition, to solve the problem of notable variations in EEG signals among different clients, a global-personalized deep neural network is designed. The global model extracts shared features from various clients, while the personalized model extracts fine-grained features from each client and outputs classification results. Finally, to address special issues such as scale/category imbalance and data pollution, three checking modules are designed for adjusting grouping, evaluating client data, and effectively applying personalized models. Through extensive experimentation, the effectiveness of each component within the framework was validated, and a mean accuracy, F1-score, and Area Under Curve (AUC) of 81.0%, 82.0%, and 87.9% was achieved, respectively, on a publicly available dataset comprising 11 subjects.

A dollar well spent: Monetizing the societal benefits of low-income weatherization programs in the United States

Low-income residential energy efficiency programs save energy and can yield numerous co-benefits or non-energy impacts (NEIs). This paper presents a two-component framework that can be used to measure and monetize household-related NEIs. Two examples of using the framework are presented, one associated with an evaluation of a low-income single family home weatherization program implemented in the Southeastern United States (U.S.) and a second associated with a broad NEI assessment of weatherized affordable multifamily buildings in the Northeastern and Midwestern regions of the U.S. Seventeen NEIs were subject to monetization, including reductions in medical interventions for being too cold or too hot in one's home and reductions in use of predatory loans. The results of the two monetization exercises indicate that the monetary value of the NEIs is equal to or exceeds the energy efficiency job costs and energy cost savings. It is also clear that the value of the NEIs differs quite substantially based on home type. Future research can focus on better estimating changes in NEI variables and expressing ranges of uncertainty in final monetization values.

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.

Racial/ethnic differences in the beneficial effect of social support on sleep duration

STUDY OBJECTIVES

Social support (SS) is associated with better health outcomes, including sleep health. However, the specific sources of SS that benefit sleep are unclear, and whether these associations vary by race/ethnicity or age is unknown. The aim of this study was to examine cross-sectional associations between sources of SS (number of friends, financial, church attendance, and emotional support) and self-reported short sleep duration (< 7 hours) overall and by race/ethnic groups and age among a representative sample.

METHODS

Using National Health and Nutrition Examination Survey (NHANES) data, logistic regression (marginal standardization) and linear regression models were fit accounting for survey design and weights to test associations between sources of SS (number of friends, financial, church attendance, emotional support) and self-reported short sleep duration (< 7 hours) overall and by race/ethnic groups (Black, Hispanic, and White) and age (< 65 vs ≥ 65 years).

RESULTS

Among 3,711 participants, the mean (standard error) age was 57 (0.3) years and 37% slept < 7 hours. Black adults had the highest prevalence of short sleep (55%). Overall, participants with financial support compared with those without financial support had a lower prevalence of short sleep: 23% (confidence interval [CI]: 0.68, 0.87). As the number of SS sources increased, the prevalence of short sleep duration decreased and the racial disparity in sleep duration narrowed. Associations between financial support and sleep were most pronounced among Hispanic and White adults and adults < 65 years.

CONCLUSIONS

In general, financial support was associated with a healthier sleep duration, particularly among those < 65 years of age. Individuals with numerous sources of SS were less likely to be short sleepers. The benefits of SS on sleep duration varied by race. Targeting specific sources of SS may help to improve sleep duration among those most at risk.

CITATION

Johnson DA, Prakash-Asrani R, Lewis BD, Bliwise DL, Lewis TT. Racial/ethnic differences in the beneficial effect of social support on sleep duration. J Clin Sleep Med. 2023;19(7):1231-1238.

Sleepy Mice Case Study: Implementation and Assessment

Case studies are a valuable teaching tool to engage students in course content using real-world scenarios. As part of the High-throughput Discovery Science & Inquiry-based Case Studies for Today's Students (HITS) Research Coordination Network (RCN), our team has created the Sleepy Mice Case Study for students to engage with RStudio and the Allen Institute for Brain Science's open access high-throughput sleep dataset on mice. Sleep is important for health, a familiar concern to college students, and was a basis for this case study. In this case, students completed an initial homework assignment, in-class work, and a final take-home application assignment. The case study was implemented in synchronous and asynchronous Introductory Neuroscience courses, a Biopsychology course, and a Human Anatomy and Physiology course, reflecting its versatility. The case can be used to teach course-specific learning objectives such as sleep-related content and/or science data processing skills. The case study was successful as shown by gains in student scores and confidence in achieving learning objectives. Most students reported enjoying learning about sleep deprivation course content using the case study. Best practices based on instructor experiences in implementation are also included to facilitate future use so that the Sleepy Mice Case Study can be used to teach content and/or research-related skills in various courses and modalities.

The preventable productivity burden of sleep apnea in Australia: a lifetime modelling study

Obstructive sleep apnea (OSA) is a common disorder. OSA is associated with cardiovascular disease (CVD), type 2 diabetes mellitus (T2DM) and depression, among other comorbidities. We aim to determine the productivity burden of OSA in Australia using productivity-adjusted life-years (PALYs). Using life table modelling, we built a multistate Markov model to estimate the impact of moderate to severe OSA on the whole working-age Australian population in 2021 (aged 20-65 years) with OSA until retirement (aged 66 years). The model also captured the impact of OSA on CVD, T2DM, depression, and vehicle-related accidents. Data for OSA and comorbidities and Australian specific labour data, were extracted from published sources. A second cohort was then modelled to test the effect of a hypothetical intervention, assuming a 10% reduction in OSA prevalence and a 10% reduction in comorbidities in patients with OSA. The primary outcome of interest were PALYs accrued. All outcomes were discounted 5% annually. Over a lifetime, the Australian population with OSA accrued 193,713,441 years of life lived and 182,737,644 PALYs. A reduction of 10% in OSA prevalence and comorbidities would result in 45,401 extra years of life lived and 150,950 extra PALYs. This resulted in more than AU$25 billion of gained gross domestic product over the lifetime of the working population. Our study highlights the substantial burden of OSA on the Australian population and the need to tailor interventions at the population level to reduce the health and economic impacts.

Decreased psychomotor vigilance is a risk factor for motor vehicle crashes irrespective of subjective daytime sleepiness: the Toon Health Study

STUDY OBJECTIVES

Although excessive daytime sleepiness (EDS) has a crucial impact on motor vehicle crashes (MVCs), the assessment of subjective sleepiness as a screening tool for MVC has limitations. Objective daytime sleepiness may be a better predictor of MVCs rather than subjective daytime sleepiness. Therefore, we aimed to examine the association of psychomotor vigilance as a surrogate marker of objective sleepiness and subjective sleepiness with MVCs in a prospective cohort study of the general population.

METHODS

The study participants were 903 community-dwelling Japanese followed up 5 years after baseline and ascertained history of MVC over the study period. Psychomotor vigilance was measured by the psychomotor vigilance test and categorized into quartiles by the reciprocal of the mean reaction time (mean1/RT). Subjective EDS was defined using the Japanese version of the Epworth Sleepiness Scale. Multivariable logistic regression analysis was used to examine the association between mean1/RT and MVC after stratification by subjective EDS.

RESULTS

The multivariable-adjusted odds ratio (95% confidence interval) for MVC among the highest quartile group of mean1/RT was 0.31 (0.17-0.57), compared with the lowest group (P for trend < .01). After stratification by subjective EDS, the significant association was found only among the nonsubjective EDS group (P for trend < .01) and not among the subjective EDS group (P for trend = .16).

CONCLUSIONS

Decreased psychomotor vigilance measured by the psychomotor vigilance test was associated with a higher risk of MVCs, and the association was more evident among the nonsubjective EDS group. The psychomotor vigilance test may be useful to prevent sleep-related MVCs in the general population, particularly for individuals without subjective EDS.

CITATION

Matsuo R, Tanigawa T, Oshima A, et al. Decreased psychomotor vigilance is a risk factor for motor vehicle crashes irrespective of subjective daytime sleepiness: the Toon Health Study. J Clin Sleep Med. 2023;19(2):319-325.

Methodologies and Wearable Devices to Monitor Biophysical Parameters Related to Sleep Dysfunctions: An Overview

Sleep is crucial for human health from metabolic, mental, emotional, and social points of view; obtaining good sleep in terms of quality and duration is fundamental for maintaining a good life quality. Over the years, several systems have been proposed in the scientific literature and on the market to derive metrics used to quantify sleep quality as well as detect sleep disturbances and disorders. In this field, wearable systems have an important role in the discreet, accurate, and long-term detection of biophysical markers useful to determine sleep quality. This paper presents the current state-of-the-art wearable systems and software tools for sleep staging and detecting sleep disorders and dysfunctions. At first, the paper discusses sleep's functions and the importance of monitoring sleep to detect eventual sleep disturbance and disorders. Afterward, an overview of prototype and commercial headband-like wearable devices to monitor sleep is presented, both reported in the scientific literature and on the market, allowing unobtrusive and accurate detection of sleep quality markers. Furthermore, a survey of scientific works related the effect of the COVID-19 pandemic on sleep functions, attributable to both infection and lifestyle changes. In addition, a survey of algorithms for sleep staging and detecting sleep disorders is introduced based on an analysis of single or multiple biosignals (EEG-electroencephalography, ECG-electrocardiography, EMG-electromyography, EOG-electrooculography, etc.). Lastly, comparative analyses and insights are provided to determine the future trends related to sleep monitoring systems.

Physiological markers of sleep quality: A scoping review

Understanding the associations between adequate sleep, performance and health outcomes is vital, yet a major limitation in the design and interpretation of studies of sleep and performance is the variability of subjective and objective markers used to assess sleep quality. The aim of this scoping review is to investigate how various physiological signals recorded during sleep or wakefulness relate to objective measures of cognitive or physical performance and subjectively perceived sleep quality to inform conceptual understanding of the elusive, amorphous, and multi-dimensional construct of sleep quality. We also aimed to suggest priorities for future areas of research in sleep quality and performance. We searched six databases ultimately yielding 439 studies after duplicate removal. Sixty-five studies were selected for full review. In general, correlations between objectively measured sleep and objective performance or subjectively assessed sleep quality were weak to moderate. Slow wave sleep was moderately correlated with better performance on tasks of vigilance, motor speed, and executive function as well as better subjective sleep quality and feeling well-rested, suggesting that slow wave sleep may be important for sleep quality and optimal daytime performance. However, these findings were inconsistent across studies. Increased sleep fragmentation was associated with poorer subjective sleep quality in both polysomnographic and actigraphic studies. Studies which simultaneously assessed physiologic sleep measures, performance measures and subjective sleep perception were few, limiting the ability to evaluate correlations between subjective and objective outcomes concurrently in the same individuals. Factors influencing the relationship between sleep quality and performance include circadian variability, sleep inertia, and mismatch between sleep stages studied and outcome measures of choice. Ultimately, the determination of "quality sleep" remains largely subjective and inconsistently quantifiable by current measures. Methods evaluating sleep as a continuous measure rather than traditional sleep stages may provide an intriguing approach to future studies of sleep and performance. Future well-designed studies using novel measures of sleep or multimodal ambulatory wearables assessing the three domains of sleep and performance (objective sleep physiology, objective performance, and subjective sleep quality) are needed to better define quality sleep.

Sleep and circadian informatics data harmonization: a workshop report from the Sleep Research Society and Sleep Research Network

The increasing availability and complexity of sleep and circadian data are equally exciting and challenging. The field is in constant technological development, generating better high-resolution physiological and molecular data than ever before. Yet, the promise of large-scale studies leveraging millions of patients is limited by suboptimal approaches for data sharing and interoperability. As a result, integration of valuable clinical and basic resources is problematic, preventing knowledge discovery and rapid translation of findings into clinical care. To understand the current data landscape in the sleep and circadian domains, the Sleep Research Society (SRS) and the Sleep Research Network (now a task force of the SRS) organized a workshop on informatics and data harmonization, presented at the World Sleep Congress 2019, in Vancouver, Canada. Experts in translational informatics gathered with sleep research experts to discuss opportunities and challenges in defining strategies for data harmonization. The goal of this workshop was to fuel discussion and foster innovative approaches for data integration and development of informatics infrastructure supporting multi-site collaboration. Key recommendations included collecting and storing findable, accessible, interoperable, and reusable data; identifying existing international cohorts and resources supporting research in sleep and circadian biology; and defining the most relevant sleep data elements and associated metadata that could be supported by early integration initiatives. This report introduces foundational concepts with the goal of facilitating engagement between the sleep/circadian and informatics communities and is a call to action for the implementation and adoption of data harmonization strategies in this domain.

Sleep Deficiency: Epidemiology and Effects

Adequate sleep is an important pillar of physical and mental health. Sleep deficiency, resulting from short sleep or suboptimal sleep quality, is highly prevalent in modern society. Occupation, social demands, psychiatric disorders, physical disorders, and sleep disorders are some of the contributing factors to sleep deficiency. Some populations are at increased risk of sleep deficiency based on ethnicity, age, marital status, sex, and hospitalization. Sleep deficiency influences cognition, alertness, mood, behavior, diabetes, cardiovascular health, renal function, immune system, and respiratory physiology. This review summarizes the epidemiology and effects of sleep deficiency.

Relationship Between Poor Sleep Quality and Injury Experience in Korea

To develop preventive policies to reduce injuries, the responsible factors should be identified. In this study, causative factors were identified by analyzing data from the Korean Community Health Survey. Logistic regression was used to analyze the data of 192 480 individuals in the survey. Correlations were found between the injury experience and the following socioeconomic factors: age, sex, monthly income, smoking status, education, marital status, and neuropsychiatric factors: depressive symptoms, cognitive decline, and stress. The study subjects were divided into two groups based on sleep quality, as determined by Pittsburgh Sleep Quality Indices of ≤5 or >5. Logistic regression analysis adjusted for potential confounders revealed a correlation between sleep quality and injury experience. The odds ratio (OR) of poor sleep quality was associated with higher odds of injury (OR: 1.26, 95% confidence interval [1.19, 1.34]), and it was also associated with higher odds of severe injury (OR: 1.23, 95% confidence interval [1.15, 1.32]), even in the adjustment of socioeconomic factors only as well as in the adjustment of socioeconomic and neuropsychiatric factors. Poor sleep quality was associated with higher odds of several injury mechanisms of severe injury, such as slipping, poisoning, and falling into water.

Prevalence, Trends, and Correlates of Joint Patterns of Aerobic and Muscle-Strengthening Activity and Sleep Duration: A Pooled Analysis of 359,019 Adults in the National Health Interview Survey 2004-2018

BACKGROUND

Physical activity (PA) and sleep duration have established associations with health outcomes individually but tend to co-occur and may be better targeted jointly. This study aimed to describe the cross-sectional prevalence, trends, and population characteristic correlates of activity-sleep patterns in a population-representative sample of US adults from the National Health Interview Survey (2004-2018).

METHODS

Participants (N = 359,019) self-reported aerobic and muscle-strengthening activity and sleep duration. They were categorized as "meeting both"/"meeting PA only"/"meeting sleep only"/"meeting neither" of the 2018 US PA guidelines and age-based sleep duration recommendations. Trends in activity-sleep patterns were analyzed using weighted multinomial logistic regression, and correlates were identified using weighted binary Poisson regressions, with P ≤ .001 considered significant.

RESULTS

"Meet sleep only" was most prevalent (46.4%) by 2018, followed by "meet neither" (30.3%), "meet both" (15.6%), and "meet PA only" (7.7%). Many significant sociodemographic, biological, and health-behavior correlates of the activity-sleep groups were identified, and the direction and magnitude of these associations differed between groups.

CONCLUSIONS

Public health campaigns should emphasize the importance of both sufficient PA and sleep; target women and older adults, current smokers, and those with lower education and poorer physical and mental health; and consider specific barriers experienced by minority ethnic groups.

Rapamycin ameliorates chronic intermittent hypoxia and sleep deprivation-induced renal damage via the mammalian target of rapamycin (mTOR)/NOD-like receptor protein 3 (NLRP3) signaling pathway

Rapamycin inhibits the activation of NOD-like receptor protein 3 (NLRP3) by regulating the mammalian target of rapamycin (mTOR) to treat obstructive sleep apnea-related renal injury. Sleep deprivation (SD) and chronic intermittent hypoxia (CIH) mouse models were used to assess the effects of autophagy in vivo. Compared with the control, SD, and CIH groups, the SD+CIH group had lower body weight and higher levels of blood urea nitrogen (BUN), creatinine, and urinary albumin (U-Alb) (P < 0.05); renal injury and oxidative damage occurred in the SD+CIH group, the kidney cell nucleus ruptured, and morphological structure of the cells was unclear in the SD+CIH group. The SD+CIH group demonstrated increased apoptosis compared with the control, SD, and CIH groups using Western blot analysis. Compared to the control, SD, and CIH groups, the SD+CIH group showed a higher degree of microtubule-associated protein light chain 3\ staining. Compared to the SD+CIH group, BUN, creatinine, and U-Alb levels decreased, and apoptosis increased in the SD+CIH+rapamycin group, and the structure of the kidney after rapamycin treatment was well preserved. The mTOR expression was increased in the kidneys of the SD+CIH group. The NLRP3, Gasdermin D (GMDSD), interleukin (IL)-18, IL-1β, and cleaved-caspase-1 protein levels were higher in the SD+CIH group than the SD+CIH+rapamycin group, and the NLRP3, GMDSD, IL-18, IL-1β, and cleaved-caspase-1 mRNA levels were higher in the SD+CIH group than the SD+CIH+rapamycin group. Following rapamycin treatment, pyroptosis was suppressed. Rapamycin ameliorates renal damage by inhibiting the mTOR/NLRP3 signaling pathway.

Abnormal Spontaneous Brain Activity and Cognitive Impairment in Obstructive Sleep Apnea

PURPOSE

This study aimed to explore the alterations in spontaneous brain activity in obstructive sleep apnea (OSA) using percent amplitude of fluctuation (PerAF) and investigate the relationship between abnormal spontaneous brain activity and cognitive impairment in OSA.

PATIENTS AND METHODS

Overall, 52 patients with moderate to severe OSA and 61 healthy controls (HCs) were eventually enrolled in this study. All participants underwent resting-state functional magnetic resonance (rs-fMRI) and T1-weighted imaging. The PerAF was calculated and compared between patients with OSA and HCs, with voxel level P < 0.001 and cluster level P < 0.05 corrected with Gaussian Random Field was be considered statistically different. A partial correlation analysis was used to assess the relationship between altered PerAF and clinical assessments in patients with OSA.

RESULTS

Compared to HCs, patients with OSA had significantly lower PerAF values in the right rectal gyrus and left superior frontal gyrus, but higher PerAF values in the right cerebellum posterior lobe and left middle frontal gyrus. The PerAF values of some specific regions in patients with OSA correlated with sleep efficiency and Montreal Cognitive Assessment scores. Additionally, support vector machine analysis showed that PerAF values in all differential brain regions could differentiate patients with OSA from HCs with good accuracy.

CONCLUSION

Specific brain areas in OSA patients may exhibit aberrant neuronal activity, and these anomalies may be linked to decreased cognitive performance. This discovery offers fresh perspectives on these patients' neurocognition.

Relevance of Sleep Disturbances to Orthopaedic Surgery: A Current Concepts Narrative and Practical Review

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Sleep disturbances can increase the risk of falls and motor vehicle accidents and may reduce bone density.

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Poor sleep can lead to worse outcomes after fracture, such as chronic pain and delayed recovery.

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Orthopaedic surgeons can play an important role in the screening of sleep disorders among their patients.

Concordance of multiple methods to define resiliency and vulnerability to sleep loss depends on Psychomotor Vigilance Test metric

STUDY OBJECTIVES

Sleep restriction (SR) and total sleep deprivation (TSD) reveal well-established individual differences in Psychomotor Vigilance Test (PVT) performance. While prior studies have used different methods to categorize such resiliency/vulnerability, none have systematically investigated whether these methods categorize individuals similarly.

METHODS

41 adults participated in a 13-day laboratory study consisting of 2 baseline, 5 SR, 4 recovery, and one 36h TSD night. The PVT was administered every 2h during wakefulness. Three approaches (Raw Score [average SR performance], Change from Baseline [average SR minus average baseline performance], and Variance [intraindividual variance of SR performance]), and within each approach, six thresholds (±1 standard deviation and the best/worst performing 12.5%, 20%, 25%, 33%, and 50%) classified Resilient/Vulnerable groups. Kendall's tau-b correlations examined the concordance of group categorizations of approaches within and between PVT lapses and 1/reaction time (RT). Bias-corrected and accelerated bootstrapped t-tests compared group performance.

RESULTS

Correlations comparing the approaches ranged from moderate to perfect for lapses and zero to moderate for 1/RT. Defined by all approaches, the Resilient groups had significantly fewer lapses on nearly all study days. Defined by the Raw Score approach only, the Resilient groups had significantly faster 1/RT on all study days. Between-measures comparisons revealed significant correlations between the Raw Score approach for 1/RT and all approaches for lapses.

CONCLUSION

The three approaches defining vigilant attention resiliency/vulnerability to sleep loss resulted in groups comprised of similar individuals for PVT lapses but not for 1/RT. Thus, both method and metric selection for defining vigilant attention resiliency/vulnerability to sleep loss is critical.

Altered hippocampal transcriptome dynamics following sleep deprivation

Widespread sleep deprivation is a continuing public health problem in the United States and worldwide affecting adolescents and adults. Acute sleep deprivation results in decrements in spatial memory and cognitive impairments. The hippocampus is vulnerable to acute sleep deprivation with changes in gene expression, cell signaling, and protein synthesis. Sleep deprivation also has long lasting effects on memory and performance that persist after recovery sleep, as seen in behavioral studies from invertebrates to humans. Although previous research has shown that acute sleep deprivation impacts gene expression, the extent to which sleep deprivation affects gene regulation remains unknown. Using an unbiased deep RNA sequencing approach, we investigated the effects of acute sleep deprivation on gene expression in the hippocampus. We identified 1,146 genes that were significantly dysregulated following sleep deprivation with 507 genes upregulated and 639 genes downregulated, including protein coding genes and long non-coding RNAs not previously identified as impacted by sleep deprivation. Notably, genes significantly upregulated after sleep deprivation were associated with RNA splicing and the nucleus. In contrast, downregulated genes were associated with cell adhesion, dendritic localization, the synapse, and postsynaptic membrane. Furthermore, we found through independent experiments analyzing a subset of genes that three hours of recovery sleep following acute sleep deprivation was sufficient to normalize mRNA abundance for most genes, although exceptions occurred for some genes that may affect RNA splicing or transcription. These results clearly demonstrate that sleep deprivation differentially regulates gene expression on multiple transcriptomic levels to impact hippocampal function.

Landscape of biomedical informatics standards and terminologies for clinical sleep medicine research: A systematic review

A systematic literature review was conducted to understand the current landscape of standards and terminologies used in clinical sleep medicine. Literature search on PubMed, EMBASE, Medline and Web of Science was performed in March 2021 using terms related to sleep, terminologies, standards, harmonization, semantics, ontology, and electronic health records (EHR). Systematic review was carried out according to PRISMA. Among 128 included studies, 35 were eligible for review. Articles were broadly classified into six topics: standard terminology efforts, reporting standards, databases and resources, data integration efforts, EHR abstraction and standards for automated sleep scoring. This review highlights the progress and challenges related to establishing computable terminologies in sleep medicine, and identifies gaps, limitations and research opportunities related to data integration that could improve adoption of clinical research informatics in this field. There is a need for the systematic adoption of standardized terminologies in all areas of sleep medicine. Existing data aggregation resources could be leveraged to support the development of an integrated infrastructure and subsequent deployment in EHR systems within sleep centers. Ultimately, the adoption of standardized practices for documenting sleep disorders and related traits facilitates data sharing, thus accelerating discovery and clinical translation of informatics approaches applied to sleep medicine.

Residual excessive daytime sleepiness in patients treated for obstructive sleep apnea: guidance for assessment, diagnosis, and management

Excessive daytime sleepiness (EDS) affects approximately half of patients with obstructive sleep apnea (OSA) and can persist in some despite normalization of breathing, oxygenation, and sleep quality with primary OSA therapy, such as continuous positive airway pressure (CPAP). EDS is often overlooked and under discussed in the primary care setting and in the follow-up of CPAP-treated patients due to difficult assessment of such a multi-dimensional symptom. This review aims to provide suggestions for procedures that can be implemented into routine clinical practice to identify, evaluate, and manage EDS in patients treated for OSA, including how to appropriately use various self-report and objective assessments along the clinical pathway and options for pharmacotherapy. In addition, examples of when it is appropriate to refer a patient to a sleep specialist for evaluation are discussed.

Obstructive sleep apnea and risk of motor vehicle accident

OBJECTIVE

To evaluate the association between obstructive sleep apnea (OSA) and risk of motor vehicle accident (MVA).

METHODS

We conducted a cohort study at Kaiser Permanente Washington using electronic health plan data and linked Washington State Department of Transportation MVA records. We included persons 18-79 years of age during 2005-2014. OSA was ascertained via diagnosis codes. The primary outcome, first MVA during cohort follow-up, was ascertained from state MVA records. Risk factors for MVAs, including medical conditions and medication use, were ascertained from health plan data. Multivariable Cox proportional hazards models were used to estimate the adjusted hazard ratio (HR) and 95% confidence interval (CI) for the association between OSA and study outcomes.

RESULTS

Among the 879,547 eligible persons, the unadjusted rate of MVA in those with and without OSA was 238 and 229 per 10,000 person-years, respectively. A diagnosis of OSA was associated with a 17% increased risk of MVA (adjusted HR = 1.17; 95% CI: 1.13 to 1.20).

CONCLUSION

In this large population-based study, a diagnosis of OSA was associated with a modestly increased risk of MVA.

Metrics of sleep apnea severity: beyond the apnea-hypopnea index

Obstructive sleep apnea (OSA) is thought to affect almost 1 billion people worldwide. OSA has well established cardiovascular and neurocognitive sequelae, although the optimal metric to assess its severity and/or potential response to therapy remains unclear. The apnea-hypopnea index (AHI) is well established; thus, we review its history and predictive value in various different clinical contexts. Although the AHI is often criticized for its limitations, it remains the best studied metric of OSA severity, albeit imperfect. We further review the potential value of alternative metrics including hypoxic burden, arousal intensity, odds ratio product, and cardiopulmonary coupling. We conclude with possible future directions to capture clinically meaningful OSA endophenotypes including the use of genetics, blood biomarkers, machine/deep learning and wearable technologies. Further research in OSA should be directed towards providing diagnostic and prognostic information to make the OSA diagnosis more accessible and to improving prognostic information regarding OSA consequences, in order to guide patient care and to help in the design of future clinical trials.

Sleepiness Behind the Wheel and the Implementation of European Driving Regulations

Sleep disturbance and sleepiness are established risk factors for driving accidents and obstructive sleep apnea (OSA) is the most prevalent medical disorder associated with excessive daytime sleepiness. Because effective treatment of OSA reduces accident risk, several jurisdictions have implemented regulations concerning the ability of patients with OSA to drive, unless effectively treated. This review provides a practical guide for clinicians who may be requested to certify a patient with OSA as fit to drive regarding the scope of the problem, the role of questionnaires and driving simulators to evaluate sleepiness, and the benefit of treatment on accident risk.

Use of multilevel modeling to examine variability of distracted driving behavior in naturalistic driving studies

Current methods of analyzing data from naturalistic driving studies provide important insights into real-world safety-related driving behaviors, but are limited in the depth of information they currently offer. Driving measures are frequently collapsed to summary levels across the study period, excluding more fine-grained differences such as changes that occur from trip to trip. By retaining trip-specific data, it is possible to quantify how much a driver differs from trip to trip (within-person variability) in addition to how he or she differs from other drivers (between-person variability). To the authors' knowledge, the current study is the first to use multilevel modeling to quantify variability in distracted driving behavior in a naturalistic dataset of older drivers. The current study demonstrates the utility of examining within-person variability in a naturalistic driving dataset of 68 older drivers across two weeks. First, multilevel models were conducted for three distracted driving behaviors to distinguish within-person variability from between-person variability in these behaviors. A high percentage of variation in distracted driving behaviors was attributable to within-person differences, indicating that drivers' behaviors varied more across their own driving trips than from other drivers (ICCs = .93). Then, to demonstrate the utility of personal characteristics in predicting daily driving behavior, a hypothetical model is presented using simulated daily sleep duration from the previous night to predict distracted driving behavior the following day. The current study demonstrates substantial variability in driving behaviors within an older adult sample and the promise of individual characteristics to provide better prediction of driving behaviors relevant to safety, which can be applied in investigations of current naturalistic driving datasets and in designing future studies.

Fluoride exposure and duration and quality of sleep in a Canadian population-based sample

BACKGROUND

Fluoride from dietary and environmental sources may concentrate in calcium-containing regions of the body such as the pineal gland. The pineal gland synthesizes melatonin, a hormone that regulates the sleep-wake cycle. We examined associations between fluoride exposure and sleep outcomes among older adolescents and adults in Canada.

METHODS

We used population-based data from Cycle 3 (2012-2013) of the Canadian Health Measures Survey. Participants were aged 16 to 79 years and 32% lived in communities supplied with fluoridated municipal water. Urinary fluoride concentrations were measured in spot samples and adjusted for specific gravity (UF_SG; n = 1303) and water fluoride concentrations were measured in tap water samples among those who reported drinking tap water (n = 1016). We used multinomial and ordered logistic regression analyses (using both unweighted and survey-weighted data) to examine associations of fluoride exposure with self-reported sleep outcomes, including sleep duration, frequency of sleep problems, and daytime sleepiness. Covariates included age, sex, ethnicity, body mass index, chronic health conditions, and household income.

RESULTS

Median (IQR) UF_SG concentration was 0.67 (0.63) mg/L. Median (IQR) water fluoride concentration was 0.58 (0.27) mg/L among participants living in communities supplied with fluoridated municipal water and 0.01 (0.06) mg/L among those living in non-fluoridated communities. A 0.5 mg/L higher water fluoride level was associated with 34% higher relative risk of reporting sleeping less than the recommended duration for age [unweighted: RRR = 1.34, 95% CI: 1.03, 1.73; p = .026]; the relative risk was higher, though less precise, using survey-weighted data [RRR = 1.96, 95% CI: 0.99, 3.87; p = .05]. UF_SG was not significantly associated with sleep duration. Water fluoride and UF_SG concentration were not significantly associated with frequency of sleep problems or daytime sleepiness.

CONCLUSIONS

Fluoride exposure may contribute to sleeping less than the recommended duration among older adolescents and adults in Canada.

Validation of the STOP-Bang questionnaire for screening of obstructive sleep apnea in the general population and commercial drivers: a systematic review and meta-analysis

Purpose

Obstructive sleep apnea (OSA) is a critical occupational health concern, but is often undiagnosed in the general population and commercial drivers. The STOP-Bang questionnaire is a simple, reliable tool to screen for OSA, which could improve public health in a cost-effective manner. The objective of this systematic review and meta-analysis is to assess the validity of the STOP-Bang questionnaire to detect OSA in these key populations.

Methods

We searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, PsycINFO, Journals @ Ovid, Web of Science, Scopus, and CINAHL for relevant articles from 2008 to March 2020. The quality of studies was appraised using Cochrane Methods criteria. To calculate pooled predictive parameters, we created 2 × 2 contingency tables and performed random-effects meta-analyses.

Results

Of 3871 citations, five studies that evaluated STOP-Bang in the general population (n = 8585) and two in commercial drivers (n = 185) were included. In the general population, prevalence of all OSA (AHI ≥ 5), moderate-to-severe OSA (AHI ≥ 15), and severe OSA (AHI ≥ 30) was 57.6%, 21.3%, and 7.8% respectively. In commercial drivers, the prevalence of moderate-to-severe OSA was 37.3%. The trends of high sensitivity and negative predictive value of a STOP-Bang score ≥ 3 illustrates that the questionnaire helps detect and rule out clinically significant OSA in the general population and commercial drivers.

Conclusion

This meta-analysis demonstrates that the STOP-Bang questionnaire is a valid and effective screening tool for OSA in the general population and commercial drivers.

Trial registration

PROSPERO No. CRD42020200379; 08/22/2020

Supplementary Information

The online version contains supplementary material available at 10.1007/s11325-021-02299-y.