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Sleep Medicine May 2022The role of the sleep environment and presleep conditions that may influence adolescents' sleep are understudied. The aims of the current study were to examine linear...
OBJECTIVE/BACKGROUND
The role of the sleep environment and presleep conditions that may influence adolescents' sleep are understudied. The aims of the current study were to examine linear and nonlinear associations between the sleep environment and presleep conditions and adolescents' daytime sleepiness and sleep/wake problems.
METHOD
Participants included 313 adolescents (M = 17.39 years, SD = 10.38 months; 51.4% girls, 48.6% boys; 59.1% White/European American, 40.3% Black/African American) from a wide range of socioeconomic backgrounds living in the southeastern United States. Adolescents completed surveys assessing the sleep environment (eg, light, bedding), four presleep conditions (ie, general worries, family concerns, arousal, somatic complaints), and sleep (daytime sleepiness, sleep/wake problems).
RESULTS
Sleep environment disruptions and worse presleep conditions were positively associated with sleepiness and sleep/wake problems in a linear fashion. Nonlinear associations emerged such that levels of sleepiness increased rapidly between low and average levels of the sleep environment and two presleep conditions (worries, arousal); the slope leveled off between average and high levels. Moreover, linear effects of environmental disruptions, family concerns, somatic complaints, and presleep arousal on sleep/wake problems were moderated by race and/or SES, indicating that positive associations between some presleep conditions and sleep/wake problems were more pronounced for Black and lower SES youth.
CONCLUSIONS
Results support the importance of the sleep environment and multiple presleep conditions and assessments of both linear and nonlinear effects for a better understanding of factors that may contribute to sleep. Additionally, results indicate the sleep environment and some presleep conditions may be more consequential for disadvantaged youth.
Topics: Adolescent; Disorders of Excessive Somnolence; Female; Humans; Male; Sleep; Sleep Initiation and Maintenance Disorders; Sleep Wake Disorders; Sleepiness; Social Class
PubMed: 34879983
DOI: 10.1016/j.sleep.2021.11.004 -
PloS One 2023Driver drowsiness is a widely recognized cause of motor vehicle accidents. Therefore, a reduction in drowsy driving crashes is required. Many studies evaluating the...
Driver drowsiness is a widely recognized cause of motor vehicle accidents. Therefore, a reduction in drowsy driving crashes is required. Many studies evaluating the crash risk of drowsy driving and developing drowsiness detection systems, have used observer rating of drowsiness (ORD) as a reference standard (i.e. ground truth) of drowsiness. ORD is a method of human raters evaluating the levels of driver drowsiness, by visually observing a driver. Despite the widespread use of ORD, concerns remain regarding its convergent validity, which is supported by the relationship between ORD and other drowsiness measures. The objective of the present study was to validate video-based ORD, by examining correlations between ORD levels and other drowsiness measures. Seventeen participants performed eight sessions of a simulated driving task, verbally responding to Karolinska sleepiness scale (KSS), while infra-red face video, lateral position of the participant's car, eye closure, electrooculography (EOG), and electroencephalography (EEG) were recorded. Three experienced raters evaluated the ORD levels by observing facial videos. The results showed significant positive correlations between the ORD levels and all other drowsiness measures (i.e., KSS, standard deviation of the lateral position of the car, percentage of time occupied by slow eye movement calculated from EOG, EEG alpha power, and EEG theta power). The results support the convergent validity of video-based ORD as a measure of driver drowsiness. This suggests that ORD might be suitable as a ground truth for drowsiness.
Topics: Humans; Automobile Driving; Sleepiness; Wakefulness; Accidents, Traffic; Eye Movements; Electroencephalography; Sleep Stages
PubMed: 37155637
DOI: 10.1371/journal.pone.0285557 -
Multiple Sclerosis and Related Disorders Sep 2022Cognitive fatigue (CF) is a disabling symptom frequently reported by patients with Multiple Sclerosis (pwMS). Whether pwMS in the early disease stages present an...
CONTEXT
Cognitive fatigue (CF) is a disabling symptom frequently reported by patients with Multiple Sclerosis (pwMS). Whether pwMS in the early disease stages present an increased sensitivity to fatigue induction remains debated. Objective measures of CF have been validated neither for clinical nor research purposes. This study aimed at (i) assessing how fatigue induction by manipulation of cognitive load affects subjective fatigue and behavioural performance in newly diagnosed pwMS and matched healthy controls (HC); and (ii) exploring the relevance of eye metrics to describe CF in pwMS.
METHODS
Nineteen pwMS with disease duration < 5 years and 19 matched HC participated to this study. CF was induced with a dual-task in two separate sessions with varying cognitive load (High and Low cognitive load conditions, HCL and LCL). Accuracy, reaction times (RTs), subjective fatigue and sleepiness states were assessed. Bayesian Analyses of Variance for repeated measures (rmANOVA) explored the effects of time, group and load condition on the assessed variables. Eye metrics (number of long blinks, pupil size and pupil response speed: PRS) were obtained during the CF task for a sub-sample (16 pwMS and 15 HC) and analysed with Generalized Linear Mixed Models (GLMM).
RESULTS
Performance (accuracy and RTs) was lower in the HCL condition and accuracy decreased over time (BFs > 100) while RTs did not significantly vary. Performance over task and conditions followed the same pattern of evolution across groups (BFs < 0.08) suggesting that pwMS did not show increased alteration of performance during fatigue induction. Regarding subjective state, both fatigue and sleepiness increased following the task (BFs > 15), regardless of condition and group (BFs < 3). CF in pwMS seems to be associated with PRS, as PRS decreased during the task amongst pwMS only and especially in the HCL condition (all p < .05). A significant Condition*Group interaction was observed regarding long blinks (p < .0001) as well as an expected effect of cognitive load condition on pupil diameter (p < .01).
CONCLUSION
These results suggest that newly diagnosed pwMS and HC behave similarly during fatigue induction, in terms of both performance decrement and accrued fatigue sensation. Eye metric data further reveal a susceptibility to CF in pwMS, which can be objectively measured.
Topics: Bayes Theorem; Cognition; Fatigue; Humans; Multiple Sclerosis; Pupil; Reaction Time; Sleepiness
PubMed: 35803086
DOI: 10.1016/j.msard.2022.104001 -
The Impact of Dietary Factors on the Sleep of Athletically Trained Populations: A Systematic Review.Nutrients Aug 2022Many athletic populations report poor sleep, especially during intensive training and competition periods. Recently, diet has been shown to significantly affect sleep in... (Review)
Review
Many athletic populations report poor sleep, especially during intensive training and competition periods. Recently, diet has been shown to significantly affect sleep in general populations; however, little is known about the effect diet has on the sleep of athletically trained populations. With sleep critical for optimal recovery and sports performance, this systematic review aimed to evaluate the evidence demonstrating that dietary factors influence the sleep of athletically trained populations. Four electronic databases were searched from inception to May 2022, with primary research articles included if they contained a dietary factor(s), an outcome measure of sleep or sleepiness, and participants could be identified as ‘athletically trained’. Thirty-five studies were included, with 21 studies assessed as positive quality, 13 as neutral, and one as negative. Sleep or sleepiness was measured objectively in 46% of studies (n = 16). The review showed that evening (≥5 p.m.) caffeine intakes >2 mg·kg−1 body mass decreased sleep duration and sleep efficiency, and increased sleep latency and wake after sleep onset. Evening consumption of high glycaemic index carbohydrates and protein high in tryptophan may reduce sleep latency. Although promising, more research is required before the impact of probiotics, cherry juice, and beetroot juice on the sleep of athletes can be resolved. Athletic populations experiencing sleep difficulties should be screened for caffeine use and trial dietary strategies (e.g., evening consumption of high GI carbohydrates) to improve sleep.
Topics: Athletes; Athletic Performance; Caffeine; Carbohydrates; Humans; Sleep; Sleep Initiation and Maintenance Disorders; Sleepiness
PubMed: 36014779
DOI: 10.3390/nu14163271 -
Sleep Jun 2022Conventional metrics of sleep quantity/depth have serious shortcomings. Odds-Ratio-Product (ORP) is a continuous metric of sleep depth ranging from 0 (very deep sleep)...
STUDY OBJECTIVES
Conventional metrics of sleep quantity/depth have serious shortcomings. Odds-Ratio-Product (ORP) is a continuous metric of sleep depth ranging from 0 (very deep sleep) to 2.5 (full-wakefulness). We describe an ORP-based approach that provides information on sleep disorders not apparent from traditional metrics.
METHODS
We analyzed records from the Sleep-Heart-Health-Study and a study of performance deficit following sleep deprivation. ORP of all 30-second epochs in each PSG and percent of epochs in each decile of ORPs range were calculated. Percentage of epochs in deep sleep (ORP < 0.50) and in full-wakefulness (ORP > 2.25) were each assigned a rank, 1-3, representing first and second digits, respectively, of nine distinct types ("1,1", "1,2" … "3,3"). Prevalence of each type in clinical groups and their associations with demographics, sleepiness (Epworth-Sleepiness-Scale, ESS) and quality of life (QOL; Short-Form-Health-Survey-36) were determined.
RESULTS
Three types ("1,1", "1,2", "1,3") were prevalent in OSA and were associated with reduced QOL. Two ("1,3" and "2,3") were prevalent in insomnia with short-sleep-duration (insomnia-SSD), but only "1,3" was associated with poor sleep depth and reduced QOL, suggesting two phenotypes in insomnia-SSD. ESS was high in types "1,1" and "1,2", and low in "1,3" and "2,3". Prevalence of some types increased with age while in others it decreased. Other types were either rare ("1,1" and "3,3") or high ("2,2") at all ages.
CONCLUSIONS
The proposed ORP histogram offers specific and unique information on the underlying neurophysiological characteristics of sleep disorders not captured by routine metrics, with potential of advancing diagnosis and management of these disorders.
Topics: Humans; Outcome Assessment, Health Care; Prevalence; Quality of Life; Sleep; Sleep Apnea, Obstructive; Sleep Initiation and Maintenance Disorders; Sleep Wake Disorders; Sleepiness
PubMed: 35272350
DOI: 10.1093/sleep/zsac059 -
Sensors (Basel, Switzerland) Mar 2020Driver drowsiness and stress are major causes of traffic deaths and injuries, which ultimately wreak havoc on world economic loss. Researchers are in full swing to...
Driver drowsiness and stress are major causes of traffic deaths and injuries, which ultimately wreak havoc on world economic loss. Researchers are in full swing to develop various algorithms for both drowsiness and stress recognition. In contrast to existing works, this paper proposes a generic model using multiple-objective genetic algorithm optimized deep multiple kernel learning support vector machine that is capable to recognize both driver drowsiness and stress. This algorithm simplifies the research formulations and model complexity that one model fits two applications. Results reveal that the proposed algorithm achieves an average sensitivity of 99%, specificity of 98.3% and area under the receiver operating characteristic curve (AUC) of 97.1% for driver drowsiness recognition. For driver stress recognition, the best performance is yielded with average sensitivity of 98.7%, specificity of 98.4% and AUC of 96.9%. Analysis also indicates that the proposed algorithm using multiple-objective genetic algorithm has better performance compared to the grid search method. Multiple kernel learning enhances the performance significantly compared to single typical kernel. Compared with existing works, the proposed algorithm not only achieves higher accuracy but also addressing the typical issues of dataset in simulated environment, no cross-validation and unreliable measurement stability of input signals.
Topics: Algorithms; Automobile Driving; Humans; ROC Curve; Sleepiness; Stress, Psychological; Support Vector Machine
PubMed: 32156100
DOI: 10.3390/s20051474 -
Sleep Medicine Oct 2022Coronavirus disease 2019 (COVID-19) represents a global healthcare crisis that has led to morbidity and mortality on an unprecedented scale. While studies on COVID-19... (Review)
Review
Coronavirus disease 2019 (COVID-19) represents a global healthcare crisis that has led to morbidity and mortality on an unprecedented scale. While studies on COVID-19 vaccines are ongoing, the knowledge about the reactogenic symptoms that can occur after vaccination and its generator mechanisms can be critical for healthcare professionals to improve compliance with the future vaccination campaign. Because sleep and immunity are bidirectionally linked, sleepiness or sleep disturbance side effects reported after some of the COVID-19 vaccines advise an academic research line in the context of physiological or pathological neuroimmune interactions. On the recognized basis of inflammatory regulation of hypothalamic neurons in sickness behavior, we hypothesized that IL-1β, INF-γ and TNF-α pro-inflammatory cytokines inhibit orexinergic neurons promoting sleepiness after peripheral activation of the innate immune system induced by the novel COVID-19 vaccines. In addition, based on knowledge of previous vaccines and disease manifestations of SARS-CoV-2 infection, it also suggests that narcolepsy must be included as potential adverse events of particular interest to consider in pharmacovigilance studies.
Topics: COVID-19; COVID-19 Vaccines; Humans; SARS-CoV-2; Sleepiness; Vaccination
PubMed: 35792321
DOI: 10.1016/j.sleep.2022.06.011 -
Proceedings of the National Academy of... Jan 2016Night-shift workers are at high risk of drowsiness-related motor vehicle crashes as a result of circadian disruption and sleep restriction. However, the impact of actual...
Night-shift workers are at high risk of drowsiness-related motor vehicle crashes as a result of circadian disruption and sleep restriction. However, the impact of actual night-shift work on measures of drowsiness and driving performance while operating a real motor vehicle remains unknown. Sixteen night-shift workers completed two 2-h daytime driving sessions on a closed driving track at the Liberty Mutual Research Institute for Safety: (i) a postsleep baseline driving session after an average of 7.6 ± 2.4 h sleep the previous night with no night-shift work, and (ii) a postnight-shift driving session following night-shift work. Physiological measures of drowsiness were collected, including infrared reflectance oculography, electroencephalography, and electrooculography. Driving performance measures included lane excursions, near-crash events, and drives terminated because of failure to maintain control of the vehicle. Eleven near-crashes occurred in 6 of 16 postnight-shift drives (37.5%), and 7 of 16 postnight-shift drives (43.8%) were terminated early for safety reasons, compared with zero near-crashes or early drive terminations during 16 postsleep drives (Fishers exact: P = 0.0088 and P = 0.0034, respectively). Participants had a significantly higher rate of lane excursions, average Johns Drowsiness Scale, blink duration, and number of slow eye movements during postnight-shift drives compared with postsleep drives (3.09/min vs. 1.49/min; 1.71 vs. 0.97; 125 ms vs. 100 ms; 35.8 vs. 19.1; respectively, P < 0.05 for all). Night-shift work increases driver drowsiness, degrading driving performance and increasing the risk of near-crash drive events. With more than 9.5 million Americans working overnight or rotating shifts and one-third of United States commutes exceeding 30 min, these results have implications for traffic and occupational safety.
Topics: Accidents, Traffic; Adult; Automobile Driving; Blinking; Electroencephalography; Electrooculography; Eye Movements; Female; Humans; Male; Middle Aged; Sleep Disorders, Circadian Rhythm; Sleep Stages; United States
PubMed: 26699470
DOI: 10.1073/pnas.1510383112 -
Journal of Neurology Sep 2022To define the boundaries and the overlaps between fatigue, sleepiness and depression in patients with multiple sclerosis (MS) by using different tools for each... (Observational Study)
Observational Study
BACKGROUND AND OBJECTIVES
To define the boundaries and the overlaps between fatigue, sleepiness and depression in patients with multiple sclerosis (MS) by using different tools for each dimension, including instrumental sleep analysis.
METHODS
In this cross-sectional, observational study, 71 MS patients (males/females: 20/51; mean age: 48.9 ± 10.5 years) filled in clinical questionnaires and performed polysomnography followed by maintenance of wakefulness test (MWT). Frequency and reciprocal overlap of sleepiness, fatigue and depression in MS were expressed by Eulero-Venn diagrams; standard multiple regression was used to assess the ability of symptoms to predict each other.
RESULTS
There was a high percentage of fatigued (70%), somnolent (45%) and depressed (27%) patients. Fatigue had the strongest overlap and correlated with both depression (beta: 0.52, p < 0.001) and sleepiness (beta: 0.74, p < 0.001). Somnolence and depression were nearly always accompanied by fatigue and were well differentiated from each other by MWT. Four MS subgroups were identified that had: (1) fatigue only; (2) fatigue and sleepiness (3) fatigue and depression; (4) fatigue, sleepiness and depression.
DISCUSSION
The subjective and objective tools are not able to clearly distinguish fatigue from sleepiness and depression, while only a test of vigilance can be helpful in separating somnolence and depression from each other.
Topics: Adult; Cross-Sectional Studies; Depression; Disorders of Excessive Somnolence; Fatigue; Female; Humans; Male; Middle Aged; Multiple Sclerosis; Sleepiness; Wakefulness
PubMed: 35507053
DOI: 10.1007/s00415-022-11143-6 -
Transplant International : Official... 2023This study aims to describe daytime sleepiness and health-related quality of life (HRQoL) among Lebanese kidney transplant (KT) recipients and to examine the medical,...
This study aims to describe daytime sleepiness and health-related quality of life (HRQoL) among Lebanese kidney transplant (KT) recipients and to examine the medical, psychosocial and transplant factors related to them. It is a cross-sectional multi-center study involving KT recipients >18 years. Daytime sleepiness was assessed using ESS Questionnaire. HRQoL was measured using the SF-36 questionnaire. Social support was self-reported. A multivariable regression analysis evaluated factors associated with daytime sleepiness and HRQoL in our sample. 118 patients were recruited over a 2 years period. Excessive daytime sleepiness was prevalent in 12.7%. It was associated with Diabetes Mellitus (OR 3.97, 95% CI 0.94-16.81, = 0.06) and obesity (OR 1.13, 95% CI 1.02, 1.27, = 0.02). Social support and higher eGFR were associated with better scores on the MCS (β 24.13 < 0.001 and β 0.26 < 0.01) and the PCS (β 15.48 < 0.01 and β 0.22 P 0.02). Conversely, depression and hospitalization were negatively associated with the MCS (β -27.44, < 0.01 and β -9.87, < 0.01) and the PCS (β -0.28.49, < 0.01 and β -10.37, < 0.01).
Topics: Humans; Cross-Sectional Studies; Sleepiness; Kidney Transplantation; Quality of Life; Developing Countries; Disorders of Excessive Somnolence; Surveys and Questionnaires
PubMed: 38020749
DOI: 10.3389/ti.2023.11547