Sleep quality and duration are associated with performance in maximal incremental test

Machine learning predicts peak oxygen uptake and peak power output for customizing cardiopulmonary exercise testing using non-exercise features

PURPOSE

Cardiopulmonary exercise testing (CPET) is considered the gold standard for assessing cardiorespiratory fitness. To ensure consistent performance of each test, it is necessary to adapt the power increase of the test protocol to the physical characteristics of each individual. This study aimed to use machine learning models to determine individualized ramp protocols based on non-exercise features. We hypothesized that machine learning models will predict peak oxygen uptake ( V ˙ O2peak) and peak power output (PPO) more accurately than conventional multiple linear regression (MLR).

METHODS

The cross-sectional study was conducted with 274 (♀168, ♂106) participants who performed CPET on a cycle ergometer. Machine learning models and multiple linear regression were used to predict V ˙ O2peak and PPO using non-exercise features. The accuracy of the models was compared using criteria such as root mean square error (RMSE). Shapley additive explanation (SHAP) was applied to determine the feature importance.

RESULTS

The most accurate machine learning model was the random forest (RMSE: 6.52 ml/kg/min [95% CI 5.21-8.17]) for V ˙ O2peak prediction and the gradient boosting regression (RMSE: 43watts [95% CI 35-52]) for PPO prediction. Compared to the MLR, the machine learning models reduced the RMSE by up to 28% and 22% for prediction of V ˙ O2peak and PPO, respectively. Furthermore, SHAP ranked body composition data such as skeletal muscle mass and extracellular water as the most impactful features.

CONCLUSION

Machine learning models predict V ˙ O2peak and PPO more accurately than MLR and can be used to individualize CPET protocols. Features that provide information about the participant's body composition contribute most to the improvement of these predictions.

TRIAL REGISTRATION NUMBER

DRKS00031401 (6 March 2023, retrospectively registered).

The Clinical Relevance of Autonomic Dysfunction, Cerebral Hemodynamics, and Sleep Interactions in Individuals Living With SCI

A myriad of physiological impairments is seen in individuals after a spinal cord injury (SCI). These include altered autonomic function, cerebral hemodynamics, and sleep. These physiological systems are interconnected and likely insidiously interact leading to secondary complications. These impairments negatively influence quality of life. A comprehensive review of these systems, and their interplay, may improve clinical treatment and the rehabilitation plan of individuals living with SCI. Thus, these physiological measures should receive more clinical consideration. This special communication introduces the under investigated autonomic dysfunction, cerebral hemodynamics, and sleep disorders in people with SCI to stakeholders involved in SCI rehabilitation. We also discuss the linkage between autonomic dysfunction, cerebral hemodynamics, and sleep disorders and some secondary outcomes are discussed. Recent evidence is synthesized to make clinical recommendations on the assessment and potential management of important autonomic, cerebral hemodynamics, and sleep-related dysfunction in people with SCI. Finally, a few recommendations for clinicians and researchers are provided.

Less daytime sleepiness and slow wave activity during sleep predict better physical readiness in military personnel

BACKGROUND

Military personnel must maintain physical performance despite exposure to operational stressors such as sleep loss, caloric restriction and high cognitive load. Habitual sleep and specific sleep features are positively associated with fitness and may contribute to physical performance in operational settings. Further, by affecting muscle recovery, sleep may contribute to the ability to maintain performance across multiple days of exposure to operational stressors.

OBJECTIVES

We examined the role of individual differences in baseline sleep on baseline physical performance and on change in physical performance throughout exposure to simulated military operational stress (SMOS).

METHODS

Military personnel (36 male, 9 female, 26.3 ± 5.3 years) completed a 5-day SMOS protocol during which they completed a tactical mobility test daily. Sleep questionnaires were administered at intake and sleep was monitored each night with polysomnography. Lasso regressions were used to identify meaningful predictors of physical performance at baseline and of change in physical performance across SMOS.

RESULTS

Better aerobic fitness, lower daytime sleepiness (Epworth Sleepiness Scale), and lower absolute slow wave activity (0.5-4 Hz) predicted better physical performance at baseline (66.1% of variance explained), but did not relate to changes in performance.

CONCLUSIONS

Collectively, higher daytime sleepiness and slow wave activity may reflect more chronic exposure to insufficient sleep and higher baseline sleep drive, which in turn led to compromised physical performance. The findings suggest that low self-report sleepiness and low objective slow wave activity may reflect two quantifiable markers of healthy sleep behaviors that have implications for operational performance.

Effect of sleep and fatigue on cardiovascular performance in young, healthy subjects

Physical performance could be negatively affected by sleep deficiency and fatigue. The present study assesses the role of sleep quality, fatigue and motivation on cardiovascular performance (VO₂peak, Wmax, and HRmax) in a sample of active young subjects. The current study is a cross-sectional design. Ninety-six university students (males 54.2%; 21.5 ± 2.9 yrs) completed an incremental exercise test on a bicycle ergometer. Sleep, fatigue, and motivation were assessed with the Pittsburgh Sleep Quality Index and two visual analogue scales, respectively. Differences in VO₂peak, Wmax, HRmax, self-perceived fatigue and motivation were compared between good and bad sleepers and sleep duration >/<7.5 h, while regression analysis defined the predictors of VO₂peak, Wmax, and HRmax_. In the male sample, good and bad sleepers' differences were significant only for self-perceived fatigue (p = 0.04). The female sample showed no statistically significant differences between good and bad sleepers and different sleep durations. In the male sample, linear regression analysis showed a significant inverse correlation between Wmax and the PSQI score (-0.4, p = 0.004). The stepwise regression model indicated that sleep (β = -0.3, p = 0.02) was a significant predictor of VO₂peak in males accounting for 20% of the variance, whereas physical performance seems more affected by fatigue (β = -0.4, p = 0.03) in females. In conclusion, chronic inadequate and self-reported sleep quality seems to be one of the factors compromising cardiovascular performance in males.

Improvements in sleep quality and fatigue are associated with improvements in functional recovery following hospitalization in older adults

Study objectives

Poor sleep quality, a frequent problem in older adults, has been shown to be associated with reduced physical function and wellbeing. However, little is known about the relationship between sleep quality and the recovery of physical function following hospitalization. Thus, we conducted this study to examine the association between sleep quality and functional recovery after an acute hospitalization in community dwelling older adults.

Methods

Older adult patients (N = 23, mean age = 74 ± 9 years) were recruited during an acute hospitalization (average length of stay 3.9 days) with a cardiovascular (56%), pulmonary (22%), or metabolic (13%) admission diagnosis. Objective physical function was measured using the Short Physical Performance Battery (SPPB) and self-reported function was assessed with Katz Index of Independence in Activities of Daily Living (ADL) and Lawton Instrumental Activities of Daily Living Scale (IADL). Sleep quality was measured using Pittsburgh Sleep Quality Index (PSQI) global score and Iowa Fatigue Score (IFS). Testing was performed prior to discharge (baseline) and 4-weeks post-discharge (follow-up).

Results

Regression models showed PSQI Subjective Sleep Quality change scores from baseline to 4-week follow-up predicted a change in ADL (β = -0.22); PSQI Use of Sleep Medications change scores predicted a change in SPPB Total (β = 1.62) and SPPB Chair Stand (β = 0.63); IFS change scores predicted SPPB Total (β = -0.16) and SPPB Chair Stand performance (β = -0.07) change scores.

Conclusions

For older adults, changes in sleep medication use, daytime dysfunction, and fatigue were associated with improvements in functional recovery (including physical performance and independence) from acute hospitalization to 4-week follow-up. These results suggest that interventions focused on improving sleep quality, daytime consequences, and fatigue might help enhance physical functioning following hospitalization.

Clinical trial registration

ClinicalTrials.gov, identifier: NCT02203656.

The effect of vitamin D on sleep quality: A systematic review and meta-analysis

Background: Poor sleep quality is a common problem in the general population that affects the quality of life of individuals. Aim: This systematic review aimed to determine the effect of vitamin D on sleep quality (primary outcome) and side effects (secondary outcome). Methods: A systematic search was performed using Cochrane Library, PubMed, Embase, Web of Sciences, Scopus, Google Scholar, SID, and Magiran databases with no limit at the time of publication. Cochrane collaboration instrument was used to evaluate the quality of the included studies. RevMan software was used for meta-analysis. Mean Difference was calculated due to the same sleep quality measurement tools in all studies. Heterogeneity of studies was assessed using I-squared (I2). Due to high heterogeneity (I2 > 75%), Random Effect was used instead of Fixed Effect. Results: Out of a total of 1637 titles and abstracts found, after removing duplicate items (23 items), 1596 items were removed due to irrelevance and lack of inclusion criteria. 18 articles were fully studied due to insufficient abstract information and finally, 5 articles were entered into systematic review and meta-analysis. The results of the meta-analysis showed that the use of vitamin D supplementation significantly improves sleep quality (MD: -1.32; 95%CI: -2.55 to -0.09; P = 0.04). Conclusions: Also, according to the findings of this study, receiving vitamin D supplementation did not cause any side effects. According to the results of this review study, sleep quality in people receiving vitamin D significantly improved compared to the control group.

Exercise improves sleep quality in older adults: a protocol for a systematic review and meta-analysis

INTRODUCTION

Sleep disturbance is a common problem among the elderly and is associated with physical and mental health. Exercise has been reported as an alternative therapeutic strategy for people with sleep disturbances. However, this topic has not been systematically reviewed for older adults. This study was conducted to provide a protocol to systematically evaluate the effects of exercise on sleep quality in the elderly.

METHODS AND ANALYSIS

An electronic search of the PubMed, Embase and Cochrane Library databases will be performed with no language restrictions, and data extraction will be performed by two independent reviewers. The reviewers will discuss and resolve any differences, and a third reviewer will be consulted in cases of uncertainty. Randomised controlled trials will be selected. The primary outcome will be an objective measurement of sleep quality (eg, polysomnography). The secondary outcomes will be self-reported sleep quality (using the Pittsburgh Sleep Quality Index scale), and adverse events (such as falls and fractures). RevMan V.5.3.5 and Stata V.16.0 software will be used for meta-analysis. If the heterogeneity tests show slight or no statistical heterogeneity, the fixed effects model will be used; in other cases, the random effect model will be used for data synthesis.

ETHICS AND DISSEMINATION

The protocol does not require ethical approval. The findings will be disseminated in peer-reviewed publications and journals.

PROSPERO REGISTRATION NUMBER

CRD42021287980.

Genome-Wide Association Study and Genetic Correlation Scan Provide Insights into Its Genetic Architecture of Sleep Health Score in the UK Biobank Cohort

PURPOSE

Most previous genetic studies of sleep behaviors were conducted individually, without comprehensive consideration of the complexity of various sleep behaviors. Our aim is to identify the genetic architecture and potential biomarker of the sleep health score, which more powerfully represents overall sleep traits.

PATIENTS AND METHODS

We conducted a genome-wide association study (GWAS) of sleep health score (overall assessment of sleep duration, snoring, insomnia, chronotype, and daytime dozing) using 336,463 participants from the UK Biobank. Proteome-wide association study (PWAS) and transcriptome-wide association study (TWAS) were then performed to identify candidate genes at the protein and mRNA level, respectively. We finally used linkage disequilibrium score regression (LDSC) to estimate the genetic correlations between sleep health score and other functionally relevance traits.

RESULTS

GWAS identified multiple variants near known candidate genes associated with sleep health score, such as MEIS1, FBXL13, MED20 and SMAD5. HDHD2 (PPWAS = 0.0146) and GFAP (PPWAS = 0.0236) were identified associated with sleep health score by PWAS. TWAS identified ORC4 (PTWAS = 0.0212) and ZNF732 (PTWAS = 0.0349) considering mRNA expression level. LDSC found significant genetic correlations of sleep health score with 3 sleep behaviors (including insomnia, snoring, dozing), 4 psychiatry disorders (major depressive disorder, attention deficit/hyperactivity disorder, schizophrenia, autism spectrum disorder), and 9 plasma protein (such as Stabilin-1, Stromelysin-2, Cytochrome c) (all LDSC PLDSC < 0.05).

CONCLUSION

Our results advance the comprehensive understanding of the aetiology and genetic architecture of the sleep health score, refine the understanding of the relationship of sleep health score with other traits and diseases, and may serve as potential targets for future mechanistic studies of sleep phenotype.

Effects of High-Intensity Interval Exercise and Acute Partial Sleep Deprivation on Cardiac Autonomic Modulation

Sleep deprivation in healthy adults has been associated with disrupted autonomic nervous system function, which in turn has been linked to cardiovascular health. High-intensity interval exercise (HIIE) may affect both sleep and cardiac autonomic modulation. Purpose: To investigate the impact of acute partial sleep deprivation on autonomic cardiac regulation before and after an acute bout of HIIE and the length of time for the autonomic system to return to resting levels. Methods: Fifteen healthy males with body mass index (BMI) of 25.8 ± 2.7 kg·m^-2 and age 31 ± 5 y participated in a reference sleep (~9.5 hr) with no HIIE (RS), a reference sleep with HIIE (RSX), and an acute partial sleep deprivation (~3.5 hr) with HIIE (SDX). HIIE was performed in 3:2 intervals at 90% and 40% of VO₂ reserve. Autonomic regulation through HRV selected time and frequency domain indices were recorded the night before, the morning of the next day, 1 hr-, 2 hr-, 4hr-, and 6-hr post-exercise. Results: HIIE performed in a 3:2 W:R ratio decreased the HRV (p < .05) at 1-hr post exercise and it took up to 4 hr to return to baseline levels. Parasympathetic related HRV indices increased the morning of the next day for SDX (p < .05). Acute partial sleep deprivation and HIIE did not modify the HRV responses compared to reference sleep and HIIE. Conclusion: HRV disturbance typically seen in responses to an acute episode of HIIE is not influenced by acute partial sleep deprivation.

Is Sleep Disordered Breathing Confounding Rehabilitation Outcomes in Spinal Cord Injury Research?

The purpose of this article is to highlight the importance of considering sleep-disordered breathing (SDB) as a potential confounder to rehabilitation research interventions in spinal cord injury (SCI). SDB is highly prevalent in SCI, with increased prevalence in individuals with higher and more severe lesions, and the criterion standard treatment with continuous positive airway pressure remains problematic. Despite its high prevalence, SDB is often untested and untreated in individuals with SCI. In individuals without SCI, SDB is known to negatively affect physical function and many of the physiological systems that negatively affect physical rehabilitation in SCI. Thus, owing to the high prevalence, under testing, low treatment adherence, and known negative effect on the physical function, it is contended that underdiagnosed SDB in SCI may be confounding physical rehabilitation research studies in individuals with SCI. Studies investigating the effect of treating SDB and its effect on physical rehabilitation in SCI were unable to be located. Thus, studies investigating the likely integrated relationship among physical rehabilitation, SDB, and proper treatment of SDB in SCI are needed. Owing to rapid growth in both sleep medicine and physical rehabilitation intervention research in SCI, the authors contend it is the appropriate time to begin the conversations and collaborations between these fields. We discuss a general overview of SDB and physical training modalities, as well as how SDB could be affecting these studies.

Considerations for Maximizing the Exercise "Drug" to Combat Insulin Resistance: Role of Nutrition, Sleep, and Alcohol

Insulin resistance is a key etiological factor in promoting not only type 2 diabetes mellitus but also cardiovascular disease (CVD). Exercise is a first-line therapy for combating chronic disease by improving insulin action through, in part, reducing hepatic glucose production and lipolysis as well as increasing skeletal muscle glucose uptake and vasodilation. Just like a pharmaceutical agent, exercise can be viewed as a "drug" such that identifying an optimal prescription requires a determination of mode, intensity, and timing as well as consideration of how much exercise is done relative to sitting for prolonged periods (e.g., desk job at work). Furthermore, proximal nutrition (nutrient timing, carbohydrate intake, etc.), sleep (or lack thereof), as well as alcohol consumption are likely important considerations for enhancing adaptations to exercise. Thus, identifying the maximal exercise "drug" for reducing insulin resistance will require a multi-health behavior approach to optimize type 2 diabetes and CVD care.

The Association between Cardiorespiratory Fitness and Reported Physical Activity with Sleep Quality in Apparently Healthy Adults: A Cross-Sectional Study

BACKGROUND

Recently, poor cardiorespiratory fitness (CRF) has been postulated as an adverse health outcome related to poor sleep quality. However, studies investigating the relationship between CRF and a subjective sleep quality index are scarce. Thus, the current study aimed to investigate the association between CRF and the Pittsburgh Sleep Quality Index (PSQI) in apparently healthy people. The secondary aim was to investigate the association between reported physical activity (PA) and PSQI.

METHODS

Thirty-three healthy male participants volunteered to participate. CRF (VO_2PEAK) was measured via cardiopulmonary exercise testing on a treadmill. A short form of the International Physical Activity Questionnaire (IPAQ) was used to measure PA, and PSQI was used for the sleep quality index.

RESULTS

There was no correlation between CRF and PSQI total score or any component of the PSQI. There was a significant inverse correlation between IPAQ and PSQI total score (r = -0.36, p = 0.04). Categorical data analysis of the two questionnaires revealed that 42.4% of the participants who reported low physical activity also had poor sleep quality.

CONCLUSIONS

The current study showed no association between CRF and the subjective sleep quality index but demonstrated a moderate inverse association between reported PA and subjective sleep quality index. The findings suggest that the more reported PA, the better the overall sleep quality.

High-Intensity Interval Exercise Performance and Short-Term Metabolic Responses to Overnight-Fasted Acute-Partial Sleep Deprivation

People practicing high-intensity interval exercise (HIIE) fasted during the morning hours under a lack of sleep. Such a habit may jeopardize the health benefits related to HIIE and adequate sleep. Fifteen habitually good sleeper males (age 31.1 ± 5.3 SD year) completed on a treadmill two isocaloric (500 kcal) HIIE sessions (3:2 min work:rest) averaged at 70% VO2reserve after 9-9.5 h of reference sleep exercise (RSE) and after 3-3.5 h of acute-partial sleep deprivation exercise (SSE). Diet and sleep patterns were controlled both 1 week prior and 2 days leading up to RSE and SSE. HIIE related performance and substrate utilization data were obtained from the continuous analysis of respiratory gases. Data were analyzed using repeated measures ANOVA with the baseline maximum oxygen uptake (VO2max) and body fat percentage (BF%) as covariates at p < 0.05. No difference was observed in VO2max, time to complete the HIIE, VE, RER, CHO%, and FAT% utilization during the experimental conditions. Whether attaining an adequate amount of sleep or not, the fasted HIIE performance and metabolism were not affected. We propose to practice the fasted HIIE under adequate sleep to receive the pleiotropic beneficial effects of sleep to the human body.

The impact of individual lifestyle and status on the acquisition of COVID-19: A case-Control study

Background

Coronavirus disease 2019 (COVID-19) has spread to the world. Whether there is an association between lifestyle behaviors and the acquisition of COVID-19 remains unclear.

Methods

In this case-control study, we recruited 105 patients with SARS-CoV-2 infection as a case group from the Wuhan Tongji Hospital (Wuhan, China). For each case two control subjects were recruited. Participants were randomly selected from communities in Wuhan and matched for sex, age (± 2yrs), and pre-existing comorbidities (hypertension and diabetes).

Results

A total of 105 patients diagnosed with COVID-19 and 210 controls were included. Compared with control group, the case group had higher proportions of lack of sleep (30.5% vs. 14.8%, P = 0.001) and increased physical activities (56.2% vs. 32.9%, P < 0.001). And patients in the case group were more likely to have alopecia (28.6% vs. 10.0%, P < 0.001) than people from the control group. Overall, we found that lack of sleep [adjusted odds ratio (OR) 1.56, 95% confidence interval (CI) 1.03–2.39)], physical activities (≥ 5 times a week) (adjusted OR 2.05, 95%CI 1.39–3.02) and alopecia (adjusted OR 1.73, 95%CI 1.13–2.66) were independent risk factors for COVID-19 infection. Conversely, low-dose alcohol intake (<100g alcohol per week), hand hygiene, and fruits intake (daily) were significantly associated with a decrease in morbidity.

Conclusions

Individual lifestyle behaviors and health status can affect the occurrence of COVID-19.

The Effect of Timing and Type of Exercise on the Quality of Sleep in Trained Individuals

Sleep is an extremely important component for overall health and for a well-balanced training program. Recent studies have highlighted the interaction between sleep, recovery, and performance in elite and recreational athletes alike. Exercise has been known to affect the quality of sleep, nevertheless the impact is not well understood in the current research, particularly the effects of exercise timing and intensity on sleep quality. The purpose of this study was to understand if exercise timing and intensity significantly impact sleep quality among recreational exercisers. The participants involved were recreational exercisers who were self-grouped into an AM or PM exercise group. They participated in a seven-day quantitative, quasi-experimental, exploratory study wearing an Actigraph watch. The participant's intensity was also self-grouped into moderate intensity or high intensity based on criteria cut points. Data was analyzed using a factorial ANOVA to examine if there was a significant difference between exercise timing and intensity on sleep quality of the participants. There were no significant differences in sleep quality in either the time group (AM vs PM) or the intensity group (MOD vs VIG) within the four measures of sleep that were looked at throughout this study; total sleep time, sleep onset latency, sleep efficiency % and wake after sleep onset (TST, SOL, SE, and WASO). Results within both, the AM and PM group and the MOD and VIG group, results showed no significant differences. These results conclude that neither exercise intensity or timing had an effect on sleep quality.

Associations of physical fitness and physical activity with sleep among middle-aged women

BACKGROUND

Sleep is an important component of health. Sleep disturbances increase in women as they enter menopause. Physical activity has been associated with improved sleep among older populations. The purpose of this study was to determine if physical activity and/or physical fitness are associated with sleep quantity and quality in middle-aged women.

METHODS

This study recruited 114 healthy women, aged 30-55 (43±8 y) from Saskatoon, Saskatchewan, from 2015-2019. Sleep quantity and quality were evaluated. Participants were classified on their aerobic fitness, based on estimated peak aerobic capacity, as high or low grip strength and, as active or inactive.

RESULTS

The high aerobic fitness group had a greater mean sleep duration of 7.04±1.02 h compared to the low fit group 6.61±1.00 h after adjusting for age, Body Mass Index, waist circumference and menstrual status (P=0.01). The percentage of high aerobic fitness women who felt rested was greater than low aerobic fitness women (67±6% vs. 45±7%, P=0.03), after adjusting for age, Body Mass Index, waist circumference and menstrual status. Our study found a significant difference between women with higher aerobic fitness levels getting more sleep each night and feeling more rested.

CONCLUSIONS

The continued examination of physical fitness and its relationship to sleep holds importance for women's health.

Nonalcoholic steatohepatitis Fitness Intervention in Thrombosis (NASHFit): Study protocol for a randomized controlled trial of a supervised aerobic exercise program to reduce elevated clotting risk in patients with NASH

Nonalcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease worldwide affecting upwards of one third the global population. For reasons not fully understood, individuals with NAFLD and its more severe variant, nonalcoholic steatohepatitis (NASH), are at increased risk for venous thromboembolism which significantly increases morbidity and mortality. Lifestyle changes centering around exercise training are the mainstay of treatment for NAFLD/NASH. While exercise training can lessen venous thromboembolic risk in healthy persons and those with cardiovascular disease, whether or not this benefit is seen in patients with NAFLD/NASH remains unknown. In order to better understand how exercise training impacts thrombosis risk in NAFLD, we present the design of a thirty-two week randomized controlled clinical trial of 42 sedentary subjects age 18-69 with biopsy proven NASH. The main aim is to determine the impact of an aerobic exercise training program on the abnormal hemostatic system unique to NAFLD/NASH. The main outcome is change in plasminogen activator inhibitor one level, an established marker for venous thromboembolism. Secondary outcomes include body composition, cardiorespiratory fitness, control of comorbid metabolic conditions (e.g., obesity, hypertension, hyperlipidemia, diabetes), dietary composition, health related quality of life, liver enzymes and histology, NAFLD/NASH disease activity (e.g., biomarkers, clinical decision aids), microbiome, other markers of hemostasis, and PNPLA3 gene expression. The study represents the first clinical trial of an exercise training program to reduce elevated clotting risk in subjects with NAFLD/NASH.

Sleep Dysfunction and Mood in Collegiate Soccer Athletes

BACKGROUND

Sleep and mood are critical factors that contribute to health and wellness and are of particular interest to collegiate athletes who are juggling high physical, academic, and social demands. The aim of this study was to examine how psychological measures, player status, and sex-related factors were associated with perceived sleep quality.

HYPOTHESIS

Higher levels of global sleep dysfunction will be related to poor mood and increased anxiety, and there will be differences in sleep dysfunction in male compared with female athletes as well as regarding playing status.

STUDY DESIGN

Prospective cohort study.

LEVEL OF EVIDENCE

Level 4.

METHODS

During the 2016 through 2018 National Collegiate Athletic Association (NCAA) seasons, the Pittsburgh Sleep Quality Index (PSQI), Profile of Mood States, and Sports Anxiety Scale-2 questionnaires were administered to 230 soccer athletes at 6 separate time points throughout each season.

RESULTS

PSQI results yielded scores ≥5 in 54% of observations. Increased sleep dysfunction was significantly related to decreased vigor and increased tension, depression, anger, fatigue, somatic anxiety, worry, and concentration disruption, although effect sizes (ES) were trivial (ES, -0.03 to 0.15). The odds ratio (OR) of reporting global sleep dysfunction increased by 8%, 9%, and 25% for every 1-unit increase in tension (OR, 1.08; 95% CI, 1.02-1.16; P = 0.015), fatigue (OR, 1.09; 95% CI, 1.03-1.16; P = 0.002), and concentration disruption (OR, 1.25; 95% CI, 1.09-1.45; P = 0.002), respectively. The odds of reporting global sleep dysfunction were 55% lower for males than females (OR, 0.45; 95% CI, 0.25-0.79; P = 0.006).

CONCLUSION

Global sleep dysfunction was prevalent in NCAA soccer players and was related to negative mental health outcomes. Female participants experienced increased odds of reporting global sleep dysfunction.

CLINICAL RELEVANCE

Regular monitoring allows for a greater understanding of the interrelatedness between sleep and mental health in athletes.

Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study

BACKGROUND

Acute infections can cause an individual to have an elevated resting heart rate (RHR) and change their routine daily activities due to the physiological response to the inflammatory insult. Consequently, we aimed to evaluate if population trends of seasonal respiratory infections, such as influenza, could be identified through wearable sensors that collect RHR and sleep data.

METHODS

We obtained de-identified sensor data from 200 000 individuals who used a Fitbit wearable device from March 1, 2016, to March 1, 2018, in the USA. We included users who wore a Fitbit for at least 60 days and used the same wearable throughout the entire period, and focused on the top five states with the most Fitbit users in the dataset: California, Texas, New York, Illinois, and Pennsylvania. Inclusion criteria included having a self-reported birth year between 1930 and 2004, height greater than 1 m, and weight greater than 20 kg. We excluded daily measurements with missing RHR, missing wear time, and wear time less than 1000 min per day. We compared sensor data with weekly estimates of influenza-like illness (ILI) rates at the state level, as reported by the US Centers for Disease Control and Prevention (CDC), by identifying weeks in which Fitbit users displayed elevated RHRs and increased sleep levels. For each state, we modelled ILI case counts with a negative binomial model that included 3-week lagged CDC ILI rate data (null model) and the proportion of weekly Fitbit users with elevated RHR and increased sleep duration above a specified threshold (full model). We also evaluated weekly change in ILI rate by linear regression using change in proportion of elevated Fitbit data. Pearson correlation was used to compare predicted versus CDC reported ILI rates.

FINDINGS

We identified 47 249 users in the top five states who wore a Fitbit consistently during the study period, including more than 13·3 million total RHR and sleep measures. We found the Fitbit data significantly improved ILI predictions in all five states, with an average increase in Pearson correlation of 0·12 (SD 0·07) over baseline models, corresponding to an improvement of 6·3-32·9%. Correlations of the final models with the CDC ILI rates ranged from 0·84 to 0·97. Week-to-week changes in the proportion of Fitbit users with abnormal data were associated with week-to-week changes in ILI rates in most cases.

INTERPRETATION

Activity and physiological trackers are increasingly used in the USA and globally to monitor individual health. By accessing these data, it could be possible to improve real-time and geographically refined influenza surveillance. This information could be vital to enact timely outbreak response measures to prevent further transmission of influenza cases during outbreaks.

FUNDING

Partly supported by the US National Institutes of Health National Center for Advancing Translational Sciences.

A Serotonin-Modulated Circuit Controls Sleep Architecture to Regulate Cognitive Function Independent of Total Sleep in Drosophila

Both the structure and the amount of sleep are important for brain function. Entry into deep, restorative stages of sleep is time dependent; short sleep bouts selectively eliminate these states. Fragmentation-induced cognitive dysfunction is a feature of many common human sleep pathologies. Whether sleep structure is normally regulated independent of the amount of sleep is unknown. Here, we show that in Drosophila melanogaster, activation of a subset of serotonergic neurons fragments sleep without major changes in the total amount of sleep, dramatically reducing long episodes that may correspond to deep sleep states. Disruption of sleep structure results in learning deficits that can be rescued by pharmacologically or genetically consolidating sleep. We identify two reciprocally connected sets of ellipsoid body neurons that form the heart of a serotonin-modulated circuit that controls sleep architecture. Taken together, these findings define a circuit essential for controlling the structure of sleep independent of its amount.