Sleep measurement tools, circadian strategies, and dietary factors pertaining to sleep in athletes and non-athletes

Obtaining sufficient sleep is important for humans to maintain optimal performance. This is especially true for elite athletes striving to improve performance while contending with unique stimuli that may impact their sleep (e.g., training, competition, travel). Measurement tools, countermeasures, and/or strategies that can be used to mitigate factors that negatively affect sleep are of great interest to athletes, coaches, and practitioners. This dissertation addresses (1) the validity of a wearable device to measure sleep; (2) the impact of evening exercise modality on sleep; (3) the effectiveness of strategies to facilitate circadian adaptation following transmeridian travel; and (4) the effectiveness of combined nutritional ingredients on sleep

Changes in health promoting behavior during COVID-19 physical distancing: Utilizing wearable technology to examine trends in sleep, activity, and cardiovascular indicators of health

The COVID-19 pandemic incited unprecedented restrictions on the behavior of society. The aims of this study were to quantify changes to sleep/wake behavior and exercise behavior, as well as changes in physiological markers of health during COVID-19 physical distancing. A retrospective analysis of 5,436 US-based subscribers to the WHOOP platform (mean age = 40.25 ± 11.33; 1,536 females, 3,900 males) was conducted covering the period from January 1st, 2020 through May 15th, 2020. This time period was separated into a 68-day baseline period and a 67-day physical distancing period. To provide context and allow for potential confounders (e.g., change of season), data were also extracted from the corresponding time periods in 2019. As compared to baseline, during physical distancing, all subjects fell asleep earlier (-0.15 hours), woke up later (0.29 hours), obtained more sleep (+0.21 hours) and reduced social jet lag (-0.13 hours). Contrasting sleep behavior was seen in 2019, with subjects falling asleep and waking up at a similar time (-0.01 hours; -0.03 hours), obtaining less sleep (-0.14 hours) and maintaining social jet lag (+0.06 hours) in corresponding periods. Individuals exercised more intensely during physical distancing by increasing the time spent in high heart rate zones. In 2020, resting heart rate decreased (-0.90 beats per minute) and heart rate variability increased (+0.98 milliseconds) during physical distancing when compared to baseline. However, similar changes were seen in 2019 for RHR (-0.51 beats per minute) and HRV (+2.97 milliseconds), suggesting the variation may not be related to the introduction of physical distancing mandates. The findings suggest that individuals improved health related behavior (i.e., increased exercise intensity and longer sleep duration) during physical distancing restrictions. While positive changes were seen to cardiovascular indicators of health, it is unclear whether these changes were a direct consequence of behavior change

Running on Empty: Self-Reported Sleep/Wake Behaviour during Ultra-Marathon Events Exceeding 100 Miles

The aim of this study was to examine sleep/wake behaviour and sleep strategies before, during and after ultra-marathon running events exceeding 100 miles (161 km). A total of 119 athletes completed a web-based questionnaire regarding their habitual sleep/wake behaviour before, during, and after ultra-marathon participation. Event-specific data were grouped by race distance categories; 100–149 miles (161–240 km), 150–199 miles (241–321 km), and ≥200 miles (322 km). Athletes commonly reported not sleeping throughout the duration of their races (74%). However, for events that were ≥200 miles, athletes reported more sleep opportunities, longer sleep duration, and more total sleep when compared to events that were 100–149 miles in distance (p ≤ 0.001). This suggests that for races of shorter distances, the benefit of continuous racing outweighs the negative impact of continuous wakefulness/sleep deprivation. However, for longer races (≥200 miles), there is an apparent tradeoff between sleep deprivation and race strategy, whereby athletes cannot sustain a desired level of performance without obtaining sleep. This is consistent with established sleep/wake behaviour models suggesting that sleep need increases as wakefulness increases, or in this case, as race duration increases. For athletes participating in ultra-marathons, sleep management education and/or consultation with a sleep scientist prior to racing may be beneficial. Future research should examine the optimal strategies concerning the frequency and duration of sleep during ultra-marathons and the subsequent impact on performance

A validation of six wearable devices for estimating sleep, heart rate and heart rate variability in healthy adults

The primary aim of this study was to examine the validity of six commonly used wearable devices, i.e., Apple Watch S6, Garmin Forerunner 245 Music, Polar Vantage V, Oura Ring Generation 2, WHOOP 3.0 and Somfit, for assessing sleep. The secondary aim was to examine the validity of the six devices for assessing heart rate and heart rate variability during, or just prior to, night-time sleep. Fifty-three adults (26 F, 27 M, aged 25.4 ± 5.9 years) spent a single night in a sleep laboratory with 9 h in bed (23:00–08:00 h). Participants were fitted with all six wearable devices—and with polysomnography and electrocardiography for gold-standard assessment of sleep and heart rate, respectively. Compared with polysomnography, agreement (and Cohen’s kappa) for two-state categorisation of sleep periods (as sleep or wake) was 88% (κ = 0.30) for Apple Watch; 89% (κ = 0.35) for Garmin; 87% (κ = 0.44) for Polar; 89% (κ = 0.51) for Oura; 86% (κ = 0.44) for WHOOP and 87% (κ = 0.48) for Somfit. Compared with polysomnography, agreement (and Cohen’s kappa) for multi-state categorisation of sleep periods (as a specific sleep stage or wake) was 53% (κ = 0.20) for Apple Watch; 50% (κ = 0.25) for Garmin; 51% (κ = 0.28) for Polar; 61% (κ = 0.43) for Oura; 60% (κ = 0.44) for WHOOP and 65% (κ = 0.52) for Somfit. Analyses regarding the two-state categorisation of sleep indicate that all six devices are valid for the field-based assessment of the timing and duration of sleep. However, analyses regarding the multi-state categorisation of sleep indicate that all six devices require improvement for the assessment of specific sleep stages. As the use of wearable devices that are valid for the assessment of sleep increases in the general community, so too does the potential to answer research questions that were previously impractical or impossible to address—in some way, we could consider that the whole world is becoming a sleep laboratory

Sleep and sexual satisfaction in couples with matched and mismatched chronotypes: A dyadic cross-sectional study

Chronotype can be defined as an overt expression of circadian rhythmicity in an individual that dictates tendencies towards being a morning or evening person–also referred to as ‘morningness’ or ‘eveningness.’ Chronotypes generally impact preferred bed and wake times, in addition to a range of personal and social factors. This study examined how matching/mismatching chronotypes within relationships impact sexual satisfaction and sleep quality. A sample of 32 couples (52% females, 38.3 ± 11.7 years) each completed an online survey that assessed chronotype (reduced Morningness Eveningness Questionnaire), sleep (Pittsburgh Sleep Quality Index), and sexual satisfaction (Index of Sexual Satisfaction). Partner surveys were matched to identify whether chronotypes were matching or mismatching. Couples with matched chronotypes reported greater sexual satisfaction than those with mismatched chronotypes, F(1, 58) = 19.57, p < .001. Matched couples also reported better sleep quality than couples whose chronotypes were mismatched, F(1,62) = 48.02, p < .001. The individual chronotype did not seem to impact on sleep quality or sexual satisfaction. To improve sleep quality and sexual satisfaction, strategies (e.g., circadian phase advance or delay) could be used to increase circadian alignment between members of a couple

Hit the gym or hit the hay: Can evening exercise characteristics predict compromised sleep in healthy adults?

Introduction: Recent sleep guidelines regarding evening exercise have shifted from a conservative (i.e., do not exercise in the evening) to a more nuanced approach (i.e., exercise may not be detrimental to sleep in circumstances). With the increasing popularity of wearable technology, information regarding exercise and sleep are readily available to the general public. There is potential for these data to aid sleep recommendations within and across different population cohorts. Therefore, the aim of this study was to examine if sleep, exercise, and individual characteristics can be used to predict whether evening exercise will compromise sleep. Methods: Data regarding evening exercise and the subsequent night’s sleep were obtained from 5,250 participants (1,321F, 3,929M, aged 30.1 ± 5.2 yrs) using a wearable device (WHOOP 3.0). Data for females and males were analysed separately. The female and male datasets were both randomly split into subsets of training and testing data (training:testing = 75:25). Algorithms were trained to identify compromised sleep (i.e., sleep efficiency <90%) for females and males based on factors including the intensity, duration and timing of evening exercise. Results: When subsequently evaluated using the independent testing datasets, the algorithms had sensitivity for compromised sleep of 87% for females and 90% for males, specificity of 29% for females and 20% for males, positive predictive value of 32% for females and 36% for males, and negative predictive value of 85% for females and 79% for males. If these results generalise, applying the current algorithms would allow females to exercise on ~ 25% of evenings with ~ 15% of those sleeps being compromised and allow males to exercise on ~ 17% of evenings with ~ 21% of those sleeps being compromised. Discussion: The main finding of this study was that the models were able to predict a high percentage of nights with compromised sleep based on individual characteristics, exercise characteristics and habitual sleep characteristics. If the benefits of exercising in the evening outweigh the costs of compromising sleep on some of the nights when exercise is undertaken, then the application of the current algorithms could be considered a viable alternative to generalised sleep hygiene guidelines

Implementing a circadian adaptation schedule after eastward flight in young male athletes

This study examined the effectiveness of a circadian adaptation schedule in male cricket-ers after an 8.5 h eastward time zone change. Ten participants (aged 18.7 ± 0.9 y) were randomly assigned to a control group or an intervention group. Participants in the intervention group followed a light exposure schedule in which they were instructed to seek light in the three hours pre-ceding, and avoid light in the three hours following their estimated core body temperature mini-mum. The rate of adaptation was assessed using the nightly excretion rate of urinary 6‐sulphatox-ymelatonin (aMT6s). General linear mixed models were conducted to assess the effect of condition (i.e., control and light intervention) on nocturnal secretion of aMT6s. Significant main effects of day (F(7, 35) = 10.4, p < 0.001) were reflected by an increase in nocturnal melatonin excretion (i.e., all participants gradually adapted to the destination time zone). Subjective jet lag decreased by day (F(7, 54) = 22.9, p < 0.001), bedtime was delayed by day (F(7, 54) = 3.1, p = 0.007) and get up time was earlier by day (F(7, 35) = 5.4, p < 0.001). On average, it took 7 days for all participants to return to baseline levels following transmeridian travel. Similarly, it took 7 days for subjective jet lag to alle-viate. In the initial 4 days of the protocol, the intervention group registered higher levels of nocturnal urinary melatonin, however, there was no significant differences in the rate of adaptation between the groups. It is possible that participants did not adhere to the intervention or that they followed the intervention but it was ineffective

Wrist-based photoplethysmography assessment of heart rate and heart rate variability: Validation of whoop

Heart rate (HR) and HR variability (HRV) infer readiness to perform exercise in athletic populations. Technological advancements have facilitated HR and HRV quantification via photo-plethysmography (PPG). This study evaluated the validity of WHOOP’s PPG-derived HR and HRV against electrocardiogram-derived (ECG) measures. HR and HRV were assessed via WHOOP and ECG over 15 opportunities. WHOOP-derived pulse-to-pulse (PP) intervals were edited with WHOOP’s proprietary filter, in addition to various filter strengths via Kubios HRV software. HR and HRV (Ln RMSSD) were quantified for each filter strength. Agreement was assessed via bias and limits of agreement (LOA), and contextualised using smallest worthwhile change (SWC) and coefficient of variation (CV). Regardless of filter strength, bias (≤0.39 ± 0.38%) and LOA (≤1.56%) in HR were lower than the CV (10–11%) and SWC (5–5.5%) for this parameter. For Ln RMSSD, bias (1.66 ± 1.80%) and LOA (±5.93%) were lowest for a 200 ms filter and WHOOP’s proprietary filter, which approached or exceeded the CV (3–13%) and SWC (1.5–6.5%) for this parameter. Acceptable agreement was found between WHOOP-and ECG-derived HR. Bias and LOA in Ln RMSSD approached or exceeded the SWC/CV for this variable and should be interpreted against its own level of bias precision

Moderate-intensity exercise performed in the evening does not impair sleep in healthy males

The aim of this study was to examine the effect of single bouts of moderate-intensity aerobic exercise and moderate-intensity resistance exercise performed in the evening on the sleep of healthy young males. The study employed a repeated-measures, counterbalanced, crossover design with three conditions (control, evening aerobic exercise, evening resistance exercise). Twelve male participants (mean ± SD; age: 21.9 ± 2.7 yr) attended the laboratory on three occasions separated by one day between each visit. Between 20:45 h and 21:30 h, participants completed either no exercise, 30 min of aerobic exercise at 75%HRmax, or 30 min of resistance exercise corresponding to 75% of 10-repetition maximum. A 9-h sleep opportunity was provided between 23:00 h and 08:00 h. Core body temperature was measured using ingestible temperature capsules and sleep was measured using polysomnography. Core body temperature was higher during the aerobic exercise and resistance exercise compared to control (p = 0.001). There was no difference in core body temperature at bedtime between the conditions. Sleep onset latency, total sleep time, slow-wave sleep duration, REM sleep duration, wake after sleep onset and sleep efficiency were similar in each condition (p > 0.05). Single bouts of moderate-intensity aerobic exercise or moderate-intensity resistance exercise performed in the evening did not impact subsequent night-time sleep. Core body temperature increased during both forms of exercise, but returned to pre-exercise levels in the 90 min prior to bedtime. Healthy young males can engage in a single bout of moderate-intensity aerobic exercise or moderate-intensity resistance exercise ceasing 90 min before bed without compromising their subsequent sleep. © 2019, © 2019 European College of Sport Science

Evaluating the Typical Day-to-Day Variability of WHOOP-Derived Heart Rate Variability in Olympic Water Polo Athletes

Heart rate (HR) and HR variability (HRV) can be used to infer readiness to perform exercise in athletic populations. Advancements in the photoplethysmography technology of wearable devices such as WHOOP allow for the frequent and convenient measurement of HR and HRV, and therefore enhanced application in athletes. However, it is important that the reliability of such technology is acceptable prior to its application in practical settings. Eleven elite male water polo players (age 28.8 ± 5.3 years [mean ± standard deviation]; height 190.3 ± 3.8 cm; body mass 95.0 ± 6.9 kg; international matches 117.9 ± 92.1) collected their HR and HRV daily via a WHOOP strap (WHOOP 3.0, CB Rank, Boston, MA, USA) over 16 weeks ahead of the 2021 Tokyo Olympic Games. The WHOOP strap quantified HR and HRV via wrist-based photoplethysmography during overnight sleep periods. The weekly (i.e., 7-day) coefficient of variation in lnRMSSD (lnRMSSDCV) and HR (HRCV) was calculated as a measure of day-to-day variability in lnRMSSD and HR, and presented as a mean of the entire recording period. The mean weekly lnRMSSDCV and HRCV over the 16-week period was 5.4 ± 0.7% (mean ± 95% confidence intervals) and 7.6 ± 1.3%, respectively. The day-to-day variability in WHOOP-derived lnRMSSD and HR is within or below the range of day-to-day variability in alternative lnRMSSD (~3–13%) and HR (~10–11%) assessment protocols, indicating that the assessment of HR and HRV by WHOOP does not introduce any more variability than that which is naturally present in these variables