The Night-Time Sleep and Autonomic Activity of Male and Female Professional Road Cyclists Competing in the Tour de France and Tour de France Femmes.

BACKGROUND: Sleep is a critical component of recovery, but it can be disrupted following prolonged endurance exercise. The objective of this study was to examine the capacity of male and female professional cyclists to recover between daily race stages while competing in the 2022 Tour de France and the 2022 Tour de France Femmes, respectively. The 17 participating cyclists (8 males from a single team and 9 females from two teams) wore a fitness tracker (WHOOP 4.0) to capture recovery metrics related to night-time sleep and autonomic activity for the entirety of the events and for 7 days of baseline before the events. The primary analyses tested for a main effect of 'stage classification'-i.e., rest, flat, hilly, mountain or time trial for males and flat, hilly or mountain for females-on the various recovery metrics. RESULTS: During baseline, total sleep time was 7.2 ± 0.3 h for male cyclists (mean ± 95% confidence interval) and 7.7 ± 0.3 h for female cyclists, sleep efficiency was 87.0 ± 4.4% for males and 88.8 ± 2.6% for females, resting HR was 41.8 ± 4.5 beats·min-1 for males and 45.8 ± 4.9 beats·min-1 for females, and heart rate variability during sleep was 108.5 ± 17.0 ms for males and 119.8 ± 26.4 ms for females. During their respective events, total sleep time was 7.2 ± 0.1 h for males and 7.5 ± 0.3 h for females, sleep efficiency was 86.4 ± 1.2% for males and 89.6 ± 1.2% for females, resting HR was 44.5 ± 1.2 beats·min-1 for males and 50.2 ± 2.0 beats·min-1 for females, and heart rate variability during sleep was 99.1 ± 4.2 ms for males and 114.3 ± 11.2 ms for females. For male cyclists, there was a main effect of 'stage classification' on recovery, such that heart rate variability during sleep was lowest after mountain stages. For female cyclists, there was a main effect of 'stage classification' on recovery, such that the percentage of light sleep (i.e., lower-quality sleep) was highest after mountain stages. CONCLUSIONS: Some aspects of recovery were compromised after the most demanding days of racing, i.e., mountain stages. Overall however, the cyclists obtained a reasonable amount of good-quality sleep while competing in these physiologically demanding endurance events. This study demonstrates that it is now feasible to assess recovery in professional athletes during multiple-day endurance events using validated fitness trackers.

Wearable-derived maternal heart rate variability as a novel digital biomarker of preterm birth.

Despite considerable health consequences from preterm births, their incidence remains unchanged over recent decades, due partially to limited screening methods and limited use of extant methods. Wearable technology offers a novel, noninvasive, and acceptable way to track vital signs, such as maternal heart rate variability (mHRV). Previous research observed that mHRV declines throughout the first 33 weeks of gestation in term, singleton pregnancies, after which it improves. The aim of this study was to explore whether mHRV inflection is a feature of gestational age or an indication of time to delivery. This retrospective case-control study considered term and preterm deliveries. Remote data collection via non-invasive wearable technology enabled diverse participation with subjects representing 42 US states and 16 countries. Participants (N = 241) were retroactively identified from the WHOOP (Whoop, Inc.) userbase and wore WHOOP straps during singleton pregnancies between March 2021 and October 2022. Mixed effect spline models by gestational age and time until birth were fit for within-person mHRV, grouped into preterm and term births. For term pregnancies, gestational age (Akaike information criterion (AIC) = 26627.6, R2m = 0.0109, R2c = 0.8571) and weeks until birth (AIC = 26616.3, R2m = 0.0112, R2c = 0.8576) were representative of mHRV trends, with significantly stronger fit for weeks until birth (relative log-likelihood ratio = 279.5). For preterm pregnancies, gestational age (AIC = 1861.9, R2m = 0.0016, R2c = 0.8582) and time until birth (AIC = 1848.0, R2m = 0.0100, R2c = 0.8676) were representative of mHRV trends, with significantly stronger fit for weeks until birth (relative log-likelihood ratio = 859.4). This study suggests that wearable technology, such as the WHOOP strap, may provide a digital biomarker for preterm delivery by screening for changes in nighttime mHRV throughout pregnancy that could in turn alert to the need for further evaluation and intervention.

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.

Wearable derived cardiovascular responses to stressors in free-living conditions.

Stress contributes to the progression of many diseases. Despite stress' contribution towards disease, few methods for continuously measuring stress exist. We investigated if continuously measured cardiovascular signals from a wearable device can be used as markers of stress. Using wearable technology (WHOOP Inc, Boston, MA) that continuously measures and calculates heart rate (HR) and heart rate variability (root-mean-square of successive differences; HRV), we assessed duration and magnitude of deviations in HR and HRV around the time of a run (from 23665 runs) or high-stress work (from 8928 high-stress work events) in free-living conditions. HR and HRV were assessed only when participants were motionless (HRmotionless). Runs were grouped into light, moderate, and vigorous runs to determine dose response relationships. When examining HRmotionless and HRV throughout the day, we found that these metrics display circadian rhythms; therefore, we normalized HRmotionless and HRV measures for each participant relative to the time of day. Relative to the period within 30 minutes leading up to a run, HRmotionless is elevated for up to 180-210 minutes following a moderate or vigorous run (P<0.05) and is unchanged or reduced following a light run. HRV is reduced for at least 300 minutes following a moderate or vigorous run (P<0.05) and is unchanged during a light run. Relative to the period within 30 minutes leading up to high-stress work, HRmotionless is elevated during and for up to 30 minutes following high-stress work. HRV tends to be lower during high-stress work (P = 0.06) and is significantly lower 90-300 minutes after the end of the activity (P<0.05). These results demonstrate that wearables can quantify stressful events, which may be used to provide feedback to help individuals manage stress.

Sleep and Alcohol Use Patterns During Federal Holidays and Daylight Saving Time Transitions in the United States.

We conducted a retrospective observational study using remote wearable and mobile application data to evaluate whether US public holidays or Daylight Saving Time transitions were associated with significant changes in sleep behaviors, including sleep duration, sleep onset and offset, and the consistency of sleep timing, as well as changes in the point prevalence of alcohol use. These metrics were analyzed using objective, high resolution sleep-wake data (10,350,760 sleep episodes) and 5,777,008 survey responses of 24,250 US subscribers (74.5% male; mean age of 37.6 ± 9.8 years) to the wrist-worn biometric device platform, WHOOP (Boston, Massachusetts, United States), who were active users during 1 May 2020, through 1 May 2021. Compared to baseline, statistically significant differences in sleep and alcohol measures were found on most DST transitions, US public holidays, and their eves. For example, New Year's Eve corresponded with a sleep consistency decrease of 13.8 ± 0.3%, a sleep onset delay of 88.9 ± 3.2 min (00:01 vs. 22:33 baseline) later, a sleep offset delay of 78.1 ± 3.1 min (07:56 vs. 06:39), and an increase in the prevalence of alcohol consumption, with more than twice as many participants having reported alcohol consumption [+138.0% ± 6.7 (74.2% vs. 31.2%)] compared to baseline. In this analysis of a non-random sample of mostly male subscribers conducted during the COVID-19 pandemic, the majority of US public holidays and holiday eves were associated with sample-level increases in sleep duration, decreases in sleep consistency, later sleep onset and offset, and increases in the prevalence of alcohol consumption. Future work would be warranted to explore the generalizability of these findings and their public health implications, including in more representative samples and over longer time intervals.

Prior sleep-wake behaviors are associated with mental health outcomes during the COVID-19 pandemic among adult users of a wearable device in the United States.

OBJECTIVES: To characterize objective sleep patterns among U.S. adults before and during the COVID-19 pandemic, and to assess for associations between adverse mental health symptoms and (1) sleep duration and (2) the consistency of sleep timing before and during the pandemic. DESIGN: Longitudinal objective sleep-wake data during January-June 2020 were linked with mental health and substance use assessments conducted during June 2020 for The COVID-19 Outbreak Public Evaluation (COPE) Initiative. SETTING: Adult users of WHOOP-a commercial, digital sleep wearable. PARTICIPANTS: Adults residing in the U.S. and actively using WHOOP wearable devices, recruited by WHOOP, Inc. INTERVENTION: The COVID-19 pandemic and its mitigation. MEASUREMENTS: Anxiety or depression symptoms, burnout symptoms, and new or increased substance use to cope with stress or emotions. RESULTS: Of 4912 participants in the primary analytic sample (response rate, 14.9%), we observed acutely increased sleep duration (0.25 h or 15 m) and sleep consistency (3.51 points out of 100) and delayed sleep timing (onset, 18.7 m; offset, 36.6 m) during mid-March through mid-April 2020. Adjusting for demographic and lifestyle variables, participants with persistently insufficient sleep duration and inconsistent sleep timing had higher odds of adverse mental health symptoms and substance use in June 2020. CONCLUSIONS: U.S. adult wearable users displayed increased sleep duration, more consistent sleep timing, and delayed sleep onset and offset times after the COVID-19 pandemic onset, with subsample heterogeneity. Associations between adverse mental health symptoms and pre- and mid-pandemic short sleep duration and inconsistent sleep timing suggest that these characteristics warrant further investigation as potential modifiable mental health and substance use risk factors.

Biometrics from a wearable device reveal temporary effects of COVID-19 vaccines on cardiovascular, respiratory, and sleep physiology.

Although vaccines against SARS-CoV-2 have been proven safe and effective, transient side-effects lasting 24-48 h postvaccination have been reported. To better understand the subjective and objective response to COVID-19 vaccination, we conducted a retrospective analysis on 69,619 subscribers to a wrist-worn biometric device (WHOOP Inc., Boston, MA) who received either the AstraZeneca, Janssen/Johnson & Johnson, Moderna, or Pfizer/BioNTech vaccine. The WHOOP device measures resting heart rate (RHR), heart rate variability (HRV), respiratory rate (RR), and sleep architecture, and these physiological measures were normalized to the same day of the week, 1 wk before vaccination. Averaging across vaccines, RHR, RR, and percent sleep derived from light sleep were elevated on the first night following vaccination and returned to baseline within 4 nights postvaccination. When statistical differences were observed between doses on the first night postvaccination, larger deviations in physiological measures were observed following the first dose of AstraZeneca and the second dose of Moderna and Pfizer/BioNTech. When statistical differences were observed between age groups or gender on the first night postvaccination, larger deviations in physiological measures were observed in younger populations and in females (compared with males). When combining self-reported symptoms (fatigue, muscle aches, headache, chills, or fever) with the objectively measured physiological parameters, we found that self-reporting fever or chills had the strongest association with deviations in physiological measures following vaccination. In summary, these results suggest that COVID-19 vaccines temporarily affect cardiovascular, respiratory, and sleep physiology and that dose, gender, and age affect the physiological response to vaccination.NEW & NOTEWORTHY Here we report the first large-scale study investigating the effect of COVID-19 vaccines on cardiovascular, respiratory, and sleep physiology. We find that vaccines temporarily impact measures of cardiovascular, respiratory, and sleep physiology and that the degree of change in physiology is influenced by the manufacturer and dose of the vaccine and the gender and age of the vaccine recipient. These results provide insights into physiological changes that occur with COVID-19 vaccination and indicate that the unique responses that occur postvaccination may depend on manufacturer, dose, gender, and age.

Mental health, substance use, and suicidal ideation among unpaid caregivers of adults in the United States during the COVID-19 pandemic: Relationships to age, race/ethnicity, employment, and caregiver intensity.

BACKGROUND: Unpaid caregivers of adults play critical roles in health care systems by providing care to older adults and those with chronic conditions. The COVID-19 pandemic has heightened caregiving needs, forcing some into caregiving roles and disrupting others. We sought to estimate the prevalence of and identify factors associated with adverse mental health symptoms, substance use, and suicidal ideation amongst unpaid caregivers of adults versus non-caregivers. METHODS: During June 24-30, 2020, surveys were administered to U.S. adults. Quota sampling and survey weighting were implemented to improve sample representativeness of age, gender, and race/ethnicity. RESULTS: Of 9,896 eligible invited adults, 5,412 (54.7%) completed surveys and 5,011 (92.6%) met screening criteria and were analyzed, including 1,362 (27.2%) caregivers. Caregivers had higher adverse mental health symptom prevalences than non-caregivers, including suicidal ideation (33.4% vs 3.7%, p < 0.0001). Symptoms were more common among caregivers who were young vs older adults (e.g., aged 18-24 vs ≥65 years, aPR 2.75, 95% CI 1.95-3.88, p < 0.0001) and with moderate and high vs low Caregiver Intensity Index scores (2.31, 1.65-3.23; 2.81, 2.00-3.94; both p < 0.0001). LIMITATIONS: Self-report data may be subject to recall, response, and social desirability biases; unpaid caregivers were self-identified; child caregiving roles were not assessed; and internet-based survey samples might not fully represent the U.S. CONCLUSIONS: Caregivers experienced disproportionately high levels of adverse mental health symptoms. Younger caregivers and those with higher caregiving intensity were disproportionately affected. Increased visibility of and access to mental health care resources are urgently needed to address mental health challenges of caregiving.

Patterns of endogenous and exogenous ovarian hormone modulation on recovery metrics across the menstrual cycle.

INTRODUCTION: As the number of female athletes competing rises globally, training methodologies should reflect sex differences across critical metrics of adaptation to training. Surrogate markers of the autonomic nervous system (ANS) used for monitoring training load are heart rate variability (HRV) and resting heart rate (RHR). The aim was to investigate ovarian hormone effects on standard recovery metrics (HRV, RHR, respiratory rate (RR) and sleep duration) across a large population of female athletes. METHODS: A retrospective study analysed 362 852 days of data representing 13 535 menstrual cycles (MC) from 4594 respondents (natural MC n=3870, BC n=455, progestin-only n=269) for relationships and/or differences between endogenous and exogenous ovarian hormones on ANS. RESULTS: HRV and return to baseline (recovery) decreased as resting HR and RR increased (p<0.001) from the early follicular to the late luteal phase of the MC. Patterning was paradoxical across phases for users of combined hormonal contraception (BC) as compared with the patterning of the MC. HRV and recovery start elevated and drop off quickly during the withdrawal bleed, rising through the active pill weeks (p<0.001). Progestin-only users had similar patterning as the MC. The relationship between normalised recovery and previous day strain is modulated by birth control type. BC exhibited steeper declines in recovery with additional strain-normalised recovery decreases by an additional 0.0055±0.00135 (p<0.001) per unit of strain; with no significant difference between MC and progestin-only (p=0.19). CONCLUSION: The patterning of ANS modulation from ovarian hormones is significantly different between naturally cycling women and those on BC, with the patterning dependent on the type of contraception used.

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.

Mental Health Among Parents of Children Aged <18 Years and Unpaid Caregivers of Adults During the COVID-19 Pandemic - United States, December 2020 and February-⁠March 2021.

Early during the COVID-19 pandemic, nearly two thirds of unpaid caregivers of adults reported adverse mental or behavioral health symptoms, compared with approximately one third of noncaregivers† (1). In addition, 27% of parents of children aged <18 years reported that their mental health had worsened during the pandemic (2). To examine mental health during the COVID-19 pandemic among U.S. adults on the basis of their classification as having a parenting role (i.e., unpaid persons caring for children and adolescents aged <18 years, referred to as children in this report) or being an unpaid caregiver of adults (i.e., persons caring for adults aged ≥18 years),§ CDC analyzed data from cross-sectional surveys that were administered during December 2020 and February-March 2021 for The COVID-19 Outbreak Public Evaluation (COPE) Initiative.¶ Respondents were categorized as parents only, caregivers of adults only, parents-caregivers (persons in both roles), or nonparents/noncaregivers (persons in neither role). Adjusted odds ratios (aORs) for any adverse mental health symptoms, particularly suicidal ideation, were higher among all respondents who were parents, caregivers of adults, or both compared with respondents who were nonparents/noncaregivers and were highest among persons in both roles (parents-caregivers) (any adverse mental health symptoms: aOR = 5.1, 95% confidence interval [CI] = 4.1-6.2; serious suicidal ideation: aOR = 8.2, 95% CI = 6.5-10.4). These findings highlight that parents and caregivers, especially those balancing roles both as parents and caregivers, experienced higher levels of adverse mental health symptoms during the COVID-19 pandemic than adults without these responsibilities. Caregivers who had someone to rely on for support had lower odds of experiencing any adverse mental health symptoms. Additional measures are needed to improve mental health among parents, caregivers, and parents-caregivers.

Analyzing changes in respiratory rate to predict the risk of COVID-19 infection.

COVID-19, the disease caused by the SARS-CoV-2 virus, can cause shortness of breath, lung damage, and impaired respiratory function. Containing the virus has proven difficult, in large part due to its high transmissibility during the pre-symptomatic incubation. The study's aim was to determine if changes in respiratory rate could serve as a leading indicator of SARS-CoV-2 infections. A total of 271 individuals (age = 37.3 ± 9.5, 190 male, 81 female) who experienced symptoms consistent with COVID-19 were included- 81 tested positive for SARS-CoV-2 and 190 tested negative; these 271 individuals collectively contributed 2672 samples (days) of data (1856 healthy days, 231 while infected with COVID-19 and 585 while negative for COVID-19 but experiencing symptoms). To train a novel algorithm, individuals were segmented as follows; (1) a training dataset of individuals who tested positive for COVID-19 (n = 57 people, 537 samples); (2) a validation dataset of individuals who tested positive for COVID-19 (n = 24 people, 320 samples); (3) a validation dataset of individuals who tested negative for COVID-19 (n = 190 people, 1815 samples). All data was extracted from the WHOOP system, which uses data from a wrist-worn strap to produce validated estimates of respiratory rate and other physiological measures. Using the training dataset, a model was developed to estimate the probability of SARS-CoV-2 infection based on changes in respiratory rate during night-time sleep. The model's ability to identify COVID-positive individuals not used in training and robustness against COVID-negative individuals with similar symptoms were examined for a critical six-day period spanning the onset of symptoms. The model identified 20% of COVID-19 positive individuals in the validation dataset in the two days prior to symptom onset, and 80% of COVID-19 positive cases by the third day of symptoms.