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

Cardiovascular autonomic neuropathy in diabetes: an update with a focus on management

Cardiovascular autonomic neuropathy (CAN) is an under-recognised yet highly prevalent microvascular complication of diabetes. CAN affects approximately 20% of people with diabetes, with recent studies highlighting the presence of CAN in prediabetes (impaired glucose tolerance and/or impaired fasting glucose), indicating early involvement of the autonomic nervous system. Understanding of the pathophysiology of CAN continues to evolve, with emerging evidence supporting a potential link between lipid metabolites, mitochondrial dysfunction and genetics. Recent advancements, such as streamlining CAN detection through wearable devices and monitoring of heart rate variability, present simplified and cost-effective approaches for early CAN detection. Further research on the optimal use of the extensive data provided by such devices is required. Despite the lack of specific pharmacological interventions targeting the underlying pathophysiology of autonomic neuropathy, several studies have suggested a favourable impact of newer glucose-lowering agents, such as sodium-glucose cotransporter 2 inhibitors and glucagon-like peptide-1 receptor agonists, where there is a wealth of clinical trial data on the prevention of cardiovascular events. This review delves into recent developments in the area of CAN, with emphasis on practical guidance to recognise and manage this underdiagnosed condition, which significantly increases the risk of cardiovascular events and mortality in diabetes.

Wearable Technology: A Wellbeing Option for Serving Police Officers and Staff? A Comparison of Results of a Pilot Study with Firearms Officers and a Group of Mixed Officers and Staff

The high-stress nature of policing contributes to deterioration of officer health and wellbeing as well as high levels of absenteeism and attrition. Wearable technology (WT) has been identified as a potential tool that can help in improving officer health and wellbeing. This pilot study aimed to give initial insight into acceptability and engagement with WT amongst officers. The study also aimed to uncover any notable areas for exploration in future research within the domain of officer health and wellbeing. Two groups were observed, firearms officers and a mixed group of officers. Participants wore the WT for an extended period, completed a variety of health and wellbeing questionnaires and discussed their experience in focus groups. Firearms officers and mixed group officers displayed similar sleep efficiency, but firearms officers have worse sleep consistency and sleep performance. Firearms officers appear to have higher HRV and a slightly lower resting heart rate. Both groups display reasonable acceptance of the use of WT, speaking favorably during the focus groups of how monitoring the data had improved their quality of life in terms of their understanding of sleep, wellbeing and how they had consequently completed lifestyle modification. WT offers some promise in managing officer health and wellbeing; studies with larger sample sizes are needed to confirm this.

Connection Between Sleep and Psychological Well-Being in U.S. Army Soldiers

INTRODUCTION

The goal of this exploratory study was to examine the relationships between sleep consistency and workplace resilience among soldiers stationed in a challenging Arctic environment.

MATERIALS AND METHODS

A total of 862 soldiers (67 females) on an Army base in Anchorage, AK, were provided WHOOP 3.0, a validated sleep biometric capture device and were surveyed at onboarding and at the conclusion of the study. Soldiers joined the study from early January to early March 2021 and completed the study in July 2021 (650 soldiers completed the onboarding survey and 210 completed the exit survey, with 151 soldiers completing both). Three comparative analyses were conducted. First, soldiers' sleep and cardiac metrics were compared against the general WHOOP population and a WHOOP sample living in AK. Second, seasonal trends (summer versus winter) in soldiers' sleep metrics (time in bed, hours of sleep, wake duration during sleep, time of sleep onset/offset, and disturbances) were analyzed, and these seasonal trends were compared with the general WHOOP population and the WHOOP sample living in AK. Third, soldiers' exertion, sleep duration, and sleep consistency were correlated with their self-reported psychological functioning. All analyses were conducted with parametric and non-parametric statistics. This study was approved by The University of Queensland Human Research Ethics Committee (Brisbane, Australia) Institutional Review Board.

RESULTS

Because of the exploratory nature of the study, the critical significance value was set at P < .001. Results revealed that: (1) Arctic soldiers had poorer sleep consistency and sleep duration than the general WHOOP sample and the Alaskan WHOOP sample, (2) Arctic soldiers showed a decrease in sleep consistency and sleep duration in the summer compared to that in the winter, (3) Arctic soldiers were less able to control their bedroom environment in the summer than in the winter, and (4) sleep consistency but not sleep duration correlated positively with self-report measures of workplace resilience and healthy social networks and negatively with homesickness.

CONCLUSIONS

The study highlights the relationship between seasonality, sleep consistency, and psychological well-being. The results indicate the potential importance of sleep consistency in psychological functioning, suggesting that future work should manipulate factors known to increase sleep consistency to assess whether improved sleep consistency can enhance the well-being of soldiers. Such efforts would be of particular value in an Arctic environment, where seasonality effects are large and sleep consistency is difficult to maintain.

Leveraging Emerging Technologies to Expand Accessibility and Improve Precision in Rehabilitation and Exercise for People with Disabilities

Physical rehabilitation and exercise training have emerged as promising solutions for improving health, restoring function, and preserving quality of life in populations that face disparate health challenges related to disability. Despite the immense potential for rehabilitation and exercise to help people with disabilities live longer, healthier, and more independent lives, people with disabilities can experience physical, psychosocial, environmental, and economic barriers that limit their ability to participate in rehabilitation, exercise, and other physical activities. Together, these barriers contribute to health inequities in people with disabilities, by disproportionately limiting their ability to participate in health-promoting physical activities, relative to people without disabilities. Therefore, there is great need for research and innovation focusing on the development of strategies to expand accessibility and promote participation in rehabilitation and exercise programs for people with disabilities. Here, we discuss how cutting-edge technologies related to telecommunications, wearables, virtual and augmented reality, artificial intelligence, and cloud computing are providing new opportunities to improve accessibility in rehabilitation and exercise for people with disabilities. In addition, we highlight new frontiers in digital health technology and emerging lines of scientific research that will shape the future of precision care strategies for people with disabilities.

Data Science and Geriatric Anesthesia Research: Opportunity and Challenges

With an increase in geriatric population undergoing surgical procedures, research focused on enhancing their perioperative outcomes is of paramount importance. Currently, most of the evidence-based medicine protocols are driven by studies concentrating on adults encompassing all adult age groups. Given the alterations in physiology with aging, geriatric patients respond differently to anesthetics and, therefore, require specific research initiatives to further expound on the same. Large databases and the development of sophisticated analytic tools can provide meaningful insights into this. Here, we discuss a few research opportunities and challenges that data scientists face when focusing on geriatric perioperative research.

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.

Accuracy of the Apple Watch Series 6 and the Whoop Band 3.0 for assessing heart rate during resistance exercises

This study aimed to determine heart rate accuracy measured by wearable devices during resistance exercises at various intensities. Twenty-nine participants (16 female) aged 19-37 years participated in this cross-sectional study. Participants completed five resistance exercises; Barbell Back Squat, Barbell Deadlift, Dumbbell Curl to Overhead Press, Seated Cable Row, and Burpees. During the exercises, heart rate was concurrently measured using the Polar H10, the Apple Watch Series 6 and the Whoop 3.0. The Apple Watch had high agreement with the Polar H10 during Barbell Back Squats, Barbell Deadlift, and Seated Cable Rows (rho > 0.832) and moderate to low agreement during Dumbbell Curl to Overhead Press and Burpees (rho > 0.364). The Whoop Band 3.0 had high agreement with the Polar H10 during Barbell Back Squats (r > 0.697), moderate agreement during Barbell Deadlift and Dumbbell Curl to Overhead Press (rho > 0.564) and low agreement during Seated Cable Rows and Burpees (rho > 0.383). The results varied across exercises and intensities and indicated the most favourable outcomes for the Apple Watch. In conclusion, our data suggest that the Apple Watch Series 6 is suitable for measuring heart rate during exercise prescription or monitoring resistance exercise performance.