The 3 pillars of health

Consumer Wearable Sleep Trackers: Are They Ready for Clinical Use?

As the importance of good sleep continues to gain public recognition, the market for sleep-monitoring devices continues to grow. Modern technology has shifted from simple sleep tracking to a more granular sleep health assessment. We examine the available functionalities of consumer wearable sleep trackers (CWSTs) and how they perform in healthy individuals and disease states. Additionally, the continuum of sleep technology from consumer-grade to medical-grade is detailed. As this trend invariably grows, we urge professional societies to develop guidelines encompassing the practical clinical use of CWSTs and how best to incorporate them into patient care plans.

How Sleep Research in Extreme Environments Can Inform the Military: Advocating for a Transactional Model of Sleep Adaptation

PURPOSE OF REVIEW

We review the literature on sleep in extreme environments. Accordingly, we present a model that identifies the need for mitigating interventions to preserve sleep quality for military deployments.

RECENT FINDINGS

Situational factors that affect sleep in extreme environments include cold temperatures, isolated and confined areas, fluctuating seasonality, photoperiodicity, and extreme latitudes and altitudes. Results vary across studies, but general effects include decreased total sleep time, poor sleep efficiency, and non-specific phase delays or phase advances in sleep onset and sleep architecture. Considering habitability measures (e.g., light or temperature control) and individual differences such as variable stress responses or sleep need can mitigate these effects to improve mood, cognition, and operational performance. Although the situational demands during military missions inevitably reduce total sleep time and sleep efficiency, mitigating factors can attenuate sleep-related impairments, hence allowing for optimal mission success and personnel safety.

Association of sleep duration and quality with depression Among University Students and Faculty

BACKGROUND AND AIM

Highly competitive and demanding environments in educational institutions led to reduced sleep time for both students and faculty globally. The primary objective of this study was to determine the duration and quality of sleep among students and faculty of Imam Abdulrahman Bin Faisal University (IAU). The secondary objective was to explore the relationship between depression and sleep duration and quality among students and faculty.

METHODS

The study was conducted during 2021 in Dammam, Saudi Arabia. An online survey was disseminated among the university students. The survey form included: demographic data, Patient Health Questionnaire (PHQ9), Pittsburg Sleep Quality Index (PSQI) and Epworth Sleepiness scale (ESS). The responses were analyzed using bivariate and multivariate analysis.

RESULTS

A total of 509 responses satisfying the inclusion criteria were included (323 student and 186 faculty). The average sleep duration for the entire cohort was 6.21 ± 1.32 hours, with 6.5% sleeping less than 5 hours per night. The mean PSQI score was 7.61 ± 3.09, with 73.1% falling in the poor sleep quality category (PSQI score >5). The mean PHQ9 score was 8.86 ± 6.20, with 63.9% falling in the  mild depression category. The mean ESS score was 6.59 ± 4.02, with 11% having a score >10 (corresponding to excessive daytime sleepiness).

CONCLUSIONS

A significant proportion of surveyed students and faculty IAU suffer from sleep insufficiency, poor sleep quality, and mild degree of depression. Initiatives to tackle the issue of poor sleep quality and quantity among university students and faculty are required.

Associations between Suboptimal Sleep and Smoking, Poor Nutrition, Harmful Alcohol Consumption and Inadequate Physical Activity ('SNAP Risks'): A Comparison of People with and without a Mental Health Condition in an Australian Community Survey

Introduction: People with a mental health condition experience disproportionate morbidity and mortality compared to the general population. This inequity has been largely attributed to a higher prevalence of chronic disease risk behaviours including smoking, poor nutrition, harmful alcohol consumption and inadequate physical activity (‘SNAP risks’). Suboptimal sleep is highly prevalent among people with a mental health condition and, as an identified risk behaviour for several chronic diseases, has been implicated as an additional contributor to this health inequity. Research involving people without a mental health condition suggests associations between poor sleep and each SNAP risk; however, interactions with mental health status have not been reported in an Australian population. This study explored associations between suboptimal sleep and all four SNAP risks, and assessed whether they vary by mental health status. Materials and Methods: A descriptive study (n = 1265) was undertaken using self-report data from a cross-sectional telephone survey of Australian adults. Based on national guidelines and recommendations that indicate when someone might be at risk of adverse health effects, SNAP risks and sleep variables were reduced to two levels: ‘at risk’ or ‘not at risk’; and ‘appropriate’ or ‘suboptimal’, respectively. Chi square tests and multivariable logistic regression models explored associations between suboptimal sleep, SNAP risks and mental health status. Results: Fifteen per cent (n = 184) of participants identified as having a mental health condition in the past 12 months. Being at risk of adverse health effects due to smoking had the strongest association with several measures of suboptimal sleep (ps < 0.05). Two-way interactions revealed that being at risk of adverse health effects due to alcohol use and physical inactivity resulted in a significantly greater likelihood of suboptimal sleep duration (OR 3.06, 95% CI 1.41 to 6.64; OR 3.06, 95% CI 1.41 to 6.69) and nap duration (OR 7.96, 95% CI 1.90 to 33.22), respectively, for people with a mental health condition compared to those without. Conclusions: The findings suggest associations between suboptimal sleep and smoking, risky alcohol consumption and physical inactivity, with the latter two perhaps being stronger among people with a mental health condition compared to those without such a condition. Poor sleep should be considered in interventions to address smoking, alcohol and physical activity; and vice versa. This study lends further support for the value of multirisk lifestyle interventions to promote physical and mental health for people with mental health conditions.

The relationship between sleep and physical activity: The moderating role of daily alcohol consumption

STUDY OBJECTIVES

Studies have demonstrated a daily, bidirectional relationship between sleep and physical activity. However, little is known about how other health behaviors, such as alcohol consumption affect this relationship. This study examined how daily and average alcohol consumption affects the relationships between sleep and physical activity.

METHODS

Participants included 70 men and women, ages 18-50 with sleep duration >6.5 h. Participants wore an actigraph, physical activity monitor and recorded number of alcoholic drinks by daily food logs for 7 days. Results were analyzed using multi-level models to evaluate the 7-day average (i.e., between-person effects) and daily effects (i.e., within-person effects) simultaneously.

RESULTS

Those with more average (7 day) minutes of vigorous physical activity had less wake after sleep onset (WASO). Furthermore, a higher number of alcoholic drinks was associated with longer sleep duration and higher WASO over 7 days. Days with a higher number of alcoholic drinks were associated with higher WASO and sleep fragmentation that night. Alcohol intake moderated the average (7 day) and daily relationships between sleep and physical activity such that high average (7 days) WASO was associated with shorter average total physical activity duration, but only for those with higher alcohol intake. In addition, longer physical activity duration during the day was associated with lower sleep fragmentation that night, but only for those with lower alcohol intake.

CONCLUSIONS

These data demonstrate that in a naturalistic setting, alcohol intake negatively impacts sleep and diminishes the benefits of physical activity on sleep.