Changes in sleep patterns of college students in Israel during COVID-19 lockdown, a sleep diaries study.

Objective To prevent and reduce the spread of COVID-19, governments around the world apply social restrictions and lockdowns. Such lockdowns significantly alter daily routine and habits. A growing body of research indicates that lockdowns affect sleep and circadian rhythms. The current study further explores that effect using sleep logs for a relatively long duration including lockdown and post-lockdown periods in Israel. Methods For five consecutive weeks, both during lockdown and during post-lockdown periods, from March 13th 2020 to May 12th 2020, Israeli students were asked to fill out daily sleep logs in which they report their sleep and wake times. The participants were also asked to fill out the Morningness-Eveningness Questionnaire (MEQ) in the beginning of the study. Results Data show increase in sleep duration and a later midsleep point during lockdown, compared to post-lockdown periods, both on workdays and on weekends. An interaction between chronotype and lockdown are also observed; Morning types sleep more both during lockdown and during post-lockdown periods. Interestingly, the midsleep point of late chronotypes is later during both workdays and weekends even during lockdown when social constrains on sleep time are in part removed. Discussion Overall, the current results based on detailed and relatively long-term sleep logs analysis confirm previous work using more limited measures such as one-time questionnaires. A lockdown period affects sleep-wake behavior: during lockdown people sleep duration is increased and their sleep onset is delayed. Nevertheless, the circadian preference of individuals is conserved across conditions.

Validation of the Munich Actimetry Sleep Detection Algorithm for estimating sleep-wake patterns from activity recordings

SummaryPeriods of sleep and wakefulness can be estimated from wrist-locomotor activity recordings via algorithms that identify periods of relative activity and inactivity. Here, we evaluated the performance of our Munich Actimetry Sleep Detection Algorithm (MASDA). MASDA uses a moving 24-hour-threshold and correlation procedure estimating relatively consolidated periods of sleep and wake.MASDA was validated against sleep logs and polysomnography. Sleep-log validation was performed on 2 field samples collected over 54 and 34 days (median) in 34 adolescents and 28 young adults. Polysomnographic validation was performed on a clinical sample of 23 individuals undergoing 1 night of polysomnography. Epoch-by-epoch analyses were conducted and comparisons of sleep measures via Bland-Altman plots and correlations.Compared with sleep logs, MASDA classified sleep with a median sensitivity of 80% (IQR = 75-86%) and specificity of 91% (87-92%). Mean onset and offset times were highly correlated (r = 0.86-0.91). Compared with polysomnography, MASDA reached a median sensitivity of 92% (85-100%), but low specificity of 33% (10-98%), owing to the low frequency of wake episodes in the nighttime polysomnographic recordings. MASDA overestimated sleep onset (~21 min) and underestimated wake after sleep onset (~26 min), while not performing systematically different from polysomnography in other sleep parameters.These results demonstrate the validity of MASDA to faithfully estimate sleep-wake patterns in field studies. With its good performance across day- and nighttime, it enables analyses of sleep-wake patterns in long recordings performed to assess circadian and sleep regularity and is therefore an excellent objective alternative to sleep logs in field settings.

Patterns of Sedentary Behavior in a Community-Based Cohort of Older Adults

Few epidemiologic studies have examined device-measured sitting patterns by demographics and health status. The Adult Changes in Thought (ACT) study is an on-going epidemiologic study of adults age ≥65 years. We conducted a sub-study that added a thigh-worn activPAL device and sleep logs for 7 days to the measurement protocol. A total of 997 had valid wear time (≥4 days with 10-20 hours of data per day) and covariate data. activPAL sedentary pattern measures included number of sitting bouts lasting 30 minutes or more and mean sitting bout duration. On average, participants (56% female, 57% > age 75, 89% non-Hispanic white) sat in bouts lasting 17 minutes (SD = 12) and had 5.9 (SD = 1.7) bouts of sitting lasting 30 minutes or more. Participants who were older, were male, had obesity, had worse self-rated health, had depression, and had difficulty walking had longer sitting bouts and more prolonged bouts.

1209 Effect Of Wearables On Sleep In Healthy Individuals: A Randomized Cross-over Trial And Validation Study

Introduction To determine whether a wearable sleep-tracker improves perceived sleep quality in healthy subjects. To test whether wearables reliably measure sleep quantity and quality compared to polysomnography. Methods A single-center randomized cross-over trial of community-based participants without medical conditions or sleep disorders. Wearable device (WHOOP, Inc.) that provided feedback regarding sleep information to the participant for 1-week and maintaining sleep logs versus 1-week of maintaining sleep logs alone. Self-reported daily sleep behaviors were documented in sleep logs. Polysomnography was performed on one night when wearing the wearable. PROMIS Sleep disturbance sleep scale was measured at baseline, 7, and 14 days of study participation. Results In 32 participants (21 women; 23.8 + 5 years), wearables improved nighttime sleep quality (PROMIS sleep disturbance; B= -1.69; 95% Confidence Interval -3.11, -0.27; P=0.021) after adjusting for age, sex, baseline, and order effect. There was a small increase in self-reported daytime naps when wearing the device (B = 3.2; SE 1.4; P=0.023) but total daily sleep remained unchanged (P=0.43). The wearable had low bias (2.5 minutes) and low precision (5.6 minutes) errors for measuring sleep duration and measured dream sleep and slow wave sleep accurately (Intra-class coefficient 0.74 + 0.28 and 0.85 + 0.15, respectively). Bias and precision error for heart rate (bias -0.17%; precision 1.5%) and respiratory rate (bias 1.8%’ precision 6.7%) were very low when compared to that measured by electrocardiogram and inductance plethysmography during polysomnography. Conclusion In healthy people, wearables can improve sleep quality and accurately measure sleep and cardiorespiratory variables. Support WHOOP Inc.

The use of wearable technology to objectively measure sleep quality and physical activity among pregnant women in urban Lima, Peru: A pilot feasibility study

Sleep quality and physical activity can affect the mental and physical health of pregnant women and their unborn babies. We investigated the feasibility of assessing sleep quality and physical activity among pregnant women in Peru. Twenty women maintained sleep logs and wore ActiSleep devices for seven consecutive days; 13 had sufficient data for analysis. Mean sleep duration was 6.9 hours (SD = 1.4). Sleep efficiency was 77.9%. Participants averaged of 6,029 steps per day (SD = 3,087). Objective assessment of sleep quality and physical activity was feasible. Wearable technology has applications in healthcare to improve sleep quality and physical activity.

SEDENTARY BEHAVIOR AND PHYSICAL ACTIVITY IN THE ADULT CHANGES IN THOUGHT (ACT) STUDY

Few epidemiologic studies have examined device-measured sitting patterns and health outcomes. Furthermore, there is a need to continue understanding the role of prospectively measured physical activity in relation to older adult health. The Adult Changes in Thought (ACT) study is an on-going epidemiologic study of adults age ≥65 years that began in 1994. Participants complete biennial assessments including a self-reported measure of physical activity. Starting in 2016, ACT participants could enroll in a physical activity sub-study that involved wearing a thigh-worn activPAL device and maintaining sleep logs for 7 days. Of those approached to participate in the sub-study, 64% agreed (N = 1139). A total of 961 had valid wear time (≥4 days with 10-20 hours of data per day) and completed survey collecting measures on pain and built environments (56% female, 57% > age 75, 89% non-Hispanic white). Participants who consented to the sub-study were generally younger and had fewer chronic conditions than those who did not consent. After removing sleep time, mean daily activPAL measures calculated included hours sitting and standing, number of sitting bouts lasting 30 minutes or more, number of breaks from sitting, and steps walked. The first session in this symposium will present historical self-reported physical activity trajectories in relation to cognitive function. The subsequent sessions will present novel cross-sectional data examining activPAL variables with measures of physical function, pain, and perceived built environments. This symposium will provide new insights on the roles of sedentary behavior and physical activity in aging and health.

But I Need Marijuana to Function as a Mother!

Polysomnography and multiple sleep latency testing (MSLT), along with detailed history and sleep logs and actigraphy, are essential for the diagnosis of narcolepsy with cataplexy (narcolepsy type 1). Interpreting polysomnography and MSLT data is challenging in patients with substance abuse. This chapter presents the case of a young woman with a history of substance abuse and confounding MSLT results due to covert use of recreational drugs. Recreational drugs affect sleep architecture, and the results of urine drug screening become a critical part of diagnostic evaluation in patients with substance abuse. Patients undergoing MSLT to characterize and confirm central hypersomnia need proper preparation to reduce false-positive, false-negative, and confounding results. Unexpected positive urine toxicology results are common in adolescents and adults undergoing MSLT and maintenance of wakefulness testing.

Digital in Her DNA

The most common sleep disorder in pre-adolescents and adolescents is insufficient sleep syndrome. The use of screen-based activities (e.g., cellphones, tablets, and video games) is a major contributor to insufficient and poor-quality sleep. The authors discuss changes in the sleep/wake pattern at the transition from pre-adolescent to adolescent age and various factors affecting these changes. They explain how self-imposed poor sleep hygiene practices and behaviors at bedtime affect sleep latency. Sleep logs or actigraphy can be useful tools in the confirmation of ISS. Strategies to avoid wake-promoting late evening activities and a consistent sleep/wake schedule are the keys to optimal daytime functioning. Treating insufficient sleep in adolescents with education and behavioral modification is effective in most cases.

Relationship Between Sedentary Time and Sleep Duration Among Korean Adolescents

Longer sedentary time and insufficient sleep are common and potentially serious problems among adolescents and have substantially adverse effects on their physical and mental health. In this school-based study, we conducted an ecological momentary assessment using actigraphy to examine the within-subject association between sedentary time and sleep duration among 80 Korean adolescents aged 12–17. Objectively measured sedentary time and sleep duration were recorded over 5 days; participants also completed a self-reported questionnaire and sleep logs. Using a generalized estimating equation, analysis revealed that daily sedentary time was significantly and negatively associated with sleep duration (β = −.36, p = .028). Additionally, the interaction between age and sedentary time significantly affected sleep duration (β = .03, p = .012). These findings suggest the need for school-based interventions that aim to reduce sedentary time and thereby improve sleep duration, helping adolescents, especially younger ones, to achieve a healthier lifestyle.