Chronotype-specific Sleep in Two Versus Four Consecutive Shifts

Imputing missing sleep data from wearables with neural networks in real-world settings

Sleep is a critical component of health and well-being but collecting and analyzing accurate longitudinal sleep data can be challenging, especially outside of laboratory settings. We propose a simple neural network model titled SOMNI (Sleep data restOration using Machine learning and Non-negative matrix factorIzation [NMF]) for imputing missing rest-activity data from actigraphy, which can enable clinicians to better handle missing data and monitor sleep-wake cycles of individuals with highly irregular sleep-wake patterns. The model consists of two hidden layers and uses NMF to capture hidden longitudinal sleep-wake patterns of individuals with disturbed sleep-wake cycles. Based on this, we develop two approaches: the individual approach imputes missing data based on the data from only one participant, while the global approach imputes missing data based on the data across multiple participants. Our models are tested with shift and non-shift workers' data from three independent hospitals. Both approaches can accurately impute missing data up to 24 hours of long dataset (>50 days) even for shift workers with extremely irregular sleep-wake patterns (AUC > 0.86). On the other hand, for short dataset (~15 days), only the global model is accurate (AUC > 0.77). Our approach can be used to help clinicians monitor sleep-wake cycles of patients with sleep disorders outside of laboratory settings without relying on sleep diaries, ultimately improving sleep health outcomes.

Adapting shift work schedules for sleep quality, sleep duration, and sleepiness in shift workers

BACKGROUND

Shift work is associated with insufficient sleep, which can compromise worker alertness with ultimate effects on occupational health and safety. Adapting shift work schedules may reduce adverse occupational outcomes.

OBJECTIVES

To assess the effects of shift schedule adaptation on sleep quality, sleep duration, and sleepiness among shift workers.

SEARCH METHODS

We searched CENTRAL, PubMed, Embase, and eight other databases on 13 December 2020, and again on 20 April 2022, applying no language restrictions.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) and non-RCTs, including controlled before-after (CBA) trials, interrupted time series, and cross-over trials. Eligible trials evaluated any of the following shift schedule components. • Permanency of shifts • Regularity of shift changes • Direction of shift rotation • Speed of rotation • Shift duration • Timing of start of shifts • Distribution of shift schedule • Time off between shifts • Split shifts • Protected sleep • Worker participation We included studies that assessed sleep quality off-shift, sleep duration off-shift, or sleepiness during shifts.

DATA COLLECTION AND ANALYSIS

Two review authors independently screened the titles and abstracts of the records recovered by the search, read through the full-text articles of potentially eligible studies, and extracted data. We assessed the risk of bias of included studies using the Cochrane risk of bias tool, with specific additional domains for non-randomised and cluster-randomised studies. For all stages, we resolved any disagreements by consulting a third review author. We presented the results by study design and combined clinically homogeneous studies in meta-analyses using random-effects models. We assessed the certainty of the evidence with GRADE.

MAIN RESULTS

We included 11 studies with a total of 2125 participants. One study was conducted in a laboratory setting and was not considered for drawing conclusions on intervention effects. The included studies investigated different and often multiple changes to shift schedule, and were heterogeneous with respect to outcome measurement. Forward versus backward rotation Three CBA trials (561 participants) investigated the effects of forward rotation versus backward rotation. Only one CBA trial provided sufficient data for the quantitative analysis; it provided very low-certainty evidence that forward rotation compared with backward rotation did not affect sleep quality measured with the Basic Nordic Sleep Questionnaire (BNSQ; mean difference (MD) -0.20 points, 95% confidence interval (CI) -2.28 to 1.89; 62 participants) or sleep duration off-shift (MD -0.21 hours, 95% CI -3.29 to 2.88; 62 participants). However, there was also very low-certainty evidence that forward rotation reduced sleepiness during shifts measured with the BNSQ (MD -1.24 points, 95% CI -2.24 to -0.24; 62 participants). Faster versus slower rotation Two CBA trials and one non-randomised cross-over trial (341 participants) evaluated faster versus slower shift rotation. We were able to meta-analyse data from two studies. There was low-certainty evidence of no difference in sleep quality off-shift (standardised mean difference (SMD) -0.01, 95% CI -0.26 to 0.23) and very low-certainty evidence that faster shift rotation reduced sleep duration off-shift (SMD -0.26, 95% CI -0.51 to -0.01; 2 studies, 282 participants). The SMD for sleep duration translated to an MD of 0.38 hours' less sleep per day (95% CI -0.74 to -0.01). One study provided very low-certainty evidence that faster rotations decreased sleepiness during shifts measured with the BNSQ (MD -1.24 points, 95% CI -2.24 to -0.24; 62 participants). Limited shift duration (16 hours) versus unlimited shift duration Two RCTs (760 participants) evaluated 80-hour workweeks with maximum daily shift duration of 16 hours versus workweeks without any daily shift duration limits. There was low-certainty evidence that the 16-hour limit increased sleep duration off-shift (SMD 0.50, 95% CI 0.21 to 0.78; which translated to an MD of 0.73 hours' more sleep per day, 95% CI 0.30 to 1.13; 2 RCTs, 760 participants) and moderate-certainty evidence that the 16-hour limit reduced sleepiness during shifts, measured with the Karolinska Sleepiness Scale (SMD -0.29, 95% CI -0.44 to -0.14; which translated to an MD of 0.37 fewer points, 95% CI -0.55 to -0.17; 2 RCTs, 716 participants). Shorter versus longer shifts One RCT, one CBA trial, and one non-randomised cross-over trial (692 participants) evaluated shorter shift duration (eight to 10 hours) versus longer shift duration (two to three hours longer). There was very low-certainty evidence of no difference in sleep quality (SMD -0.23, 95% CI -0.61 to 0.15; which translated to an MD of 0.13 points lower on a scale of 1 to 5; 2 studies, 111 participants) or sleep duration off-shift (SMD 0.18, 95% CI -0.17 to 0.54; which translated to an MD of 0.26 hours' less sleep per day; 2 studies, 121 participants). The RCT and the non-randomised cross-over study found that shorter shifts reduced sleepiness during shifts, while the CBA study found no effect on sleepiness. More compressed versus more spread out shift schedules One RCT and one CBA trial (346 participants) evaluated more compressed versus more spread out shift schedules. The CBA trial provided very low-certainty evidence of no difference between the groups in sleep quality off-shift (MD 0.31 points, 95% CI -0.53 to 1.15) and sleep duration off-shift (MD 0.52 hours, 95% CI -0.52 to 1.56).

AUTHORS' CONCLUSIONS

Forward and faster rotation may reduce sleepiness during shifts, and may make no difference to sleep quality, but the evidence is very uncertain. Very low-certainty evidence indicated that sleep duration off-shift decreases with faster rotation. Low-certainty evidence indicated that on-duty workweeks with shift duration limited to 16 hours increases sleep duration, with moderate-certainty evidence for minimal reductions in sleepiness. Changes in shift duration and compression of workweeks had no effect on sleep or sleepiness, but the evidence was of very low-certainty. No evidence is available for other shift schedule changes. There is a need for more high-quality studies (preferably RCTs) for all shift schedule interventions to draw conclusions on the effects of shift schedule adaptations on sleep and sleepiness in shift workers.

Sleep deprivation, sleep fragmentation, and social jet lag increase temperature preference in Drosophila

Despite the fact that sleep deprivation substantially affects the way animals regulate their body temperature, the specific mechanisms behind this phenomenon are not well understood. In both mammals and flies, neural circuits regulating sleep and thermoregulation overlap, suggesting an interdependence that may be relevant for sleep function. To investigate this relationship further, we exposed flies to 12 h of sleep deprivation, or 48 h of sleep fragmentation and evaluated temperature preference in a thermal gradient. Flies exposed to 12 h of sleep deprivation chose warmer temperatures after sleep deprivation. Importantly, sleep fragmentation, which prevents flies from entering deeper stages of sleep, but does not activate sleep homeostatic mechanisms nor induce impairments in short-term memory also resulted in flies choosing warmer temperatures. To identify the underlying neuronal circuits, we used RNAi to knock down the receptor for Pigment dispersing factor, a peptide that influences circadian rhythms, temperature preference and sleep. Expressing UAS-Pdfr^RNAi in subsets of clock neurons prevented sleep fragmentation from increasing temperature preference. Finally, we evaluated temperature preference after flies had undergone a social jet lag protocol which is known to disrupt clock neurons. In this protocol, flies experience a 3 h light phase delay on Friday followed by a 3 h light advance on Sunday evening. Flies exposed to social jet lag exhibited an increase in temperature preference which persisted for several days. Our findings identify specific clock neurons that are modulated by sleep disruption to increase temperature preference. Moreover, our data indicate that temperature preference may be a more sensitive indicator of sleep disruption than learning and memory.

Early Time-Restricted Eating Reduces Weight and Improves Glycemic Response in Young Adults: A Pre-Post Single-Arm Intervention Study

INTRODUCTION

Time-restricted eating (TRE) has cardiometabolic health benefits by optimizing circadian rhythms. However, limited data are available on the effect of early TRE in young adults. The objective of this pre-post single-arm trial was to test the effect of TRE on body composition and cardiometabolic risk factors and to evaluate changes in meal and sleep timing by TRE among young adults with typically late bedtime.

METHODS

This 4-week intervention was conducted in healthy young adults aged 18-39 years. Dietary records with time logs were collected before and during the intervention, and nutrient intake and meal timing were evaluated. Snack packages containing 20 g of protein per day were provided weekly. Body composition was measured weekly using bioelectrical impedance analysis. Blood samples were collected before and after the intervention, and cardiometabolic parameters were evaluated.

RESULTS

Of the 36 screened participants, 34 completed the study (completion rate 94.4%). The average age was 23.4 ± 2.9 years with 64.7% female. The mean wake-up time and bedtime were 09:16 ± 01:26 and 01:51 ± 01:39 with average sleep duration of 7.4 ± 1.4 h. Body weight and fat mass, excluding muscle mass, were significantly reduced over 4 weeks compared to baseline only in the early TRE group starting before noon. The early TRE group also showed significantly reduced fasting glucose, fasting insulin, and serum triglyceride (TG) levels after 4 weeks. However, the late TRE group starting after noon showed no significant changes except a reduced TG level. The meal timing was changed by TRE, where the first meal was delayed and the last meal was shifted. Neither sleep duration nor timing was significantly changed by TRE. Energy intakes were not different, but protein intake increased from 19.2% to 22.6% due to snack packages during intervention. However, no significant correlation between nutrient intakes and body composition changes was found. There were no adverse events related to study participation.

CONCLUSIONS

An early TRE regimen may be a feasible and effective strategy to manage body composition and cardiometabolic risk factors in young adults without altering the sleep-wake cycle.

Impact of sleep timing on attention, sleepiness, and sleep quality among real-life night shift workers with shift work disorder: a cross-over clinical trial

STUDY OBJECTIVES

To examine the effect of sleep timing intervention on sleep quality, attention, and sleepiness at work among night shift workers with shift work disorder.

METHODS

We recruited 60 real-life night shift workers through advertisements to participate this cross-over clinical trial. Shift work disorder was confirmed with interview and sleep log. Participants were designated to follow evening sleep (15:00-23:00) and morning sleep (09:00-17:00) schedules in a randomized order. Chronotype was confirmed by the Munich Chronotype Questionnaire. Sleep behaviors and light exposure were recorded using actigraphy. Outcome measures were sleepiness evaluated by the Karolinska Sleepiness Scale, sleep quality evaluated by the Pittsburgh Sleep Quality Index, and attention performance assessed with psychomotor vigilance test. Differences in outcome between the morning and evening sleep schedules were compared using repeated measures ANOVA.

RESULTS

The participants slept for longer durations during evening sleep schedules compared with morning sleep schedules. Lower sleepiness scores, higher sleep quality, and shorter reaction times and less lapse numbers in the psychomotor vigilance test were observed for participants during evening sleep schedules than morning sleep schedules after adjustment for light exposure and sleep duration. Significant interaction effects were observed for reaction time and lapse number between chronotype and sleep schedule, where the differences between sleep schedules were most prominent among those with late chronotypes.

CONCLUSIONS

It is recommended that night shift workers with shift work disorder arrange to sleep in the evening instead of the morning for better sleep and attention performance, especially those with late chronotypes.

TRIAL REGISTRATION

Sleep Schedule Intervention Study Among Night Shift Workers, https://clinicaltrials.gov/ct2/show/NCT04160572, ClinicalTrials.gov Identifier: NTC04160572.