Simulated Night Shift Research Articles

Comparison of 45-min nap versus no-nap during simulated night shift work on endothelial function: a randomized crossover feasibility trial.

Night shift workers face increased risk of cardiovascular disease (CVD) compared to non-shift workers. Evidence supports on-shift napping and regular non-invasive monitoring of endothelial function for risk mitigation, yet neither strategy is widely used. We evaluated the feasibility of non-invasive assessment of peripheral arterial tone (PAT) to assess the effect of napping during simulated night shift work on endothelial function. We used a single-site, randomized crossover trial of simulated night shift work with a 45-min nap condition versus a control, no-nap condition (ClinicalTrials.gov NCT05436951). Theprimary outcome was the number of participants with ≥ 70% of endothelial function assessments. Secondary outcomes included mean reactive hyperemia index (RHI), BP, and cognitive performance with the brief psychomotor vigilance task (PVT-B). Of the 10 consented, 9 completed both conditions. All participants exceeded feasibility benchmarks. Mean RHI did not differ by nap condition, and the delta from pre- to post measure did not differ (difference in delta = - 0.26, 95% CI - 1.09, 0.58). Hourly PVT-B assessments from 19:00 to 07:00h did not differ by nap condition. Compared to pre-nap measures, cognitive performance on the PVT-B was poorest at + 0min post-nap. Our findings can inform larger studies evaluating the effects of night shift work and napping on endothelial function. ClinicalTrials.gov (NCT05436951, registered on June 23, 2022).

The impact of breaking up sitting during simulated nightshifts on musculoskeletal pain: A randomised controlled trial

ObjectivesProlonged sitting is associated with an increased risk of musculoskeletal pain, especially in nightshift workers. However, research investigating effects of breaking up sitting on musculoskeletal pain during nightshifts is lacking. This study evaluated effects of prolonged sitting or breaking up sitting with short bouts of light-intensity physical activity on pain in healthy adults during simulated nightshifts. MethodsAn in-laboratory randomised controlled trial was undertaken with 52 healthy adults completing five simulated nightshifts. Participants were randomised to prolonged sitting (Sit9; n = 26) or breaking up prolonged sitting (Break9; n = 26). Break9 group completed 3-min walking every 30 min during nightshifts, while Sit9 group remained seated. Musculoskeletal pain intensity and sensory/affective pain experiences were assessed. Linear mixed models examined pain within nights (pre-to post-shift) and across nights (pre-shift-night-1 to pre-shift-night-5). ResultsMusculoskeletal pain intensity increased within nights for both Sit9 (mean change [95%CI] points: 0.14 [0.05, 0.24]) and Break9 (0.09 [0.001, 0.19], but not across nights (Sit9: −0.13 [-0.33, 0.08]; Break9: 0.07 [-0.14, 0.29]). Sensory-pain experience improved across nights for Sit9 (−3.08 [-4.72, −1.45]), but not within nights (0.77 [-0.004, 1.55]). There was no change in affective-pain experience in either group. Between-group difference was observed favouring Sit9 for improving sensory-pain across nights (β: 3.71 [1.42, 5.99]). No other between-group difference was observed. ConclusionBoth prolonged sitting and breaking up sitting were associated with a within-night increase in musculoskeletal pain intensity. Compared to prolonged sitting, breaking up sitting did not induce benefits on pain in healthy adults working simulated nightshifts. Trial registrationACTRN12619001516178.

A circadian-informed lighting intervention accelerates circadian adjustment to a night work schedule in a submarine lighting environment.

Night work has detrimental impacts on sleep and performance, primarily due to misalignment between sleep-wake schedules and underlying circadian rhythms. This study tested whether circadian-informed lighting accelerated circadian phase delay, and thus adjustment to night work, compared to blue-depleted standard lighting under simulated submariner work conditions. Nineteen healthy sleepers (12 males; mean±SD aged 29 ±10 y) participated in two separate 8-day visits approximately one month apart to receive, in random order, circadian-informed lighting (blue-enriched and dim, blue-depleted lighting at specific times) and standard lighting (dim, blue-depleted lighting). After an adaptation night (day 1), salivary dim light melatonin onset (DLMO) assessment was undertaken from 18:00-02:00 on days 2-3. During days 3-7, participants completed simulated night work from 00:00-08:00 and a sleep period from 10:00-19:00. Post-condition DLMO assessment occurred from 21:00-13:00 on days 7-8. Ingestible capsules continuously sampled temperature to estimate daily core body temperature minimum (Tmin) time. Tmin and DLMO circadian delays were compared between conditions using mixed effects models. There were significant condition-by-day interactions in Tmin and DLMO delays (both p<0.001). After four simulated night shifts, circadian-informed lighting produced a mean [95%CI] 4.3 [3.3 to 5.4] h greater delay in Tmin timing and a 4.2 [3 to 5.6] h greater delay in DLMO timing compared to standard lighting. Circadian-informed lighting accelerates adjustment to shiftwork in a simulated submariner work environment. Circadian lighting interventions warrant consideration in any dimly lit and blue-depleted work environments where circadian adjustment is relevant to help enhance human performance, safety, and health.

0096 Simulated Night Shift Schedule Alters Endogenous Temporal Regulation of Glucose and Insulin

0096 Simulated Night Shift Schedule Alters Endogenous Temporal Regulation of Glucose and Insulin

0141 Nighttime Napping Dampens Daily Peak of Sleepiness in Simulated Night Shift Schedules with Restricted Daytime Sleep

0141 Nighttime Napping Dampens Daily Peak of Sleepiness in Simulated Night Shift Schedules with Restricted Daytime Sleep

Molecular-Level Dysregulation of Insulin Pathways and Inflammatory Processes in Peripheral Blood Mononuclear Cells by Circadian Misalignment.

Circadian misalignment due to night work has been associated with an elevated risk for chronic diseases. We investigated the effects of circadian misalignment using shotgun protein profiling of peripheral blood mononuclear cells taken from healthy humans during a constant routine protocol, which was conducted immediately after participants had been subjected to a 3-day simulated night shift schedule or a 3-day simulated day shift schedule. By comparing proteomic profiles between the simulated shift conditions, we identified proteins and pathways that are associated with the effects of circadian misalignment and observed that insulin regulation pathways and inflammation-related proteins displayed markedly different temporal patterns after simulated night shift. Further, by integrating the proteomic profiles with previously assessed metabolomic profiles in a network-based approach, we found key associations between circadian dysregulation of protein-level pathways and metabolites of interest in the context of chronic metabolic diseases. Endogenous circadian rhythms in circulating glucose and insulin differed between the simulated shift conditions. Overall, our results suggest that circadian misalignment is associated with a tug of war between central clock mechanisms controlling insulin secretion and peripheral clock mechanisms regulating insulin sensitivity, which may lead to adverse long-term outcomes such as diabetes and obesity. Our study provides a molecular-level mechanism linking circadian misalignment and adverse long-term health consequences of night work.

Circadian-based lighting substantially improves vigilance in simulated night shift work conditions compared to standard lighting

Circadian-based lighting substantially improves vigilance in simulated night shift work conditions compared to standard lighting

Estimating vigilance from the pre-work shift sleep using an under-mattress sleep sensor.

Predicting vigilance impairment in high-risk shift work occupations is critical to help to reduce workplace errors and accidents. Current methods rely on multi-night, often manually entered, sleep data. This study developed a machine learning model for predicting vigilance errors based on a single prior sleep period, derived from an under-mattress sensor. Twenty-four healthy volunteers (mean [SD] age = 27.6 [9.5] years, 12 male) attended the laboratory on two separate occasions, 1 month apart, to compare wake performance and sleep under two different lighting conditions. Each condition occurred over an 8 day protocol comprising a baseline sleep opportunity from 10 p.m. to 7 a.m., a 27 h wake period, then daytime sleep opportunities from 10 a.m. to 7 p.m. on days 3-7. From 12 a.m. to 8 a.m. on each of days 4-7, participants completed simulated night shifts that included six 10 min psychomotor vigilance task (PVT) trials per shift. Sleep was assessed using an under-mattress sensor. Using extra-trees machine learning models, PVT performance (reaction times <500 ms, reaction, and lapses) during each night shift was predicted based on the preceding daytime sleep. The final extra-trees model demonstrated moderate accuracy for predicting PVT performance, with standard errors (RMSE) of 19.9 ms (reaction time, 359 [41.6]ms), 0.42 reactions/s (reaction speed, 2.5 [0.6] reactions/s), and 7.2 (lapses, 10.5 [12.3]). The model also correctly classified 84% of trials containing ≥5 lapses (Matthews correlation coefficient = 0.59, F1 = 0.83). Model performance is comparable to current fatigue prediction models that rely upon self-report or manually entered data. This efficient approach may help to manage fatigue and safety in non-standard work schedules.

The effects of fasting compared to eating a meal or snack during simulated night shift on changes in metabolism associated with circadian misalignment: a protocol and methods paper.

This protocol paper outlines the methods that will be used to examine the impact of altering meal timing on metabolism, cognitive performance, and mood during the simulated night shift. Participants (male and female) will be recruited according to an a priori selected sample size to complete a 7-day within and between participant's laboratory protocol. Participants will be randomly assigned to one of the three conditions: meal at night or snack at night or no meal at night. This protocol includes an 8-hour nighttime baseline sleep, followed by 4 consecutive nights of simulated nightshift (7 hours day sleep; 10:00-17:00 hours), and an 8-hour nighttime sleep (return to dayshift). During the simulated night shift, meals will be provided at ~06:30, 09:30, 14:10, and 19:00 hours (no eating at night); ~06:30, 19:00, and 00:30 hours (meal at night); or ~06:30, 14:10, 19:00, and 00:30 hours (snack at night). Meal composition will be strictly controlled throughout the study (45%-65% carbohydrates, 15%-25% protein, and 20%-35% fat per day) with daily energy provided to meet individual needs using the Harris-Benedict equation (light/sedentary activity). The primary outcome measures are serum concentrations of blood glucose, insulin, and free fatty acids area under the curve in response to the oral glucose tolerance test. Mixed-effect ANOVAs will be conducted. This protocol paper describes a methodology to describe an innovative approach to reduce the metabolic disease impact associated with shift work.

Human serum proteomics reveals a molecular signature after one night of sleep deprivation.

Sleep deprivation is highly prevalent and caused by conditions such as night shift work or illnesses like obstructive sleep apnea. Compromised sleep affects cardiovascular-, immune-, and neuronal systems. Recently, we published human serum proteome changes after a simulated night shift. This pilot proteomic study aimed to further explore changes in human blood serum after 6 hours of sleep deprivation at night. Human blood serum samples from eight self-declared healthy females were analyzed using Orbitrap Eclipse mass spectrometry (MS-MS) and high-pressure liquid chromatography. We used a within-participant design, in which the samples were taken after 6 hours of sleep at night and after 6 hours of sleep deprivation the following night. Systems biological databases and bioinformatic software were used to analyze the data and comparative analysis were done with other published sleep-related proteomic datasets. Out of 494 proteins, 66 were found to be differentially expressed proteins (DEPs) after 6 hours of sleep deprivation. Functional enrichment analysis revealed the associations of these DEPs with several biological functions related to the altered regulation of cellular processes such as platelet degranulation and blood coagulation, as well as associations with different curated gene sets. This study presents serum proteomic changes after 6 hours of sleep deprivation, supports previous findings showing that short sleep deprivation affects several biological processes, and reveals a molecular signature of proteins related to pathological conditions such as altered coagulation and platelet function, impaired lipid and immune function, and cell proliferation. Data are available via ProteomeXchange with identifier PXD045729. This paper is part of the Genetic and other molecular underpinnings of sleep, sleep disorders, and circadian rhythms including translational approaches Collection.

Circadian adaptation to night shift work is associated with higher REM sleep duration

ObjectiveTo investigate the influence of the degree of circadian adaptation to night work on sleep architecture following night shift. MethodsThirty four night workers (11 females; 33.8 ± 10.1years) completed a simulated night shift following 2-7 typical night shifts. Participants completed a laboratory-based simulated night shift (21:00-07:00 hours), followed by a recovery sleep opportunity (∼09:00-17:00 hours), recorded using polysomnography. Urinary 6-sulphatoxymelatonin (aMT6s) rhythm acrophase was used as a marker of circadian phase. Sleep duration and architecture were compared between individuals with aMT6s acrophase before (unadapted group, n = 22) or after (partially adapted group, n = 12) bedtime. ResultsBedtime occurred on average 2.16 hours before aMT6s acrophase in the partially adapted group and 3.91 hours after acrophase in the unadapted group. The partially adapted group had more sleep during the week before the simulated night than the unadapted group (6.47 ± 1.02 vs. 5.26 ± 1.48 hours, p = .02). After the simulated night shift, both groups had similar total sleep time (partially adapted: 6.68 ± 0.80 hours, unadapted: 6.63 ± 0.88 hours, p > .05). The partially adapted group had longer total rapid eye movement sleep duration than the unadapted group (106.79 ± 32.05 minutes vs. 77.90 ± 28.86 minutes, p = .01). After 5-hours, rapid eye movement sleep accumulation was higher in the partially adapted compared to the unadapted group (p = .02). Sleep latency and other stages were not affected by circadian adaptation. DiscussionPartial circadian adaptation to night shift was associated with longer rapid eye movement sleep duration during daytime sleep, highlighting the influence of entrainment between the sleep-wake cycle and the circadian pacemaker in night workers. The findings have important implications for sleep and subsequent alertness associated with shift work.

O003 Investigating the relationship between core body temperature and changes in cognitive performance during simulated night shifts

Abstract Introduction The timing of circadian and sleep-wake behaviours is disrupted by night shift-work. Interventions involving light may prove beneficial in adjusting the circadian rhythm to shift work, although the changes in vigilance remain uncertain. This study examined the temporal relationship between core body temperature (CBT) rhythm and vigilance during a work-shift through lighting. Methods 19 healthy individuals (12 males, mean±SD age of 28.7±10.4 years) participated in two 8-day experimental conditions with 4 days of circadian-informed lighting vs standard lighting. On Day 2, participants transitioned from a typical day-night wake-sleep schedule to night shift-work from 00:00 to 08:00 on Days 3 to 7. Psychomotor vigilance tasks (PVTs) were administered six times on shift. CBT was monitored via ingestible capsules. Daily CBT minimum (CBTmin) time was compared to the timing of the worst PVT performance on-shift (task with most lapses). Results In the parent study, circadian lighting improved on-shift performance and sleep quality. These effects were accompanied by a significant day-by-condition interaction effect on the degree of temporal offset between CBTmin time and worst PVT performance time during the work shift, F(3,74.660)= 4.09, p=0.01; the disparity increased over successive days under the influence of circadian-informed lighting compared to standard lighting., p&amp;lt;0.01. Conclusions The modest adjustment in the timing of the worst on-shift performance provides support that circadian lighting improves on-shift performance. These results emphasise the importance of considering the combined impact of circadian rhythms, sleep patterns, and time-on-task effects on performance outcomes when assessing fatigue and implementing countermeasures to phase-shift biological rhythms.

O077 The Impact of Breaking up sitting during Simulated Nightshifts on Driving Performance during the Commute Home

Abstract Introduction The commute home from a nightshift is associated with increased accident risk. Driving performance strategies typically occur immediately before or during the commute, such as napping and caffeine. It is unknown whether strategies that target alertness throughout the nightshift could impact the commute home. Breaking up sitting with walking is an effective strategy to improve alertness during dayshifts. This study investigated the impact of breaking up sitting during the nightshift on driving performance post-shift. Method 41 adults (age M±SD: 24.4±4.6 years; 21 females) participated in a 7-day laboratory study, with 5 nightshifts (2200-0630). Participants were randomly allocated to: Breaking up sitting (BUS; n=21) or Sedentary (SED; n=20). Every 30-min during the nightshift BUS participants completed 3-min bouts of light-intensity walking, while SED participants remained sitting. At 2130 (pre-shift) and 0700 (post-shift) participants completed a 20-min simulated drive and the Karolinska Sleepiness Scale. Results Linear mixed models revealed a significant interaction between time (pre- or post-shift) and nightshift on driving performance and sleepiness, such that there was increased lane variability (p=0.03), speed variability (p&amp;lt;0.05), and sleepiness (p&amp;lt;0.05) post-shift compared to pre-shift, with performance worse on the first nightshift. There were no significant 2-way or 3-way interactions between condition (BUS or SED), time, or nightshift. Discussion Breaking up sitting with light-intensity walking did not improve performance for the commute home. However, given that breaking up sitting did not increase risk on the commute home, and it has benefits for cardiovascular health, it is an important strategy to promote to nightshift workers.

O073 The Relationship between Circadian type and Physical Activity on Cognitive Performance during Simulated Nightshifts: A Randomised Controlled Trial.

Abstract Introduction Physical activity might be a nonphotic strategy which could improve cognitive performance for nightshift workers. Innate characteristics like circadian type may also influence individual performance. Thus, this study explores the relationship between circadian type and physical activity on cognition over consecutive nightshifts. Methods Thirty-two healthy adults (age M±SD: 24.3±4.6 years; 19 females) participated in a 7-day laboratory study, with 5 nightshifts (2200-0600). Participants were randomised into the Breaking up sitting (BUS; n=19) or Sedentary (SED; n=13) condition. Overnight, BUS participants completed 3-min bouts of light-intensity walking every 30-min, while SED participants remained seated. At 2200, 0000, 0200, 0400 and 0600, participants completed the 10-min Psychomotor Vigilance Task (mean RRT). Participants completed the 11-item revised Circadian Type Inventory (factor 1: rigid/flexible; factor 2: languid/vigorous), resulting in four-subgroups (rigid; n= 12, flexible; n= 11, and languid; n= 11, vigorous; n= 13). Participants may only be one type from either factor (i.e. rigid and vigorous). Results Linear mixed models showed a significant 3-way interaction between nightshift (1-5), condition (BUS, SED), and circadian type (rigid/flexible) for mean RRT (p=0.03), such that flexible types in the Breaking up sitting condition outperformed Sedentary flexible types and Breaking up sitting rigid types, with performance worse on the first nightshift. There were no significant interactions between nightshift, condition and circadian type (languid/vigorous). Discussion Breaking up sitting improved performance for flexible types over rigid types. These findings have significant implications for nightshift rostering, suggesting that incorporating breaking up sitting may optimise cognitive performance, and therefore work efficiency.

P052 Is Circadian Adaptation to Night Work Affected by the Intensity of Ambient Lighting?

Abstract Introduction The aim of this study was to examine whether the intensity of ambient lighting affects the rate at which the human circadian system adapts to working at night. Methods. The whole study will include 60 participants (50:50, F:M; aged 28–35yr; good sleep/health) randomised to one of three conditions. In each condition, participants work 14 x 12-hr simulated night shifts (19:00–07:00h) while living 24h/day in an accommodation suite. The only difference between conditions is in the light intensity during night shifts – dim (5–10lx), moderate (50–100lx), normal (300–350lx). Circadian adaptation is being assessed using the hourly rate of 6-sulphatoxymelatonin (aMT6s) production during sleep. Results The project is in progress, so these results are for the first 6–12 participants in each condition. For each day, circadian adaptation is assessed by expressing the rate of aMT6s excreted during the daytime sleep period as a percentage of the rate of aMT6s excreted during the night-time baseline sleep period (for an adaption score of 0–100%). On average, participants in the dim condition are adapted by 26%,37%,32% after nights 1,7,14; participants in the moderate condition are adapted by 23%,37%,60% after nights 1,7,14; and participants in the normal condition are adapted by 27%,117%,103% after nights 1,7,14. Discussion These data indicate that the rate, and degree, of circadian adaptation to night work is substantially affected by the intensity of ambient lighting. Therefore, lighting conditions should be incorporated into OHS guidelines related to managing the fatigue risks associated with night work.

Impact Of Simulated Night Shift Work On Subjective Desire To Eat In Healthy Lean Adults

Impact Of Simulated Night Shift Work On Subjective Desire To Eat In Healthy Lean Adults

Effect of Short versus Long Duration Naps on Blood Pressure during Simulated Night Shift Work: A Randomized Crossover Trial

Objective Blunting of the sleep-related dip in blood pressure (BP) has been linked to numerous cardiovascular outcomes including myocardial infarction. Blunting of BP dipping occurs during night shift work and previous research suggest that a 60-min or longer on-shift nap is needed to restore normal/healthy BP dipping. We sought to determine the effect of different durations of napping on BP during and following simulated night shifts. We hypothesized that the greatest benefit in terms of restoration of normal BP dipping during night shift work would be observed during a longer duration nap versus a shorter nap opportunity. Methods We used a randomized crossover laboratory-based study design. Participants consented to complete three separate 72-hr conditions that included a 12-hr simulated night shift. Nap conditions included a 30-min and 2-hr nap compared to a no-nap condition. Ambulatory BP monitoring was assessed hourly and every 10-30 mins during in-lab naps. Blunted BP dipping during in-lab naps was the primary outcome. Goal enrollment of 25 (35 with attrition) provided 80% power to detect a mean difference of 5 mmHg in BP between nap conditions. Results Of the 58 screened, 28 were consented, and 26 completed all three 72-hr conditions. More than half (53.6%) were female. Mean age was 24.4 years (SD7.2). Most (85.7%) were certified as emergency medical technicians or paramedics. The mean percentage dip in systolic BP (SBP) and diastolic BP (DBP) did not differ between the 30-min and 2-hr nap conditions (p > 0.05), yet a greater proportion of participants experienced a 10-20% dip in SBP or DBP during the 2-hr nap versus the 30-min nap (p < 0.05). For every additional minute of total sleep during the 30-min nap, the percentage of SBP dip improved by 0.60%, and the percentage of DBP dip improved by 0.68% (p < 0.05). These improvements approximate to a 6% per minute relative advancement toward normal/healthy BP dipping. Conclusions Restoration of a normal/healthy dip in BP is achievable during short and long duration nap opportunities during simulated night shift work. Our findings support the hypothesis that BP dipping is more common during longer 2-hr versus shorter 30-min naps. Trial registration ClinicalTrials.gov, NCT04469803. Registered on 9 July 2020.

Effects of 90- and 30-min naps or a 120-min nap on alertness and performance: reanalysis of an existing pilot study

The aim of this study was to investigate alertness and cognitive performance immediately after and until the end of the night shift after taking a 120-min monophasic nap (One-nap) or a split 90-min and 30-min nap (Two-nap) during a 16-h simulated night shift, and the relationship between sleep quality and both alertness and performance. This study was performed in 41 females. Among them, 15 participants were included in the No-nap group, 14 in the One-nap group (22:00–00:00), and 12 in the Two-nap group (22:30–00:00 and 02:30–03:00). Participants were tested every hour from 16:00 to 09:00 for performance on the Uchida-Kraepelin test, as well as for subjective feelings of fatigue and drowsiness, body temperature, and heart rate variability. The shorter the sleep latency, the worse the alertness immediately after the 90-min nap. The 120-min and 30-min naps also revealed that prolonged total sleep time led to increased fatigue and drowsiness upon awakening. From 04:00 to 09:00, in the No-nap and One-nap groups, fatigue was higher than in the Two-nap group. The One-nap and Two-nap groups did not show improved morning performance. These results suggest that a split nap might improve drowsiness and fatigue during a long night shift.

Are Short Duration Naps Better than Long Duration Naps for Mitigating Sleep Inertia? Brief Report of a Randomized Crossover Trial of Simulated Night Shift Work

Objective We sought to test the effects of different duration naps on post-nap cognitive performance during simulated night shifts. Methods We used a randomized laboratory-based crossover trial design with simulated 12-hr night shifts and each participant completing three conditions of 72 hrs each (Clinicaltrials.gov; registration # NCT04469803). The three conditions tested included no-nap, a 30-min nap opportunity, and a 2-hr nap opportunity. Naps occurred at 02:00 hrs. Cognitive performance was assessed with the Brief 3-min Psychomotor Vigilance Test (PVT-B). Four PVT-B measures include: reaction time (RT in milliseconds (ms)), lapses (RT > 355 ms), false starts (reactions before stimulus or RT <100 ms), and speed (1,000/RT). The PVT-B was performed at the start of the simulated night shift (19:00), end of shift (07:00), pre-nap (02:00), and at 0 mins, 10 mins, 20 mins, and 30 mins following the 30-min and 2-hr nap conditions. Simultaneously, participants reported subjective ratings of fatigue and other constructs. Results Twenty-eight (15 female), mostly certified emergency medical technicians or paramedics, consented to participate. For all three conditions, looking within condition, PVT-B lapse performance at the end of the 12-hr simulated night shift (at 07:00) was poorer compared to shift start (p < 0.05). Performance on PVT-B speed, RT, and false starts were poorer at shift end than shift start for the no-nap and 30-min nap conditions (p < 0.05), but not for the 2-hr nap condition (p > 0.05). Compared to pre-nap measures, performance on the PVT-B assessed at 0 mins post-nap showed significant performance declines for lapses and speed for both the 30-min and 2-hr nap conditions (p < 0.05), but not at 10, 20, or 30 mins post-nap. After waking from the 2-hr on-shift nap opportunity (at 0 mins), participants rated sleepiness, difficulty with concentration, and alertness poorer than pre-nap (p < 0.05). Participants in the 30-min nap condition rated alertness poorer immediately after the nap (at 0 mins) compared to pre-nap (p < 0.05) Conclusions While sleep inertia was detectable immediately following short 30-min and long 2-hr nap opportunities during simulated night shift work, deficits in cognitive performance and subjective ratings quickly dissipated and were not detectable at 10–30 mins post-nap.

0003 Sleep and Circadian Disruption Induced by Simulated Night Shift Work Impair Cardiometabolic Outcomes in Healthy Adults

Abstract Introduction People who work evening, night or rotating shifts make up 20% of the US workforce and have a heightened risk for Type 2 diabetes (T2D) and cardiovascular disease (CVD) compared to people who work days, possibly due to repeated bouts of sleep and circadian disruption. However, the mechanism(s) by which sleep and circadian disruption impair cardiometabolic health are unclear. We therefore investigated the impact of acute circadian misalignment on factors related to cardiometabolic health including interstitial glucose concentration, glucose tolerance, resting systolic blood pressure (SBP), diastolic blood pressure (DBP) and heart rate (HR). Methods Ten healthy adults (6F, 25.0±4.5y, BMI: 22.0±2.2kg/m2; mean±SD) participated in an ongoing 6d inpatient simulated night shift protocol to induce sleep and circadian disruption. Participants lived at the Sleep and Metabolism Laboratory for 2d to simulate day shift work followed by 2d of simulated night shift work. Continuous interstitial glucose monitoring was conducted throughout the study (FreeStyle Libre Pro; Abbott, Alameda, CA, USA). BP and HR were assessed 30 minutes after waketime (Omron HEM-FL31; Omron Healthcare, Kyoto, JP) followed by an oral glucose tolerance tests (OGTT) conducted 1.5h after waketime in both conditions. Results Simulated night shift work was associated with significantly higher interstitial glucose area under the curve (AUC) in response to an identical first meal after waking (18,299±1412 v 14,606±2035 [mg/dl]*min; p=0.009; mean±SEM) as well as plasma glucose AUC during the OGTT (23,239±2574 v 18,776±1832; p=0.002) compared to simulated day work. Furthermore, simulated night shift work was associated with a significant increase in resting DBP (75±3 v 66±2; p=0.017) compared to day work. No changes were observed in resting SBP (p=0.40) or HR (p=0.11) between conditions. Conclusion Sleep and circadian disruption induced by simulated night shift work appear to impair markers of cardiometabolic health, even in healthy, lean adults. Night shift work is largely unavoidable in modern society, thus is it critical to identify strategies or countermeasures to prevent the impact of circadian misalignment on T2D and CVD risk in a large portion of the population. Support (if any) This project was supported in part by R01DK125653 &amp; F31HL165883.