Calibrated to drive: Measuring self-assessed driving ability and perceived workload after prolonged sitting and sleep restriction.

Self-assessed driving ability may differ from actual driving performance, leading to poor calibration (i.e., differences between self-assessed driving ability and actual performance), increased risk of accidents and unsafe driving behaviour. Factors such as sleep restriction and sedentary behaviour can impact driver workload, which influences driver calibration. This study aims to investigate how sleep restriction and prolonged sitting impact driver workload and driver calibration to identify strategies that can lead to safer and better calibrated drivers. Participants (n = 84, mean age = 23.5 ± 4.8, 49 % female) undertook a 7-day laboratory study and were randomly allocated to a condition: sitting 9-h sleep opportunity (Sit9), breaking up sitting 9-h sleep opportunity (Break9), sitting 5-h sleep opportunity (Sit5) and breaking up sitting 5-h sleep opportunity (Break5). Break9 and Break5 conditions completed 3-min of light-intensity walking on a treadmill every 30 min between 09:00-17:00 h, while participants in Sit9 and Sit5 conditions remained seated. Each participant completed a 20-min simulated commute in the morning and afternoon each day and completed subjective assessments of driving ability and perceived workload before and after each commute. Objective driving performance was assessed using a driving simulator measuring speed and lane performance metrics. Driver calibration was analysed using a single component and 3-component Brier Score. Correlational matrices were conducted as an exploratory analysis to understand the strength and direction of the relationship between subjective and objective driving outcomes. Analyses revealed participants in Sit9 and Break9 were significantly better calibrated for lane variability, lane position and safe zone-lane parameters at both time points (p < 0.0001) compared to Sit5 and Break5. Break5 participants were better calibrated for safe zone-speed and combined safe zone parameters (p < 0.0001) and speed variability at both time points (p = 0.005) compared to all other conditions. Analyses revealed lower perceived workload scores at both time points for Sit9 and Break9 participants compared to Sit5 and Break5 (p = <0.001). Breaking up sitting during the day may reduce calibration errors compared to sitting during the day for speed keeping parameters. Future studies should investigate if different physical activity frequency and intensity can reduce calibration errors, and better align a driver's self-assessment with their actual performance.

Move the night way: how can physical activity facilitate adaptation to shift work?

Shift work, involving night work, leads to impaired sleep, cognition, health and wellbeing, and an increased risk of occupational incidents. Current countermeasures include circadian adaptation to phase shift circadian biomarkers. However, evidence of real-world circadian adaptation is found primarily in occupations where light exposure is readily controlled. Despite this, non-photic adaptation to shift work remains under researched. Other markers of shift work adaptation exist (e.g., improvements in cognition and wellbeing outcomes) but are relatively unexplored. Timeframes for shift work adaptation involve changes which occur over a block of shifts, or over a shift working career. We propose an additional shift work adaptation timeframe exists which encompasses acute within shift changes in markers of adaptation. We also propose that physical activity might be an accessible and cost-effective countermeasure that could influence multiple markers of adaptation across three timeframes (Within Shift, Within Block, Within Work-span). Finally, practical considerations for shift workers, shift work industries and future research are identified.

The Development and Validation of the Health Belief Model for Shift Workers (HBM-SW) Scale.

OBJECTIVE: Shift work is associated with circadian misalignment, sleep loss, and suboptimal health behaviors, which may contribute to longer term negative health outcomes. To inform future interventions for shift workers, the present study aimed to develop and evaluate the Health Belief Model for Shift Workers (HBM-SW) scale. METHODS: The HBM-SW development involved a seven-step process, including a literature review, expert panel analysis, cognitive interviews with shift workers, and a trial with a pilot sample of shift workers (n = 153). Utilizing exploratory factor analysis for factor identification and item reduction, the developed scale loaded on seven factors in line with the theoretical framework of the Health Belief Model: Perceived Threat, Perceived Severity, Perceived Benefits, Perceived Barriers, Cues to Action, Self-efficacy, and Health Motivation. Validation of the scale was conducted utilizing Pittsburgh Sleep Quality Index, International Physical Activity Questionnaire, and Food Frequency Questionnaire. RESULTS: The pilot sample had an average age of 34.0 (18.0) years, was majority female (54.2%), with an average of 8.0 (11.0) years shift work experience. The HBM-SW showed good - excellent (α = 0.74-0.93) internal consistency and moderate - good (ICC = 0.64-0.89) test re-test reliability. Using health behavior outcome measures, the HBM-SW scale showed meaningful correlations with sleep quality, sleep duration, diet quality and leisure time physical activity, and acceptable validity and reliability. Further testing should be conducted in a larger sample to facilitate confirmatory factor analysis. CONCLUSIONS: The developed Health Belief Model for Shift Workers scale is likely beneficial for use in future studies of interventions for shift workers.

How do infant feeding method, sleeping location, and postpartum depression interact with maternal sleep quality?

New mothers generally experience poor and/or disrupted sleep. A range of infant care and mental health factors may impact new mothers' sleep quality. A cross-sectional online survey was completed by a sample of 101 Australian new mothers with children under 12 months (M = 5.52 months, SD = 3.29 months) to examine the relationship between infant feeding method, infant sleeping location, and postpartum depression with maternal sleep quality. Subjective maternal sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI), and postpartum depression was measured using the Edinburgh Postpartum Depression Scale (EPDS). Overall, new mothers experienced poor subjective sleep quality, with high average PSQI scores, above the cut-off of 5 (M = 9.63, SD = 4.07). The majority of new mothers did not experience postpartum depression, with an average EPDS score below the cut-off of 11 (8.66, SD = 5.20). Mothers who breastfed their infants experienced significantly better subjective sleep quality than mothers who bottle-fed, with a medium effect size (ηp2 = 0.458). Subjective maternal sleep quality did not differ based on infant sleeping location. Poor subjective maternal sleep quality was a significant predictor of postpartum depression. While poor sleep was common in this sample of Australian new mothers, this study demonstrated that new mothers who breastfeed may experience slightly better subjective sleep quality than other feeding methods. Further research into, and better services for the education and advocation of, new mothers' sleep quality will be beneficial to both new mothers and clinicians.

"Mars Bar and a Tin of Red Bull Kept Me and My Patients Alive": Exploring Barriers to Healthy Eating through Facebook Comments of Shiftworkers.

The negative impact of an unhealthy diet on the shiftworker population has been well-documented. However, little evidence exists on the underlying reasons for unhealthy eating behaviours and the existing barriers to healthy eating withinshiftwork environments. This qualitative study investigated the dietary behaviours reported by shiftworkers through Facebook comments. Comments were collected if they were on public shiftworker-relevant posts pertaining to dietary news or dietary information on Facebook and were posted by self-identified shiftworkers, relatives of shiftworkers, or partners of shiftworkers. A thematic analysis of the 144 comments collected generated four categories that can be used to understand the motivations for eating behaviour on-shift: what shiftworkers eat, where food is sourced from, when food is eaten, and why certain foods are chosen. Results reveal motivations, attitudes, and both internal and external barriers to healthy eating behaviours, as well as similarities and differences across shiftwork industries. Recommendations for future research include further explorations on the link between scheduled eating (e.g., time-restricted eating) and shiftwork, the impact of a rotating shift arrangements on dietary health behaviours, and the impact of interpersonal relationships on shiftworker dietary choices. Understanding these motivations will inform strategies to promote healthy eating and help understand barriers for shiftworkers.

Sleep hygiene strategies for individuals with chronic pain: a scoping review.

OBJECTIVES: Up to a quarter of the world's population experience chronic pain, which, in addition to interfering with daily activities and waking function, is often associated with poor sleep. Individuals experiencing poor sleep are often encouraged to implement sleep hygiene strategies. However, current sleep hygiene strategies have not been developed considering the unique challenges faced by individuals with chronic pain and therefore they might not be as effective in this population. The aim of this scoping review is to map the state of the existing literature examining sleep hygiene strategies in individuals with chronic pain. DESIGN: This scoping review included a search of four online databases (Medline, Embase, PsycINFO and CINAHL) to identify articles examining the use of sleep hygiene strategies in populations with chronic pain. RESULTS: Thirty articles investigated at least one sleep hygiene strategy in individuals with chronic pain, with improvements to sleep reported for six sleep hygiene strategies (education, exercise, limiting alcohol use, limiting tobacco use, prebed state and sleep environment). However, the timing of these strategies was often not reported which limits the degree to which these strategies can be generalised for use as a presleep strategy. CONCLUSION: This scoping review examined the existing literature focusing on sleep hygiene strategies for people with chronic pain. There are limitations to the methodology of the existing literature and gaps in our understanding of sleep hygiene strategies in some chronic pain conditions that must be addressed in future research before the effectiveness of these strategies can be understood.

A Deep Learning Approach to Classify Sitting and Sleep History from Raw Accelerometry Data during Simulated Driving.

Prolonged sitting and inadequate sleep can impact driving performance. Therefore, objective knowledge of a driver's recent sitting and sleep history could help reduce safety risks. This study aimed to apply deep learning to raw accelerometry data collected during a simulated driving task to classify recent sitting and sleep history. Participants (n = 84, Mean ± SD age = 23.5 ± 4.8, 49% Female) completed a seven-day laboratory study. Raw accelerometry data were collected from a thigh-worn accelerometer during a 20-min simulated drive (8:10 h and 17:30 h each day). Two convolutional neural networks (CNNs; ResNet-18 and DixonNet) were trained to classify accelerometry data into four classes (sitting or breaking up sitting and 9-h or 5-h sleep). Accuracy was determined using five-fold cross-validation. ResNet-18 produced higher accuracy scores: 88.6 ± 1.3% for activity (compared to 77.2 ± 2.6% from DixonNet) and 88.6 ± 1.1% for sleep history (compared to 75.2 ± 2.6% from DixonNet). Class activation mapping revealed distinct patterns of movement and postural changes between classes. Findings demonstrate the suitability of CNNs in classifying sitting and sleep history using thigh-worn accelerometer data collected during a simulated drive. This approach has implications for the identification of drivers at risk of fatigue-related impairment.

Interventions to improve sleep in caregivers: A systematic review and meta-analysis.

Unpaid caregivers often experience sleep impairments as an unintended consequence of providing care. This systematic review and meta-analysis investigated the efficacy of interventions to improve sleep in unpaid caregivers. Six databases were searched from journal inception to 7-Sep-2021 to identify randomised controlled trials. Random-effects meta-analyses estimated mean differences (MD) at end-of-intervention. Twenty-one studies were identified (15 eligible for meta-analysis). Compared to control, interventions improved sleep quality (Pittsburgh Sleep Quality Index; 12 studies, 1153 participants, MD = -1.66, 95% CI [-2.91, -0.41], p = 0.009, I2 = 90.51%, GRADE = low), and total sleep time (hours; two studies, 122 participants, MD = 0.45, 95% CI [0.42, 0.48], p = 0.003, I2 = 0.00%, GRADE = low), but not sleeping problems (sleep item on Symptom Distress Scale of the Omega Screening Questionnaire; two studies, 529 participants, MD = -0.06, 95% CI [-0.69, 0.58], p = 0.458, I2 = 0.01%, GRADE = low). There is low quality evidence that interventions improve sleep quality in unpaid caregivers compared to control. Limitations include the lack of evidence for specific intervention modes and limited use of objective sleep measures. Future research should explore potential effect modifiers such as care recipient condition (CRD42021278670).

A Time to Rest, a Time to Dine: Sleep, Time-Restricted Eating, and Cardiometabolic Health.

Cardiovascular disease (CVD) poses a serious health and economic burden worldwide. Modifiable lifestyle factors are a focus of research into reducing the burden of CVD, with diet as one of the most investigated factors. Specifically, the timing and regularity of food intake is an emerging research area, with approaches such as time-restricted eating (TRE) receiving much attention. TRE involves shortening the time available to eat across the day and is associated with improved CVD outcomes compared with longer eating windows. However, studies that have examined TRE have not considered the impact of sleep on CVD outcomes despite recent evidence showing that sleep duration can influence the timing and amount of food eaten. In this article, we argue that as TRE and sleep influence each other, and influence the same cardiometabolic parameters, experiencing inadequate sleep may attenuate any positive impact TRE has on CVD. We examine the relationship between TRE and CVD, with sleep as a potential mediator in this relationship, and propose a research agenda to investigate this relationship. This will provide necessary evidence to inform future interventions aimed at reducing the burden of CVD.

Does breaking up sitting in office-based settings result in cognitive performance improvements which last throughout the day? A review of the evidence.

Sedentary behavior at work contributes to detrimental cognitive outcomes (e.g., decreases in attention). The length of time that cognitive performance benefits are sustained following bouts of breaking up sitting (e.g., using sit-stand desks or walking) is not known. A narrative review of the literature was conducted using a systematic search strategy, with keywords related to breaking up sitting interventions in office-based environments and cognitive performance outcomes in the period immediately post the cessation of the breaking up sitting intervention. Three types of office-based breaking up sitting interventions were identified; 1) sit-stand desks, 2) walking desks and 3) cycling desks. From the eight studies which met the criteria, the impacts of these interventions on cognitive performance outcomes were mixed, with significant benefits in some studies and others reporting no benefit. Of the cognitive domains assessed, working memory, attention, and psychomotor function showed significant sustained improvement for up to 30 minutes post intervention. While there are benefits to a key set of cognitive performance domains following breaking up sitting interventions in office-based settings, no studies have evaluated whether benefits to cognitive performance persist for longer than 30 minutes after the breaking up sitting intervention. Furthermore, specific applications of these cognitive benefits to tasks outside of work (e.g., driving home from work) are unknown.

The impact of a truncated competition on the sleep and wellness of sub-elite netballers.

BACKGROUND: Sleep and wellness outcomes have been explored in elite netball athletes, but research examining these outcomes in sub-elite athletes is lacking despite high participation rates at the sub-elite level. The aim was to investigate the impact of the scheduling of games over consecutive days during a truncated four-round netball competition on the sleep and wellness outcomes of sub-elite netballers. METHODS: A total of 12 female, sub-elite netball players were examined via sleep outcomes, stress, fatigue, mood, muscle soreness, and overall wellness on the night before, the night of, and for two nights after games during a four-round truncated competition. Linear mixed models examined changes for variables across days around game day. RESULTS: Bedtime (P=0.038), wake time (P=0.001), fatigue (P=0.003), and muscle soreness (P<0.001) differed according to game status (i.e., pre-game days, game days, and post-game days). Bedtime was later on game days compared to pre-game days, and wake-up time was later on post-game days than pre-game days. Fatigue and muscle soreness were greater the day after the game, compared to days before the game. Over the four rounds, bedtime (P=0.027) and wake-up time (P<0.001) tended to be later, while wellness did not change. CONCLUSIONS: These data may help guide coaching staff to plan training and travel arrangements during truncated multi-week competitions.

The Relationship Between Diet and Sleep in Older Adults: a Narrative Review.

PURPOSE OF REVIEW: Older adults more frequently experience reduced sleep quality and quantity compared to younger adults. Diet is one modifiable lifestyle factor that may influence sleep outcomes in older adults. The purpose of this review is to synthesise the current literature investigating the impact of diet, including foods and nutrients, on the sleep quality and quantity of older adults. RECENT FINDINGS: Overall, the observational and intervention studies suggest that following a Mediterranean diet, and the consumption of certain food items (e.g. milk), and nutrients (e.g. vitamin D and vitamin E) may influence (improve or reduce) sleep quality and quantity. This review describes the potential efficacy for dietary factors to improve sleep outcomes in older adults. However, given the heterogeneity of included studies in this review (i.e. aims, methodologies, and outcomes assessed), it is difficult to consolidate the available evidence to make specific recommendations. More targeted research exploring the relationship between diet and sleep in older adults is needed to strengthen the current evidence base.

Sleep and physical activity in university students: A systematic review and meta-analysis.

University students have low levels of physical activity and report disturbances to sleep, which are independently associated with poor health outcomes. Some research suggests that there is a bi-directional relationship between sleep and physical activity in adults. However, the relationship between sleep and physical activity in university students has not yet been evaluated. Therefore, the aim of this systematic review and meta-analysis was to qualitatively synthesise and quantitatively evaluate the evidence for the association between sleep and physical activity in university students. Twenty-nine eligible studies were included, with a total of 141,035 participants (43% men and 57% women). Only four studies used device-based measures of sleep and/or physical activity, with the remainder including self-report measures. Qualitative synthesis found that the majority of studies did not find any association between sleep and physical activity in university students. However, random-effects meta-analysis showed that moderate-to-high intensity physical activity was associated with lower PSQI scores (e.g., better sleep quality) [r = -0.18, 95% CI (-0.37, 0.03), p = 0.100]. Further, a weak negative association between moderate-to-vigorous physical activity level and sleep duration was also found [r = -0.02, 95% CI (-0.16, 0.12), p = 0.760]. As the findings of this review are predominantly derived from cross-sectional investigations, with limited use of device-based measurement tools, further research is needed to investigate the relationship between sleep and physical activity in university students. Future studies should employ longitudinal designs, with self-report and device-based measures, and consider the intensity and time of physical activity as well as records of napping behaviour.

The Discrepancy between Knowledge of Sleep Recommendations and the Actual Sleep Behaviour of Australian Adults.

Introduction: Inadequate sleep is a major public health concern, with large economic, health, and operational costs to Australia. Despite the implementation of public sleep health campaigns, approximately 40% of Australian adults do not obtain the recommended 7-9 hours of sleep. Thus, while people may know how much sleep is required, this knowledge may not be adequately translated to actual sleep behavior. Consequently, this study aims to examine the discrepancy between knowledge of sleep recommendations and self-reported sleep behaviors.Methods: A sample of 1265 Australian adults (54% female, aged 18-65) completed a phone interview as part of the 2017 National Social Survey and were asked questions about their knowledge of sleep guidelines and their actual sleep behavior. Binary logistic regression was used to determine the factors associated with awareness of sleep recommendations and whether this corresponded with reported sleep duration.Results: The final sample size was 998. Although 94% of the sample were aware of current sleep recommendations, 23% of participants did not self-report regularly obtaining 7-9 h sleep per night. These participants were less likely to want to obtain more sleep, less likely to view sleep as a priority before stressful events, and less likely to self-report good health.Conclusion: Although a majority of the sample were aware of sleep recommendations, almost a quarter of the participants' behavior did not align with their knowledge. Future sleep health campaigns should consider options beyond education, including emphasis on practical strategies and modifiable lifestyle factors to assist individuals to obtain the recommended amount of sleep.

The impact of a meal, snack, or not eating during the night shift on simulated driving performance post-shift.

Objective The commute home following a night shift is associated with an increased risk for accidents. This study investigated the relationship between food intake during the night shift and simulated driving performance post-shift. Methods Healthy non-shift working males (N=23) and females (N=16), aged 18-39 years (mean 24.5, standard deviation 5.0, years) participated in a seven-day laboratory study and underwent four simulated night shifts. Participants were randomly allocated to one of three conditions: meal at night (N=12; 7 males), snack at night (N=13; 7 males) or no eating at night (N=14; 9 males). During the night shift at 00:30 hours, participants either ate a large meal (meal at night condition), a snack (snack at night condition), or did not eat during the night shift (no eating at night condition). During the second simulated night shift, participants performed a 40-minute York driving simulation at 20:00, 22:30, 01:30, 04:00, and 07:30 hours (similar time to a commute from work). Results The effects of eating condition, drive time, and time-on-task, on driving performance were examined using mixed model analyses. Significant condition×time interactions were found, where at 07:30 hours, those in the meal at night condition displayed significant increases in time spent outside of the safe zone (percentage of time spent outside 10 km/hour of the speed limit and 0.8 meters of the lane center; P<0.05), and greater lane and speed variability (both P<0.01) compared to the snack and no eating conditions. There were no differences between the snack and no eating conditions. Conclusion Driver safety during the simulated commute home is greater following the night shift if a snack, rather than a meal, is consumed during the shift.

The impact of dayshifts and sleepover nightshifts on the eating and driving behaviours of residential support workers: An exploratory workplace study.

BACKGROUND: Residential support workers (RSWs) provide 24-hour care to clients and many work overnight sleepover nightshifts. Although RSWs perform safety-critical tasks and are at high-risk of work stress and exhaustion, the health and safety of RSWs has not been investigated. OBJECTIVE: This explorative workplace case study explored the impact of support work on the eating and driving behaviours of RSWs. METHODS: Thirteen RSWs who had worked a dayshift (n = 6) or a sleepover nightshift (n = 7) completed questions on the timing of food intake during their shift, motivations for eating during the shift, subjective work performance, alertness and sleepiness post-shift, and driving performance post-shift. RESULTS: RSWs reported snacking during the night on a sleepover nightshift. Time available was the biggest determinant for when RSWs ate during a day and sleepover nightshift. Ratings of subjective alertness and sleepiness after eating were not different between shift types, however participants reported an increase in work performance after eating during a dayshift. Driving events were more frequently reported post-sleepover nightshift, compared to post-dayshift. CONCLUSIONS: Findings demonstrate an impact of shift type on eating and driving behaviours of RSWs and highlight the importance of further investigation of this under-researched group to identify appropriate strategies for improving health and safety.

Are prolonged sitting and sleep restriction a dual curse for the modern workforce? a randomised controlled trial protocol.

INTRODUCTION: Prolonged sitting and inadequate sleep are a growing concern in society and are associated with impairments to cardiometabolic health and cognitive performance. However, the combined effect of prolonged sitting and inadequate sleep on measures of health and cognitive performance are unknown. In addition, the circadian disruption caused by shiftwork may further impact workers' cardiometabolic health and cognitive performance. This protocol paper outlines the methodology for exploring the impact of simultaneous exposure to prolonged sitting, sleep restriction and circadian disruption on cardiometabolic and cognitive performance outcomes. METHODS AND ANALYSIS: This between-subjects study will recruit 208 males and females to complete a 7-day in-laboratory experimental protocol (1 Adaptation Day, 5 Experimental Days and 1 Recovery Day). Participants will be allocated to one of eight conditions that include all possible combinations of the following: dayshift or nightshift, sitting or breaking up sitting and 5 hour or 9 hour sleep opportunity. On arrival to the laboratory, participants will be provided with a 9 hour baseline sleep opportunity (22:00 to 07:00) and complete five simulated work shifts (09:00 to 17:30 in the dayshift condition and 22:00 to 06:30 in the nightshift condition) followed by a 9 hour recovery sleep opportunity (22:00 to 07:00). During the work shifts participants in the sitting condition will remain seated, while participants in the breaking up sitting condition will complete 3-min bouts of light-intensity walking every 30 mins on a motorised treadmill. Sleep opportunities will be 9 hour or 5 hour. Primary outcome measures include continuously measured interstitial blood glucose, heart rate and blood pressure, and a cognitive performance and self-perceived capacity testing battery completed five times per shift. Analyses will be conducted using linear mixed models. ETHICS AND DISSEMINATION: The CQUniversity Human Ethics Committee has approved this study (0000021914). All participants who have already completed the protocol have provided informed consent. Study findings will be disseminated via scientific publications and conference presentations. TRIAL REGISTRATION DETAILS: This study has been registered on Australian New Zealand Clinical Trials Registry (12619001516178) and is currently in the pre-results stage.

Hot, Tired and Hungry: The Snacking Behaviour and Food Cravings of Firefighters During Multi-Day Simulated Wildfire Suppression.

Firefighters are exposed to numerous stressors during wildfire suppression, including working in hot temperatures and sleep restricted conditions. Research has shown that when sleep restricted, individuals choose foods higher in carbohydrates, fat, and sugar, and have increased cravings for calorie dense foods. However, there is currently no research on the combined effect of heat and sleep restriction on snacking behaviour. Conducting secondary analyses from a larger study, the current study aimed to investigate the impact of heat and sleep restriction on snacking behaviour and food cravings. Sixty-six firefighters completed three days of simulated physically demanding firefighting work and were randomly allocated to either the control (n = 18, CON; 19 °C, 8h sleep opportunity), sleep restricted (n = 16, SR; 19 °C, 4-h sleep opportunity), hot (n = 18, HOT; 33 °C, 8h sleep opportunity), or hot and sleep restricted (n = 14 HOT + SR; 33 °C, 4-h sleep opportunity) condition. During rest periods firefighters were able to self-select sweet, savoury, or healthy snacks from a ration pack and were asked to rate their hunger, fullness, and cravings every two hours (eating block). Mixed model analyses revealed no difference in total energy intake between conditions, however there was a significant interaction between eating block and condition, with those in the CON, HOT, and HOT + SR condition consuming significantly more energy between 1230 and 1430 compared to the SR condition (p = 0.002). Sleep restriction and heat did not impact feelings of hunger and fullness across the day, and did not lead to greater cravings for snacks, with no differences between conditions. These findings suggest that under various simulated firefighting conditions, it is not the amount of food that differs but the timing of food intake, with those that are required to work in hot conditions while sleep restricted more likely to consume food between 1230 and 1430. This has potential implications for the time of day in which a greater amount of food should be available for firefighters.

Altering meal timing to improve cognitive performance during simulated nightshifts.

Altering meal timing could improve cognition, alertness, and thus safety during the nightshift. This study investigated the differential impact of consuming a meal, snack, or not eating during the nightshift on cognitive performance (ANZCTR12615001107516). 39 healthy participants (59% male, age mean±SD: 24.5 ± 5.0y) completed a 7-day laboratory study and underwent four simulated nightshifts. Participants were randomly allocated to: Meal at Night (MN; n= 12), Snack at Night (SN; n = 13) or No Eating at Night (NE; n = 14). At 00:30 h, MN consumed a meal and SN consumed a snack (30% and 10% of 24 h energy intake respectively). NE did not eat during the nightshift. Macronutrient intake was constant across conditions. At 20:00 h, 22:30 h, 01:30 h, and 04:00 h, participants completed the 3-min Psychomotor Vigilance Task (PVT-B), 40-min driving simulator, post-drive PVT-B, subjective sleepiness scale, 2-choice Reaction Time task, and Running Memory task. Objective sleep was recorded for each of the day sleeps using Actigraphy and for the third day sleep, Polysomnography was used. Performance was compared between conditions using mixed model analyses. Significant two-way interactions were found. At 04:00 h, SN displayed increased time spent in the safe zone (p < .001; percentage of time spent within 10 km/h of the speed limit and 0.8 m of lane center), and decreases in speed variability (p < .001), lane variability (p < .001), post-drive PVT-B lapses (defined as RT > 355 ms; p < .001), and reaction time on the 2-choice reaction time task (p < .001) and running memory task (p < .001) compared to MN and NE. MN reported greater subjective sleepiness at 04:00 h (p < .001) compared to SN and NE. There was no difference in objective sleep between eating conditions. Eating a large meal during the nightshift impairs cognitive performance and sleepiness above the effects of time of night alone. For improved performance, shiftworkers should opt for a snack at night.

Subjective Hunger, Gastric Upset, and Sleepiness in Response to Altered Meal Timing during Simulated Shiftwork.

Shiftworkers report eating during the night when the body is primed to sleep. This study investigated the impact of altering food timing on subjective responses. Healthy participants (n = 44, 26 male, age Mean ± SD = 25.0 ± 2.9 years, BMI = 23.82 ± 2.59kg/m2) participated in a 7-day simulated shiftwork protocol. Participants were randomly allocated to one of three eating conditions. At 00:30, participants consumed a meal comprising 30% of 24 h energy intake (Meal condition; n = 14, 8 males), a snack comprising 10% of 24 h energy intake (Snack condition; n = 14; 8 males) or did not eat during the night (No Eating condition; n = 16, 10 males). Total 24 h individual energy intake and macronutrient content was constant across conditions. During the night, participants reported hunger, gut reaction, and sleepiness levels at 21:00, 23:30, 2:30, and 5:00. Mixed model analyses revealed that the snack condition reported significantly more hunger than the meal group (p < 0.001) with the no eating at night group reporting the greatest hunger (p < 0.001). There was no difference in desire to eat between meal and snack groups. Participants reported less sleepiness after the snack compared to after the meal (p < 0.001) or when not eating during the night (p < 0.001). Gastric upset did not differ between conditions. A snack during the nightshift could alleviate hunger during the nightshift without causing fullness or increased sleepiness.