The 10-min psychomotor vigilance task (PVT) has often been used to assess the impact of sleep loss on performance. Due to time constraints, however, regular testing may not be practical in field studies. The aim of the present study was to examine the suitability of tests shorter than 10 min. in duration. Changes in performance across a night of sustained wakefulness were compared during a standard 10-min PVT, the first 5 min of the PVT, and the first 2 min of the PVT. Four performance metrics were assessed: (1) mean reaction time (RT), (2) fastest 10% of RT, (3) lapse percentage, and (4) slowest 10% of RT. Performance during the 10-min PVT significantly deteriorated with increasing wakefulness for all metrics. Performance during the first 5 min and the first 2 min of the PVT deteriorated in a manner similar to that observed for the whole 10-min task, with all metrics except lapse percentage displaying significant impairment across the night. However, the shorter the task sampling time, the less sensitive the test is to sleepiness. Nevertheless, the 5-min PVT may provide a viable alternative to the 10-min PVT for some performance metrics.

There is a wealth of evidence to say that sleep impacts maternal health during pregnancy, however, little has been published on fetal health and maternal sleep. This scoping review summarises current literature on maternal sleep including sleep disordered breathing, sleep quality, sleep duration and supine sleep position, as these relate to fetal outcomes specifically birth weight, growth, preterm birth and stillbirth. An overall interpretation of the studies evaluated shows that events occurring during maternal sleep such as obstructive sleep apnea, sleep disruption and sleep position may have a negative effect on the fetus resulting in altered growth, gestational length and even death. These effects are biologically and physically plausible. In conclusion, there is limited and often conflicting information on maternal sleep and fetal outcomes. However, existing evidence suggests that this is an important area for future research. This area is ripe for investigation if there is to be reduction in the physical, emotional, and financial burden of poor fetal outcomes related to maternal sleep.

BackgroundSleep restriction is associated with development of metabolic ill-health, and hormonal mechanisms may underlie these effects. The aim of this study was to determine the impact of short term sleep restriction on male health, particularly glucose metabolism, by examining adrenocorticotropic hormone (ACTH), cortisol, glucose, insulin, triglycerides, leptin, testosterone, and sex hormone binding globulin (SHBG).Methodology/Principal FindingsN = 14 healthy men (aged 27.4±3.8, BMI 23.5±2.9) underwent a laboratory-based sleep restriction protocol consisting of 2 baseline nights of 10 h time in bed (TIB) (B1, B2; 22:00–08:00), followed by 5 nights of 4 h TIB (SR1–SR5; 04:00–08:00) and a recovery night of 10 h TIB (R1; 22:00–08:00). Subjects were allowed to move freely inside the laboratory; no strenuous activity was permitted during the study. Food intake was controlled, with subjects consuming an average 2000 kcal/day. Blood was sampled through an indwelling catheter on B1 and SR5, at 09:00 (fasting) and then every 2 hours from 10:00–20:00. On SR5 relative to B1, glucose (F 1,168 = 25.3, p<0.001) and insulin (F 1,168 = 12.2, p<0.001) were increased, triglycerides (F 1,168 = 7.5, p = 0.007) fell and there was no significant change in fasting homeostatic model assessment (HOMA) determined insulin resistance (F 1,168 = 1.3, p = 0.18). Also, cortisol (F 1,168 = 10.2, p = 0.002) and leptin (F 1,168 = 10.7, p = 0.001) increased, sex hormone binding globulin (F 1,167 = 12.1, p<0.001) fell and there were no significant changes in ACTH (F 1,168 = 0.3, p = 0.59) or total testosterone (F 1,168 = 2.8, p = 0.089).Conclusions/SignificanceSleep restriction impaired glucose, but improved lipid metabolism. This was associated with an increase in afternoon cortisol, without significant changes in ACTH, suggesting enhanced adrenal reactivity. Increased cortisol and reduced sex hormone binding globulin (SHBG) are both consistent with development of insulin resistance, although hepatic insulin resistance calculated from fasting HOMA did not change significantly. Short term sleep curtailment leads to changes in glucose metabolism and adrenal reactivity, which when experienced repeatedly may increase the risk for type 2 diabetes.

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Shiftwork leads to altered eating patterns, with workers often eating foods at all times across the 24 h period. Strategies to reduce the burden of shiftwork on the workers should be prioritised and altering these eating patterns is an important area for change. This narrative review examines the current evidence on the individual and environmental factors influencing the eating behaviours of shiftworkers. A systematic search was conducted and yielded 62 articles. These were split into four themes that influence eating patterns; When shiftworkers eat, What type of foods shiftworkers eat, Where the food is sourced from, and Why shiftworkers choose to eat on shift. Irregular working hours was the biggest influence on when workers ate on shift, shift-type was the biggest influence on what workers ate, the majority of food was sourced from canteens and cafeterias, and socialising with colleagues was the biggest reason why workers chose to eat. While more research is needed to explore multiple industries and shift-types, and to investigate the ideal size, type and timing of food on shift, this review has highlighted that future research into shiftworker eating needs to adopt an integrative approach and consider the different individual and social contexts that influence eating patterns.

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The frequency and severity of adverse events in Australian healthcare is under increasing scrutiny. A recent state government report identified 31 events involving "death or serious [patient] harm" and 452 "very high risk" incidents. Australia-wide, a previous study identified 2,324 adverse medical events (AME) in a single year, with more than half considered preventable. Despite the recognized link between fatigue and error in other industries, to date, few studies of medical errors have assessed the fatigue of the healthcare professionals involved. Nurses work extended and unpredictable hours with a lack of regular breaks and are therefore likely to experience elevated fatigue. Currently, there is very little available information on Australian nurses' sleep or fatigue levels, nor is there any information about whether this affects their performance. This study therefore aims to examine work hours, sleep, fatigue and error occurrence in Australian nurses. Using logbooks, 23 full-time nurses in a metropolitan hospital completed daily recordings for one month (644 days, 377 shifts) of their scheduled and actual work hours, sleep length and quality, sleepiness, and fatigue levels. Frequency and type of nursing errors, near errors, and observed errors (made by others) were recorded. Nurses reported struggling to remain awake during 36% of shifts. Moderate to high levels of stress, physical exhaustion, and mental exhaustion were reported on 23%, 40%, and 36% of shifts, respectively. Extreme drowsiness while driving or cycling home was reported on 45 occasions (11.5%), with three reports of near accidents. Overall, 20 errors, 13 near errors, and 22 observed errors were reported. The perceived potential consequences for the majority of errors were minor; however, 11 errors were associated with moderate and four with potentially severe consequences. Nurses reported that they had trouble falling asleep on 26.8% of days, had frequent arousals on 34.0% of days, and that work-related concerns were either partially or fully responsible for their sleep disruption on 12.5% of occasions. Fourteen out of the 23 nurses reported using a sleep aid. The most commonly reported sleep aids were prescription medications (62.7%), followed by alcohol (26.9%). Total sleep duration was significantly shorter on workdays than days off (p < 0.01). In comparison to other workdays, sleep was significantly shorter on days when an error (p < 0.05) or a near error (p < 0.01) was recorded. In contrast, sleep was higher on workdays when someone else's error was recorded (p = 0.08). Logistic regression analysis indicated that sleep duration was a significant predictor of error occurrence (chi2 = 6.739, p = 0.009, e beta = 0.727). The findings of this pilot study suggest that Australian nurses experience sleepiness and related physical symptoms at work and during their trip home. Further, a measurable number of errors occur of various types and severity. Less sleep may lead to the increased likelihood of making an error, and importantly, the decreased...

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