Some shiftwokers in the long-haul transportation industries (i.e. road, rail, sea, air) have the opportunity to sleep in on-board rest facilities during duty periods. These rest facilities are typically fitted with a seat with a maximum back angle to the vertical of 20°, 40°, or 90°. The aim of this study was to examine the impact of "back angle" on the quantity and quality of sleep obtained in a seat during a daytime nap. Six healthy adults (3 females aged 27.0 years and 3 males aged 22.7 years) each participated in three conditions. For each condition, participants had a 4-h sleep opportunity in a bed (02:00-06:00 h) followed by a 4-h sleep opportunity in a seat (13:00-17:00 h). The only difference between conditions was in the back angle of the seat to the vertical during the seat-based sleep periods: 20° (upright), 40° (reclined), and 90° (flat). Polysomnographic data were collected during all sleep episodes. For the seat-based sleep episodes, there was a significant effect of back angle on three of four measures of sleep quantity, i.e. total sleep time, slow-wave sleep, and rapid eye movement (REM) sleep, and three of four measures of sleep quality, i.e. latency to REM sleep, arousals, and stage shifts. In general, the quantity and quality of sleep obtained in the reclined and flat seats were better than those obtained in the upright seat. In particular, compared to the flat seat, the reclined seat resulted in similar amounts of total sleep and slow-wave sleep, but 37% less REM sleep; and the upright seat resulted in 29% less total sleep, 30% less slow-wave sleep, and 79% less REM sleep. There are two main mechanisms that may explain the results. First, it is difficult to maintain the head in a comfortable position for sleep when sitting upright, and this is likely exacerbated during REM sleep, when muscle tone is very low. Second, an upright posture increases sympathetic activity and decreases parasympathetic activity, resulting in a heightened level of physiological arousal.

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Shiftwork is a common activity across oil and gas operations. One of the biggest threats associated with shiftwork is fatigue-related impairment. While the relationship between fatigue and safety risk are widely acknowledged, the practical implications and management practices within the oil and gas industry are not well understood, practiced or monitored. This paper will explore the prevalence and nature of fatigue-related impairment in a small population of oil and gas workers. Data will be presented on actual work hours, sleep quality and quantity, and the relationship with performance impairment. Data was collected using questionnaires, work, sleep and symptom diaries, wrist activity monitors and psychomotor vigilance tasks using a hand held palm pilot.The results portray the difference in risk profile across a two week period of 12-hour night shifts, contrasted against a twoweek period of 12-hour day shifts. The results draw attention to high-risk periods across a shift work roster, and propose targeted management strategies using the hierarchy of control. The paper concludes with areas for further research and industry collaboration.

Continuous glucose monitoring devices measure glucose in interstitial fluid. The devices are effective when used by patients with type 1 and 2 diabetes but are increasingly being used by researchers who are interested in the effects of various behaviours of glucose concentrations in healthy participants. Despite their more frequent application in this setting, the devices have not yet been validated for use under such conditions. A total of 124 healthy participants were recruited to a ten-day laboratory study. Each participant underwent four oral glucose tolerance tests, and a total of 3315 out of a possible 4960 paired samples were included in the final analysis. Bland–Altman plots and mean absolute relative differences were used to determine the agreement between the two methods. Bland–Altman analyses revealed that the continuous glucose monitoring devices had proportional bias (R = 0.028, p < 0.001) and a mean bias of −0.048 mmol/L, and device measurements were more variable as glucose concentrations increased. Ninety-nine per cent of paired values were in Zones A and B of the Parkes Error Grid plot, and there was an overall mean absolute relative difference of 16.2% (±15.8%). There was variability in the continuous glucose monitoring devices, and this variability was higher when glucose concentrations were higher. If researchers were to use continuous glucose monitoring devices to measure glucose concentrations during an oral glucose tolerance test in healthy participants, this variability would need to be considered.