Shortened sleep and circadian misalignment, as seen in shift workers, has adverse metabolic and behavioral consequences which lead to obesity and associated comorbidities. This study demonstrates a simulated night shift enhances preference for high fat foods, which may be a contributing factor for shift work-related weight gain. Increasing awareness of changes in food preference may promote healthier food choices. Key terms: diet; dietary intake; eating; fat; food; habit; health; health; high-fat food; night duty; night shift; night work; nutrition; obesity; shift work; shift worker; simulated night shift; sleep loss; weight gain This article in PubMed: www.ncbi.nlm.nih.gov/pubmed/25699635 288 Scand J Work Environ Health 2015, vol 41, no 3Short communication Scand J Work Environ Health. 2015;41(3):288-293. doi:10.5271/sjweh.3486 Enhanced preference for high-fat foods following a simulated night shift by Sean W Cain, PhD,1 Ashleigh J Filtness, PhD,2 Craig L Phillips, PhD,3,4 Clare Anderson, PhD 1,5 Cain SW, Filtness AJ, Phillips CL, Anderson C. Enhanced preference for high-fat foods following a simulated night shift. Scand J Work Environ Health. 2015;41(3):288-293. doi:10.5271/sjweh.3486 Objectives Shift workers are prone to obesity and associated co-morbidities such as diabetes and cardiovascular disease. Sleep restriction associated with shift work results in dramatic endocrine and metabolic effects that predispose shift workers to these adverse health consequences. While sleep restriction has been associated with increased caloric intake, food preference may also play a key role in weight gain associated with shift work. This study examined the impact of an overnight simulated night shift on food preference.Methods Sixteen participants [mean 20.1, standard deviation (SD) 1.4 years; 8 women] underwent a simulated night shift and control condition in a counterbalanced order. On the following morning, participants were provided an opportunity for breakfast that included high-and low-fat food options (mean 64.8% and 6.4% fat, respectively). ResultsParticipants ate significantly more high-fat breakfast items after the simulated night shift than after the control condition [167.3, standard error of the mean (SEM) 28.7) g versus 211.4 (SEM 35.6) g; P=0.012]. The preference for high-fat food was apparent among the majority of individuals following the simulated night shift (81%), but not for the control condition (43%). Shift work and control conditions did not differ, however, in the total amount of food or calories consumed.Conclusions A simulated night shift leads to preference for high-fat food during a subsequent breakfast opportunity. These results suggest that food choice may contribute to weight-related chronic health problems commonly seen among night shift workers.Key terms diet; dietary intake; eating; food; habit; health; night duty; night work; nutrition; obesity; shift work; shift worker; sleep loss; weight gain. Working shifts outside of regular working hours is prevalent in modern industrialize...

Additional Information:• NOTICE: this is the author's version of a work that was accepted for publication in Biological Psychology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published at: EEG power, and a near significant increase of subjective sleepiness. Correlations between the EEG and subjective measures were highly significant for both groups, indicating good self-insight into increasing sleepiness. This study confirms the greater vulnerability of younger drivers to sleep loss under prolonged driving, even during the early afternoon.

words)Operators of highly automated driving systems may exhibit behaviour characteristic for overtrust issues due to an insufficient awareness of automation fallibility. Consequently, situation awareness in critical situations is reduced and safe driving performance following emergency takeovers is impeded. A driving simulator study was used to assess the impact of dynamically communicating system uncertainties on monitoring, trust, workload, takeovers, and physiological responses. The uncertainty information was conveyed visually using a stylised heart beat combined with a numerical display and users were engaged in a visual search task.Multilevel analysis results suggest that uncertainty communication helps operators calibrate their trust and gain situation awareness prior to critical situations, resulting in safer takeovers.Additionally, eye tracking data indicate that operators can adjust their gaze behaviour in correspondence with the level of uncertainty. However, conveying uncertainties using a visual display significantly increases operator workload and impedes users in the execution of nondriving related tasks. Keywords: vehicle ergonomics; attitudes and behaviour; attention and vigilance; humancomputer-interaction; information displaysPractitioner summary (50 words): This paper illustrates how the communication of system uncertainty information helps operators calibrate their trust in automation and, consequently, gain situation awareness. Multilevel analysis results of a driving simulator study affirm the benefits for trust calibration and highlight that operators adjust their behaviour according to multiple uncertainty levels.

The objective of this paper is the review and comparative assessment of infrastructure related crash risk factors, with the explicit purpose of ranking them based on how detrimental they are towards road safety (i.e. crash risk, frequency and severity). This analysis was carried out within the SafetyCube project, which aimed to identify and quantify the effects of risk factors and measures related to behaviour, infrastructure or vehicles, and integrate the results in an innovative road safety Decision Support System (DSS). The evaluation was conducted by examining studies from the existing literature. These were selected and analysed using a specifically designed common methodology. Infrastructure risk factors were structured in a hierarchical taxonomy of 10 areas with several risk factors in each area (59 specific risk factors in total), examples include: alignment features (e.g. horizontal-vertical alignment deficiencies), cross-section characteristics (e.g. superelevation, lanes, median and shoulder deficiencies), road surface deficiencies, workzones, junction deficiencies (interchange and at-grade) etc. Consultation with infrastructure stakeholders (international organisations, road authorities, etc.) took place in dedicated workshops to identify user needs for the DSS, as well as "hot topics" of particular importance. The following analysis methodology was applied to each infrastructure risk factor: (i) A search for relevant international literature, (ii) Selection of studies on the basis of rigorous criteria, (iii) Analysis of studies in terms of design, methods and limitations, (iv) Synthesis of findings-and meta-analysis, when feasible. In total 243 recent and high quality studies were selected and analysed. Synthesis of results was made through 39 'Synopses' (including 4 original meta-analyses) on individual risk factors or groups of risk factors. This allowed the ranking of infrastructure risk factors into three groups: risky (11 risk factors), probably risky (18 risk factors), and unclear (7 risk factors).

Driver fatigue has received increased attention during recent years and is now considered to be a major contributor to approximately 15–30% of all crashes. However, little is known about fatigue in city bus drivers. It is hypothesized that city bus drivers suffer from sleepiness, which is due to a combination of working conditions, lack of health and reduced sleep quantity and quality. The overall aim with the current study is to investigate if severe driver sleepiness, as indicated by subjective reports of having to fight sleep while driving, is a problem for city based bus drivers in Sweden and if so, to identify the determinants related to working conditions, health and sleep which contribute towards this. The results indicate that driver sleepiness is a problem for city bus drivers, with 19% having to fight to stay awake while driving the bus 2–3 times each week or more and nearly half experiencing this at least 2–4 times per month. In conclusion, severe sleepiness, as indicated by having to fight sleep during driving, was common among the city bus drivers. Severe sleepiness correlated with fatigue related safety risks, such as near crashes.