This review summarises the literature on shift work and its relation to insufficient sleep, chronic diseases, and accidents. It is based on 38 meta-analyses and 24 systematic reviews, with additional narrative reviews and articles used for outlining possible mechanisms by which shift work may cause accidents and adverse health. Evidence shows that the effect of shift work on sleep mainly concerns acute sleep loss in connection with night shifts and early morning shifts. A link also exists between shift work and accidents, type 2 diabetes (relative risk range 1.09-1.40), weight gain, coronary heart disease (relative risk 1.23), stroke (relative risk 1.05), and cancer (relative risk range 1.01-1.32), although the original studies showed mixed results. The relations of shift work to cardiometabolic diseases and accidents mimic those with insufficient sleep. Laboratory studies indicate that cardiometabolic stress and cognitive impairments are increased by shift work, as well as by sleep loss. Given that the health and safety consequences of shift work and insufficient sleep are very similar, they are likely to share common mechanisms. However, additional research is needed to determine whether insufficient sleep is a causal pathway for the adverse health effects associated with shift work.

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SUMMAR Y The present study aimed to provide subject-specific estimates of the relation between subjective sleepiness measured with the Karolinska Sleepiness Scale (KSS) and blink duration (BLINKD) and lane drifting calculated as the standard deviation of the lateral position (SDLAT) in a high-fidelity moving base driving simulator. Five male and five female shift workers were recruited to participate in a 2-h drive (08:00-10:00 hours) after a normal night sleep and after working a night shift. Subjective sleepiness was rated on the KSS in 5-min intervals during the drive, electro-occulogram (EOG) was measured continuously to calculate BLINKD, and SDLAT was collected from the simulator. A mixed model anova showed a significant (P < 0.001) effect of the KSS for both dependent variables. A test for a quadratic trend suggests a curvilinear effect with a steeper increase at high KSS levels for both SDLAT (P < 0.001) and BLINKD (P ¼ 0.003). Large individual differences were observed for the intercept (P < 0.001), suggesting that subjects differed in their overall driving performance and blink duration independent of sleepiness levels. The results have implications for any application that needs prediction at the subject level (e.g. driver fatigue warning systems) as well as for research design and the interpretation of group average data.k e y w o r d s lane drifting, mixed models, standard deviation of lateral position

The results show that sleep deprivation affects features relating to the eyes, mouth, and skin, and that these features function as cues of sleep loss to other people. Because these facial regions are important in the communication between humans, facial cues of sleep deprivation and fatigue may carry social consequences for the sleep deprived individual in everyday life.

SUMMARYThe main consequence of insufficient sleep is sleepiness. While measures of sleep latency, continuous encephalographical/electro-oculographical (EEG/EOG) recording and performance tests are useful indicators of sleepiness in the laboratory and clinic, they are not easily implemented in large, real-life field studies. Subjective ratings of sleepiness, which are easily applied and unobtrusive, are an alternative, but whether they measure sleepiness sensitively, reliably and validly remains uncertain. This review brings together research relevant to these issues. It is focused on the Karolinska Sleepiness Scale (KSS), which is a nine-point Likert-type scale. The diurnal pattern of sleepiness is U-shaped, with high KSS values in the morning and late evening, and with great stability across years. KSS values increase sensitively during acute total and repeated partial sleep deprivation and night work, including night driving. The effect sizes range between 1.5 and 3. The relation to driving performance or EEG/EOG indicators of sleepiness is highly significant, strongly curvilinear and consistent across individuals. High (>6) KSS values are associated particularly with impaired driving performance and sleep intrusions in the EEG. KSS values are also increased in many clinical conditions such as sleep apnea, depression and burnout. The context has a strong influence on KSS ratings. Thus, physical activity, social interaction and light exposure will reduce KSS values by 1-2 units. In contrast, time-on-task in a monotonous context will increase KSS values by 1-2 units. In summary, subjective ratings of sleepiness as described here is as sensitive and valid an indicator of sleepiness as objective measures, and particularly suitable for field studies.