Summary Humans show large inter-individual differences in organising their behaviour within the 24-h day-this is most obvious in their preferred timing of sleep and wakefulness. Sleep and wake times show a near-Gaussian distribution in a given population, with extreme early types waking up when extreme late types fall asleep. This distribution is predominantly based on differences in an individuals' circadian clock. The relationship between the circadian system and different ''chronotypes'' is formally and genetically well established in experimental studies in organisms ranging from unicells to mammals. To investigate the epidemiology of the human circadian clock, we developed a simple questionnaire (Munich ChronoType Questionnaire, MCTQ) to assess chronotype. So far, more than 55,000 people have completed the MCTQ, which has been validated with respect to the Horne-Østberg morningness-eveningness questionnaire (MEQ), objective measures of activity and rest (sleep-logs and actimetry), and physiological parameters. As a result of this large survey, we established an algorithm which optimises chronotype assessment by incorporating the information on timing of sleep and wakefulness for both work and free days. The timing and duration of sleep are generally independent. However, when the two are analysed separately for work and free days, sleep duration strongly depends on chronotype. In addition, chronotype is both age-and sex-dependent.

A quarter of the world's population is subjected to a 1 hr time change twice a year (daylight saving time, DST). This reflects a change in social clocks, not environmental ones (e.g., dawn). The impact of DST is poorly understood. Circadian clocks use daylight to synchronize (entrain) to the organism's environment. Entrainment is so exact that humans adjust to the east-west progression of dawn within a given time zone. In a large survey (n = 55,000), we show that the timing of sleep on free days follows the seasonal progression of dawn under standard time, but not under DST. In a second study, we analyzed the timing of sleep and activity for 8 weeks around each DST transition in 50 subjects who were chronotyped (analyzed for their individual phase of entrainment). Both parameters readily adjust to the release from DST in autumn but the timing of activity does not adjust to the DST imposition in spring, especially in late chronotypes. Our data indicate that the human circadian system does not adjust to DST and that its seasonal adaptation to the changing photoperiods is disrupted by the introduction of summer time. This disruption may extend to other aspects of seasonal biology in humans.

The dim light melatonin onset (DLMO) is the most reliable measure of central circadian timing in humans. However, it is not always possible to measure the DLMO because sample collection has to occur in the hours before usual sleep onset, it requires staff support and considerable participant effort, and it is relatively expensive. Questionnaires that ask people about the timing of their behavior, such as their sleep, may provide an easier and less expensive estimate of circadian timing. The objective of this analysis was to compare the MEQ score derived from the Morningness-Eveningness Questionnaire (MEQ) and the MSFsc derived from the Munich ChronoType Questionnaire (MCTQ) to the DLMO in the largest sample to date (N = 60). Our hypothesis was that MSFsc would correlate more highly with the DLMO than MEQ score. Our sample of 36 healthy controls and 24 patients with delayed sleep phase disorder ranged in age from 18 to 62 years. All participants slept at times of their own choosing for a week before the assessment of their DLMO. The DLMO correlated significantly with both the MEQ score (r = –0.70, p < 0.001) and MSFsc (r = 0.68, p < 0.001). A linear regression using MEQ, MSFsc, and age to predict the DLMO explained 60% of the DLMO variance. The strongest predictor of the DLMO was MSFsc (beta = 0.51, p = 0.001), followed by MEQ (beta = –0.41, p = 0.004), and age (beta = 0.26, p = 0.013). The beta values for MSFsc and MEQ score were not statistically different from each other. Nonetheless, around a 4-h range in the DLMO was observed at a given MEQ score and a given MSFsc, indicating that neither questionnaire should be exclusively used to time light or exogenous melatonin treatment, as this could result in the mistiming of these treatments relative to the DLMO, thereby potentially worsening circadian misalignment.

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Little is known about human entrainment under natural conditions, partly due to the complexity of human behavior, torn between biological and social time and influenced by zeitgebers (light-dark cycles) that are progressively "polluted" (and thereby weakened) by artificial light. In addition, data about seasonal variations in sleep parameters are scarce. We, therefore, investigated seasonal variation in cross-sectional assessments of sleep/wake times of 9765 subjects from four European populations (EGCUT = Estonian Genome Centre, University of Tartu in Estonia; KORA = Cooperative Health Research in the Region of Augsburg in Germany; KORCULA = The Korcula study in Croatia; and ORCADES = The Orkney Complex Disease Study in Scotland). We identified time-of-year dependencies for the distribution of chronotype (phase of entrainment assessed as the mid-sleep time point on free days adjusted for sleep deficit of workdays) in cohorts from Estonia (EGCUT) and Germany (KORA). Our results indicate that season (defined as daylight saving time - DST and standard zonetime periods - SZT) specifications of photoperiod influence the distribution of chronotype (adjusted for age and sex). Second, in the largest investigated sample, from Estonia (EGCUT; N = 5878), we could detect that seasonal variation in weekly average sleep duration was dependent on individual chronotype. Later chronotypes in this cohort showed significant variation in their average sleep duration across the year, especially during DST (1 h advance in social time from the end of March to end of October), while earlier chronotypes did not. Later chronotypes not only slept less during the DST period but the average chronotype of the population assessed during this period was earlier than during the SZT (local time for a respective time zone) period. More in detail, hierarchical multiple regression analyses showed that, beyond season of assessment (DST or SZT), social jetlag (SJl; the discrepancy between the mid sleep on free and work days - which varied with age and sex) contributed to a greater extent to the variation in sleep duration than chronotype (after taking into account factors that are known to influence sleep duration, i.e. age, sex and body mass index). Variation in chronotype was also dependent on age, sex, season of assessment and SJl (which is highly correlated with chronotype - SJl was larger among later chronotypes). In summary, subjective assessments of sleep/wake times are very reliable to assess internal time and sleep duration (e.g. reproducing sleep duration and timing tendencies related to age and sex across the investigated populations), but season of assessment should be regarded as a potential confounder. We identified in this study photoperiod (seasonal adaptation) and SJl as two main factors influencing seasonal variation in chronotype and sleep duration. In conclusion, season of assessment, sex and age have an effect on epidemiological variation in sleep duration, chronotype and SJl, and should be included in studies investigating assoc...

Shift-work seriously affects the health and well-being of millions of people worldwide, and the number of shift workers is constantly rising (currently approximately 20% of the workforce). While some effects are acute, others lead to chronic syndromes that persist after retirement. Though health problems in shift workers are well established, we still do not properly understand the causal mechanisms underlying shift-work's effects on health. One reason may be the heterogeneity in shift-work research design and methodology, rendering comparison between studies difficult or even impossible. Shift-work also involves a multitude of interacting factors, and we do not yet fully understand many of these interactions. Interindividual differences between workers are central predictors for health. Among these, individual differences in internal time (chronotype) should play a key role in a worker's ability to adjust to shift-work. While the importance of chronotype is receiving increased attention in chronobiology, it is still being largely ignored by shift-work studies, particularly by those performed in the field. Shift-work research would greatly benefit from increased attention to circadian components in real-life shift-work situations.Here, we summarize the current state of shift-work research in an attempt to address the reasons as to why we still do not clearly understand the links between shift-work and health. The aim of shift-work research should ultimately be to improve health and well-being (including social issues) in shift workers by means of improved work schedules. Society as a whole would benefit from such improvements -the individual worker, the health system, and industry.

Daylight stems solely from direct, scattered and reflected sunlight, and undergoes dynamic changes in irradiance and spectral power composition due to latitude, time of day, time of year and the nature of the physical environment (reflections, buildings and vegetation). Humans and their ancestors evolved under these natural day/night cycles over millions of years. Electric light, a relatively recent invention, interacts and competes with the natural light–dark cycle to impact human biology. What are the consequences of living in industrialised urban areas with much less daylight and more use of electric light, throughout the day (and at night), on general health and quality of life? In this workshop report, we have classified key gaps of knowledge in daylight research into three main groups: (I) uncertainty as to daylight quantity and quality needed for “optimal” physiological and psychological functioning, (II) lack of consensus on practical measurement and assessment methods and tools for monitoring real (day) light exposure across multiple time scales, and (III) insufficient integration and exchange of daylight knowledge bases from different disciplines. Crucial short and long-term objectives to fill these gaps are proposed.

Light is necessary for vision; it enables us to sense and perceive our surroundings and in many direct and indirect ways, via eye and skin, affects our physiological and psychological health. The use of light in built environments has comfort, behavioural, economic and environmental consequences. Daylight has many particular benefits including excellent visual performance, permitting good eyesight, effective entrainment of the circadian system as well as a number of acute non-image forming effects and the important role of vitamin D production. Some human responses to daylight seem to be well defined whilst others require more research to be adequately understood. This paper presents an overview of current knowledge on how the characteristics of daylight play a role in fulfilling these and other functions often better than electric lighting as conventionally delivered.