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Author (up) Porcheret, K.; Wald, L.; Fritschi, L.; Gerkema, M.; Gordijn, M.; Merrrow, M.; Rajaratnam, S.M.W.; Rock, D.; Sletten, T.L.; Warman, G.; Wulff, K.; Roenneberg, T.; Foster, R.G.
Title Chronotype and environmental light exposure in a student population Type Journal Article
Year 2018 Publication Chronobiology International Abbreviated Journal Chronobiol Int
Volume 35 Issue 10 Pages 1365-1374
Keywords Human Health
Abstract In humans and most other species, changes in the intensity and duration of light provide a critical set of signals for the synchronisation of the circadian system to the astronomical day. The timing of activity within the 24 h day defines an individual's chronotype, i.e. morning, intermediate or evening type. The aim of this study was to investigate the associations between environmental light exposure, due to geographical location, on the chronotype of university students. Over 6 000 university students from cities in the Northern Hemisphere (Oxford, Munich and Groningen) and Southern Hemisphere (Perth, Melbourne and Auckland) completed the Munich ChronoType Questionnaire. In parallel, light measures (daily irradiance, timing of sunrise and sunset) were compiled from satellite or ground stations at each of these locations. Our data shows that later mid-sleep point on free days (corrected for oversleep on weekends MFSsc) is associated with (i) residing further from the equator, (ii) a later sunset, (iii) spending more time outside and (iv) waking from sleep significantly after sunrise. However, surprisingly, MSFsc did not correlate with daily light intensity at the different geographical locations. Although these findings appear to contradict earlier studies suggesting that in the wider population increased light exposure is associated with an earlier chronotype, our findings are derived exclusively from a student population aged between 17 and 26 years. We therefore suggest that the age and occupation of our population increase the likelihood that these individuals will experience relatively little light exposure in the morning whilst encountering more light exposure later in the day, when light has a delaying effect upon the circadian system.
Address a Sleep and Circadian Neuroscience Institute (SCNi), Nuffield Department of Clinical Neurosciences , University of Oxford , Oxford , UK
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0742-0528 ISBN Medium
Area Expedition Conference
Notes PMID:29913073 Approved no
Call Number GFZ @ kyba @ Serial 1962
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Author (up) Sletten, T.L.; Cappuccio, F.P.; Davidson, A.J.; Van Cauter, E.; Rajaratnam, S.M.W.; Scheer, F.A.J.L.
Title Health consequences of circadian disruption Type Journal Article
Year 2020 Publication Sleep Abbreviated Journal Sleep
Volume 43 Issue 1 Pages
Keywords Human Health; Circadian Rhythm; Chronobiology; Sleep; Review
Abstract The circadian system is key for optimal functioning by maintaining synchrony between internal circadian rhythms, behaviors, and external cues. Many clinicians are not fully aware, however, of the far-reaching implications of the circadian system for human health. Clinical attention to circadian rhythms has largely focused on sleep disturbances. The impact of the circadian system on health is, however, much broader. Clinical diagnoses are often based on single time point assessments during the day, ignoring circadian influences on physiology. Even when time is considered, using (external) clock time ignores the large interindividual differences in internal timing.
Address Division of Sleep Medicine, Harvard Medical School, Boston, MA
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0161-8105 ISBN Medium
Area Expedition Conference
Notes PMID:31930347 Approved no
Call Number IDA @ john @ Serial 2822
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Author (up) Stone, J.E.; Phillips, A.J.K.; Ftouni, S.; Magee, M.; Howard, M.; Lockley, S.W.; Sletten, T.L.; Anderson, C.; Rajaratnam, S.M.W.; Postnova, S.
Title Generalizability of A Neural Network Model for Circadian Phase Prediction in Real-World Conditions Type Journal Article
Year 2019 Publication Scientific Reports Abbreviated Journal Sci Rep
Volume 9 Issue 1 Pages 11001
Keywords Human Health; Instrumentation
Abstract A neural network model was previously developed to predict melatonin rhythms accurately from blue light and skin temperature recordings in individuals on a fixed sleep schedule. This study aimed to test the generalizability of the model to other sleep schedules, including rotating shift work. Ambulatory wrist blue light irradiance and skin temperature data were collected in 16 healthy individuals on fixed and habitual sleep schedules, and 28 rotating shift workers. Artificial neural network models were trained to predict the circadian rhythm of (i) salivary melatonin on a fixed sleep schedule; (ii) urinary aMT6s on both fixed and habitual sleep schedules, including shift workers on a diurnal schedule; and (iii) urinary aMT6s in rotating shift workers on a night shift schedule. To determine predicted circadian phase, center of gravity of the fitted bimodal skewed baseline cosine curve was used for melatonin, and acrophase of the cosine curve for aMT6s. On a fixed sleep schedule, the model predicted melatonin phase to within +/- 1 hour in 67% and +/- 1.5 hours in 100% of participants, with mean absolute error of 41 +/- 32 minutes. On diurnal schedules, including shift workers, the model predicted aMT6s acrophase to within +/- 1 hour in 66% and +/- 2 hours in 87% of participants, with mean absolute error of 63 +/- 67 minutes. On night shift schedules, the model predicted aMT6s acrophase to within +/- 1 hour in 42% and +/- 2 hours in 53% of participants, with mean absolute error of 143 +/- 155 minutes. Prediction accuracy was similar when using either 1 (wrist) or 11 skin temperature sensor inputs. These findings demonstrate that the model can predict circadian timing to within +/- 2 hours for the vast majority of individuals on diurnal schedules, using blue light and a single temperature sensor. However, this approach did not generalize to night shift conditions.
Address School of Physics, University of Sydney, Sydney, New South Wales, Australia
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2045-2322 ISBN Medium
Area Expedition Conference
Notes PMID:31358781; PMCID:PMC6662750 Approved no
Call Number GFZ @ kyba @ Serial 2667
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