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The timing of sleep is under the control of the circadian clock, which uses light to entrain to the external light‐dark cycle. A combination of genetic, physiological and environmental factors produces individual differences in chronotype (entrained phase as manifest in sleep timing). A mismatch between circadian and societal (e.g., work) clocks leads to a condition called social jetlag, which is characterized by changing sleep times over work and free days and accumulation of sleep debt. Social jetlag, which is prevalent in late chronotypes, has been related to several health issues. One way to reduce social jetlag would be to advance the circadian clock via modifications of the light environment. We thus performed two intervention field studies to describe methods for decreasing social jetlag. One study decreased evening light exposure (via blue‐light‐blocking glasses) and the other used increased morning light (via the use of curtains). We measured behaviour as well as melatonin; the latter in order to validate that behaviour was consistent with this neuroendocrinological phase marker of the circadian clock. We found that a decrease in evening blue light exposure led to an advance in melatonin and sleep onset on workdays. Increased morning light exposure advanced neither melatonin secretion nor sleep timing. Neither protocol led to a significant change in social jetlag. Despite this, our findings show that controlling light exposure at home can be effective in advancing melatonin secretion and sleep, thereby helping late chronotypes to better cope with early social schedules. [ABSTRACT FROM AUTHOR]

Night shiftwork can have a serious impact on health. Here, we assesswhether and hownight shift work influences the metabolite profiles, specifically with respect to different chronotype classes. We have recruited 100 women including 68 nurses working both, day shift and night shifts for up to 5 consecutive days and collected 3640 spontaneous urine samples. About 424waking-up urine samples were measured using a targeted metabolomics approach. To account for urine dilution, we applied three methods to normalize the metabolite values: creatinine-, osmolality- and regression-based normalization. Based on linear mixed effect models, we found 31 metabolites significantly (false discovery rate <0.05) affected in nurses working in night shifts. One metabolite, acylcarnitine C10:2, was consistently identified with all three normalization methods. We further observed 11 and 4 metabolites significantly associated with night shift in early and late chronotype classes, respectively. Increased levels of medium- and long chain acylcarnitines indicate a strong impairment of the fatty acid oxidation. Our results show that night shift work influences acylcarnitines and BCAAs, particularly in nurses in the early chronotype class. Women with intermediate and late chronotypes appear to be less affected by night shift work. [ABSTRACT FROM AUTHOR]

The timing of the circadian clock, circadian period and chronotype varies among individuals. To date, not much is known about how these parameters vary over time in an individual. We performed an analysis of the following five common circadian clock and chronotype measures: 1) the dim light melatonin onset (DLMO, a measure of circadian phase), 2) phase angle of entrainment (the phase the circadian clock assumes within the 24-h day, measured here as the interval between DLMO and bedtime/dark onset), 3) free-running circadian period (tau) from an ultradian forced desynchrony protocol (tau influences circadian phase and phase angle of entrainment), 4) mid-sleep on work-free days (MSF from the Munich ChronoType Questionnaire; MCTQ) and 5) the score from the Morningness–Eveningness Questionnaire (MEQ). The first three are objective physiological measures, and the last two are measures of chronotype obtained from questionnaires. These data were collected from 18 individuals (10 men, eight women, ages 21–44 years) who participated in two studies with identical protocols for the first 10 days. We show how much these circadian rhythm and chronotype measures changed from the first to the second study. The time between the two studies ranged from 9 months to almost 3 years, depending on the individual. Since the full experiment required living in the laboratory for 14 days, participants were unemployed, had part-time jobs or were freelance workers with flexible hours. Thus, they did not have many constraints on their sleep schedules before the studies. The DLMO was measured on the first night in the lab, after free-sleeping at home and also after sleeping in the lab on fixed 8-h sleep schedules (loosely tailored to their sleep times before entering the laboratory) for four nights. Graphs with lines of unity (when the value from the first study is identical to the value from the second study) showed how much each variable changed from the first to the second study. The DLMO did not change more than 2 h from the first to the second study, except for two participants whose sleep schedules changed the most between studies, a change in sleep times of 3 h. Phase angle did not change by more than 2 h regardless of changes in the sleep schedule. Circadian period did not change more than 0.2 h, except for one participant. MSF did not change more than 1 h, except for two participants. MEQ did not change more than 10 points and the categories (e.g. M-type) did not change. Pearson’s correlations for the DLMO between the first and second studies increased after participants slept in the lab on their individually timed fixed 8-h sleep schedules for four nights. A longer time between the two studies did not increase the difference between any of the variables from the first to the second study. This analysis shows that the circadian clock and chronotype measures were fairly reproducible, even after many months between the two studies. [ABSTRACT FROM PUBLISHER]