Several studies have investigated the relationship between daylight saving time (DST) and sleep alterations, psychiatric disorders, cardiovascular events and traffic accidents. However, very few have monitored participants while maintaining their usual lifestyle before and after DST. Considering that DST transitions modify human behavior and, therefore, people's light exposure patterns, the aim of this study was to investigate the potential effects of DST on circadian variables, considering sleep and, for the first time, the human phase response curve to light. To accomplish this, eight healthy adults (33 ± 11 years old, mean ± SD) were recruited to monitor multivariable circadian markers and light exposure by means of a wearable ambulatory monitoring device: Kronowise®. The following night phase markers were calculated: midpoints of the five consecutive hours of maximum wrist temperature (TM5) and the five consecutive hours of minimum time in movement (TL5), sleep onset and offset, as well as sleep duration and light intensity. TM5 for wrist temperature was set as circadian time 0 h, and the balance between advances and delays considering the phase response curve to light was calculated individually before and after both DST transitions. To assess internal desynchronization, the possible shift in TM5 for wrist temperature and TL5 for time in movement were compared. Our results indicate that the transition to DST seems to force the circadian system to produce a phase advance to adapt to the new time. However, the synchronizing signals provided by natural and personal light exposure are not in line with such an advance, which results in internal desynchronization and the need for longer synchronization times. On the contrary, the transition back to ST, which implies a phase delay, is characterized by a faster adaptation and maintenance of internal synchronization, despite the fact that exposure to natural light would favor a phase advance. Considering the pilot nature of this study, further research is needed with higher sample sizes.
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