Abstract

Shift work has become an integral part of our life with almost 20% of the population being involved in different shift schedules in developed countries. However, the atypical work times, especially the night shifts, are associated with reduced quality and quantity of sleep that leads to increase of sleepiness often culminating in accidents. It has been demonstrated that shift workers’ sleepiness can be improved by a proper scheduling of light exposure and optimizing shifts timing. Here, an integrated physiologically-based model of sleep-wake cycles is used to predict adaptation to shift work in different light conditions and for different shift start times for a schedule of four consecutive days of work. The integrated model combines a model of the ascending arousal system in the brain that controls the sleep-wake switch and a human circadian pacemaker model. To validate the application of the integrated model and demonstrate its utility, its dynamics are adjusted to achieve a fit to published experimental results showing adaptation of night shift workers (n = 8) in conditions of either bright or regular lighting. Further, the model is used to predict the shift workers’ adaptation to the same shift schedule, but for conditions not considered in the experiment. The model demonstrates that the intensity of shift light can be reduced fourfold from that used in the experiment and still produce good adaptation to night work. The model predicts that sleepiness of the workers during night shifts on a protocol with either bright or regular lighting can be significantly improved by starting the shift earlier in the night, e.g.; at 21∶00 instead of 00∶00. Finally, the study predicts that people of the same chronotype, i.e. with identical sleep times in normal conditions, can have drastically different responses to shift work depending on their intrinsic circadian and homeostatic parameters.

Highlights

  • Shift work has become an essential part of our 24-h society

  • Along with benefits of around-the-clock service, it leads to increased sleepiness of shift workers, which leads to accidents and work-related injuries

  • In the following we first demonstrate the dynamics of the model on the experimental protocol [25] with the fitted parameter values, and use the model to investigate the dynamics in conditions that were not considered in the experiment

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Summary

Introduction

Along with benefits of around-the-clock service, it leads to increased sleepiness of shift workers, which leads to accidents and work-related injuries. This can have detrimental consequences for the shift workers themselves, and for people around them. In a person exposed to a natural light-dark cycle, the peak of the circadian activity appears during daytime and its minimum during the night. This rhythm is reflected in fluctuations of the core body temperature (CBT), which demonstrates minimum during the night, usually 2–3 hours before awakening, and maximum during daytime. The timing of the CBT minimum is traditionally used as a marker of the circadian phase, as it is a reasonably precise and noninvasive measure [13]

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