PLoS ONENeurosciencePeer-reviewed journal article
Home-EEG assessment of possible compensatory mechanisms for sleep disruption in highly irregular shift workers - The ANCHOR study
Lara J. MentinkiD, Jana ThomasiD, René J. F. MelisiD, Marcel G. M. Olde RikkertiD, Sebastiaan OvereemiD, Jurgen A.H.R. ClaasseniD
Abstract
Study objectivesWhile poor sleep quality has been related to increased risk of Alzheimers disease, long-time shift workers (maritime pilots) did not manifest evidence of early Alzheimers disease in a recent study. We explored two hypotheses of possible compensatory mechanisms for sleep disruption: Increased efficiency in generating deep sleep during workweeks (model 1) and rebound sleep during rest weeks (model 2). MethodsWe used data from ten male maritime pilots (mean age: 51.6{+/-}2.4 years) with a history of approximately 18 years of irregular shift work. Subjective sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI). A single lead EEG-device was used to investigate sleep in the home/work environment, quantifying total sleep time (TST), deep sleep time (DST), and deep sleep time percentage (DST%). Using multilevel models, we studied the sleep architecture of maritime pilots over time, at the transition of a workweek to a rest week. ResultsMaritime pilots reported worse sleep quality in workweeks compared to rest weeks (PSQI=8.2{+/-}2.2 vs. 3.9{+/-}2.0; p<0.001). Model 1 showed a trend towards an increase in DST% of 0.6% per day during the workweek (p=0.08). Model 2 did not display an increase in DST% in the rest week (p=0.87). ConclusionsOur findings indicated that increased efficiency in generating deep sleep during workweeks is a more likely compensatory mechanism for sleep disruption in the maritime pilot cohort than rebound sleep during rest weeks. Compensatory mechanisms for poor sleep quality might mitigate sleep disruption-related risk of developing Alzheimers disease. These results should be used as a starting point for future studies including larger, more diverse populations of shift workers.
- organism: human
- assay: electronic health records
- research focus: benchmarking
- approach: statistical model
- Citations
- 11
- FWCI
- 0.97
- Field percentile
- top 20%
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