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Power Spectral Analysis of Electroencephalographic Activity during Sleep in Cigarette Smokers

¹Department of Epidemiology, Johns Hopkins University ²Department of Biostatistics, Johns Hopkins University ³Department of Medicine, Johns Hopkins University ⁴Applied Physics Lab, Johns Hopkins University

npunjabi{at}jhmi.edu

Abstract

Background: Research on the effects of cigarette smoking on sleep architecture is limited. The objective of this investigation was to examine differences in the sleep electroencephalogram (EEG) between smokers and nonsmokers.

Methods: Smokers and nonsmokers free of all medical co-morbidities were matched on factors including age, gender, race, body mass index, and other measures of body composition. Home polysomnography was conducted using a standard recording montage. Sleep architecture was assessed using visual sleep stage scoring. The discrete Fast Fourier Transform (FFT) was used to calculate the EEG power spectrum for the entire night within contiguous 30-second epochs of sleep for the following frequency bandwidths: (0.8-4.0Hz), (4.1-8.0Hz), (8.1-13.0Hz), and ß (13.1-20.0Hz).

Results: Conventional sleep stages were similar between the two groups. However, spectral analysis of the sleep EEG showed that, compared to nonsmokers, smokers had, on average, 15.1% lower EEG power in the -bandwidth (p<0.01) and 58.3% higher EEG power in -bandwidth (p<0.0002). Differences in the EEG power spectrum between smokers and nonsmokers were greatest in the early part of the sleep period and decreased towards the end. Subjective complaints of lack of restful sleep were also more prevalent in smokers than nonsmokers (22.5% vs. 5.0%, p<0.02) and were explained, in part, by the differences in EEG spectral power.

Conclusions: Cigarette smokers manifest disturbances in the sleep EEG that are not evident in conventional measures of sleep architecture. Nicotine in cigarette smoke and withdrawal from it during sleep may contribute to these changes and the subjective experience of non-restorative sleep.

Key Words: Cigarette smoking • sleep architecture • power spectral analysis