Chest
Volume 133, Issue 2, February 2008, Pages 427-432
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Original Research
Sleep Medicine
Power Spectral Analysis of EEG Activity During Sleep in Cigarette Smokers

https://doi.org/10.1378/chest.07-1190Get rights and content

Background

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

Methods

Smokers and nonsmokers who were free of all medical comorbidities were matched on different factors, including age, gender, race, body mass index, and anthropometric measures. Home polysomnography was conducted using a standard recording montage. Sleep architecture was assessed using visual sleep-stage scoring. The discrete fast Fourier transform was used to calculate the EEG power spectrum for the entire night within contiguous 30-s epochs of sleep for the following frequency bandwidths: δ (0.8 to 4.0 Hz); θ (4.1 to 8.0 Hz); α (8.1 to 13.0 Hz); and β (13.1 to 20.0 Hz).

Results

Conventional sleep stages were similar between the two groups. However, spectral analysis of the sleep EEG showed that, compared to nonsmokers, smokers had a lower percentage of EEG power in the δ-bandwidth (59.7% vs 62.6%, respectively; p < 0.04) and higher percentage of EEG power in α-bandwidth (15.6% vs 12.5%, respectively; p < 0.001). Differences in the EEG power spectrum between smokers and nonsmokers were greatest in the early part of the sleep period and decreased toward the end. Subjective complaints of lack of restful sleep were also more prevalent in smokers than in nonsmokers (22.5% vs 5.0%, respectively; 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 nonrestorative sleep.

Section snippets

Study Sample

The current investigation used data from the Sleep Heart Health Study (SHHS), which is a multicenter study on sleep-disordered breathing and cardiovascular disease. Details regarding the design of the SHHS study have been published previously.5 Briefly, the baseline cohort for the SHHS study was recruited from ongoing epidemiologic studies of cardiovascular and respiratory disease. The SHHS cohort was used to identify a group of matched smokers and nonsmokers using a computerized algorithm.

Results

Forty smokers and nonsmokers met the strict exclusion criteria, and were individually matched on age, gender, race, BMI, neck circumference, and AHI (Table 1). Smokers reported smoking an average of 25.3 cigarettes per day (range, 20 to 50 cigarettes per day). Lack of restful sleep was reported by 5.0% of the nonsmokers and 22.5% of the smokers (p < 0.02). Measures of mental health status were similar between smokers and nonsmokers as was the amount of self-reported alcohol consumption.

Discussion

The last few decades have seen substantial advancements in our knowledge of the harmful health effects of cigarette smoking. The present study shows that cigarette smoking can alter sleep architecture independent of factors such as age, gender, race, anthropometric measures, caffeine and alcohol consumption, medical comorbidity, and mental health status. Despite similar sleep stage architecture, the EEG power spectrum in smokers was shifted toward higher frequencies compared to nonsmokers.

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    The opinions expressed in this paper are those of the authors and do not necessarily reflect the views of the Indian Health Service.

    Supported by the National Heart, Lung, and Blood Institute through the following cooperative agreements: HL53940 (University of Washington); HL53941 (Boston University); HL63463 (Case Western Reserve University); HL53937 (Johns Hopkins University); HL53938 (University of Arizona); HL53916 (University of California, Davis); HL53934 (University of Minnesota); HL63429 (Missouri Breaks Research); and HL53931 (New York University). Dr. Punjabi was also supported by grants HL075078, HL086862, and AG025553.

    The authors have reported to the ACCP that no significant conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

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