Association between electroencephalogram-based sleep characteristics and physical health in the general adult population

Abstract We examined the associations between electroencephalogram (EEG)-based sleep characteristics and physical health parameters in general adults via a cross-sectional study recruiting 100 volunteers aged 30–59 years. Sleep characteristics were measured at home using a portable multichannel elec...

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Main Authors: Masao Iwagami, Jaehoon Seol, Tetsuro Hiei, Akihiro Tani, Shigeru Chiba, Takashi Kanbayashi, Hideaki Kondo, Takashi Tanaka, Masashi Yanagisawa
Format: Article
Language:English
Published: Nature Portfolio 2023-12-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-47979-9
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author Masao Iwagami
Jaehoon Seol
Tetsuro Hiei
Akihiro Tani
Shigeru Chiba
Takashi Kanbayashi
Hideaki Kondo
Takashi Tanaka
Masashi Yanagisawa
author_facet Masao Iwagami
Jaehoon Seol
Tetsuro Hiei
Akihiro Tani
Shigeru Chiba
Takashi Kanbayashi
Hideaki Kondo
Takashi Tanaka
Masashi Yanagisawa
author_sort Masao Iwagami
collection DOAJ
description Abstract We examined the associations between electroencephalogram (EEG)-based sleep characteristics and physical health parameters in general adults via a cross-sectional study recruiting 100 volunteers aged 30–59 years. Sleep characteristics were measured at home using a portable multichannel electroencephalography recorder. Using the k-means +  +  clustering method, according to 10 EEG-based parameters, participants were grouped into better (n = 39), middle (n = 46), and worse (n = 15) sleep groups. Comparing 50 physical health parameters among the groups, we identified four signals of difference (P < 0.05), including systolic (sBP) and diastolic blood pressure (dBP), γ-glutamyl transpeptidase (γ-GTP), and serum creatinine, where sBP reached a Bonferroni-corrected threshold (P < 0.001). The sBP was higher by 7.9 (95% confidence interval 1.9–13.9) and 15.7 (7.3–24.0) mmHg before adjustment and 5.4 (− 0.1–10.9) and 8.7 (1.1–16.3) mmHg after adjustment for age, sex, body mass index, smoking, drinking habits, and 3% oxygen desaturation index in the middle and worse sleep groups, respectively, than in the better group. As another approach, among 500 combinations of EEG-based and physical health parameters, there were 45 signals of correlation, of which 4 (N1% and sBP, dBP, γ-GTP, and triglycerides) reached a Bonferroni-corrected threshold (P < 0.0001). Thus, EEG-based sleep characteristics are associated with several physical health parameters, particularly sBP.
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spelling doaj.art-d10e69d834714b46844e3e86ea478c4f2023-12-10T12:19:57ZengNature PortfolioScientific Reports2045-23222023-12-0113111110.1038/s41598-023-47979-9Association between electroencephalogram-based sleep characteristics and physical health in the general adult populationMasao Iwagami0Jaehoon Seol1Tetsuro Hiei2Akihiro Tani3Shigeru Chiba4Takashi Kanbayashi5Hideaki Kondo6Takashi Tanaka7Masashi Yanagisawa8International Institute for Integrative Sleep Medicine (IIIS), University of TsukubaInternational Institute for Integrative Sleep Medicine (IIIS), University of TsukubaS’UIMIN Inc.S’UIMIN Inc.International Institute for Integrative Sleep Medicine (IIIS), University of TsukubaInternational Institute for Integrative Sleep Medicine (IIIS), University of TsukubaInternational Institute for Integrative Sleep Medicine (IIIS), University of TsukubaKRD NihombashiInternational Institute for Integrative Sleep Medicine (IIIS), University of TsukubaAbstract We examined the associations between electroencephalogram (EEG)-based sleep characteristics and physical health parameters in general adults via a cross-sectional study recruiting 100 volunteers aged 30–59 years. Sleep characteristics were measured at home using a portable multichannel electroencephalography recorder. Using the k-means +  +  clustering method, according to 10 EEG-based parameters, participants were grouped into better (n = 39), middle (n = 46), and worse (n = 15) sleep groups. Comparing 50 physical health parameters among the groups, we identified four signals of difference (P < 0.05), including systolic (sBP) and diastolic blood pressure (dBP), γ-glutamyl transpeptidase (γ-GTP), and serum creatinine, where sBP reached a Bonferroni-corrected threshold (P < 0.001). The sBP was higher by 7.9 (95% confidence interval 1.9–13.9) and 15.7 (7.3–24.0) mmHg before adjustment and 5.4 (− 0.1–10.9) and 8.7 (1.1–16.3) mmHg after adjustment for age, sex, body mass index, smoking, drinking habits, and 3% oxygen desaturation index in the middle and worse sleep groups, respectively, than in the better group. As another approach, among 500 combinations of EEG-based and physical health parameters, there were 45 signals of correlation, of which 4 (N1% and sBP, dBP, γ-GTP, and triglycerides) reached a Bonferroni-corrected threshold (P < 0.0001). Thus, EEG-based sleep characteristics are associated with several physical health parameters, particularly sBP.https://doi.org/10.1038/s41598-023-47979-9
spellingShingle Masao Iwagami
Jaehoon Seol
Tetsuro Hiei
Akihiro Tani
Shigeru Chiba
Takashi Kanbayashi
Hideaki Kondo
Takashi Tanaka
Masashi Yanagisawa
Association between electroencephalogram-based sleep characteristics and physical health in the general adult population
Scientific Reports
title Association between electroencephalogram-based sleep characteristics and physical health in the general adult population
title_full Association between electroencephalogram-based sleep characteristics and physical health in the general adult population
title_fullStr Association between electroencephalogram-based sleep characteristics and physical health in the general adult population
title_full_unstemmed Association between electroencephalogram-based sleep characteristics and physical health in the general adult population
title_short Association between electroencephalogram-based sleep characteristics and physical health in the general adult population
title_sort association between electroencephalogram based sleep characteristics and physical health in the general adult population
url https://doi.org/10.1038/s41598-023-47979-9
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