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Effects of sleep quality on diurnal variation of brain volume in older adults: A retrospective cross-sectional study

Authors :
Jun Sung Kim
Ji Won Han
Dae Jong Oh
Seung Wan Suh
Min Jeong Kwon
Jieun Park
Sungman Jo
Jae Hyoung Kim
Ki Woong Kim
Source :
NeuroImage, Vol 288, Iss , Pp 120533- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

Aim: Brain volume is influenced by several factors that can change throughout the day. In addition, most of these factors are influenced by sleep quality. This study investigated diurnal variation in brain volume and its relation to overnight sleep quality. Methods: We enrolled 1,003 healthy Koreans without any psychiatric disorders aged 60 years or older. We assessed sleep quality and average wake time using the Pittsburgh Sleep Quality Index, and divided sleep quality into good, moderate, and poor groups. We estimated the whole and regional brain volumes from three-dimensional T1-weighted brain MRI scans. We divided the interval between average wake-up time and MRI acquisition time (INT) into tertile groups: short (INT1), medium (INT2), and long (INT3). Results: Whole and regional brain volumes showed no significance with respect to INT. However, the `interaction between INT and sleep quality showed significance for whole brain, cerebral gray matter, and cerebrospinal fluid volumes (p < .05). The INT2 group showed significantly lower volumes of whole brain, whole gray matter, cerebral gray matter, cortical gray matter, subcortical gray matter, and cerebrospinal fluid than the INT1 and INT3 groups only in the individuals with good sleep quality. Conclusion: Human brain volume changes significantly within a day associated with overnight sleep in the individuals with good sleep quality.

Details

Language :
English
ISSN :
10959572
Volume :
288
Issue :
120533-
Database :
Directory of Open Access Journals
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
edsdoj.3a7bd39760cd4dc1be421fdb2761b42d
Document Type :
article
Full Text :
https://doi.org/10.1016/j.neuroimage.2024.120533