Relationships between sleep efficiency and lifestyle evaluated by objective sleep assessment: SLeep Epidemiology Project at University of Tsukuba

Objectively measured sleep efficiency has recently been shown to be associated with health problems. Although several factors have previously been reported to be associated with sleep efficiency, most of these studies were conducted on older or younger adults, and the factors associated with sleep e...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Nagoya journal of medical science 2022-08, Vol.84 (3), p.554-569
Hauptverfasser: Ikeda, Yu, Morita, Emi, Muroi, Kei, Arai, Yo, Ikeda, Tomohiko, Takahashi, Tsukasa, Shiraki, Nagisa, Doki, Shotaro, Hori, Daisuke, Oi, Yuichi, Sasahara, Shin‐ichiro, Ishihara, Asuka, Matsumoto, Sumire, Yanagisawa, Masashi, Satoh, Makoto, Matsuzaki, Ichiyo
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Objectively measured sleep efficiency has recently been shown to be associated with health problems. Although several factors have previously been reported to be associated with sleep efficiency, most of these studies were conducted on older or younger adults, and the factors associated with sleep efficiency in healthy workers remain unknown. The aim of this study was to investigate the relationship between sleep efficiency and lifestyle factors using sleep measurement data recorded by an activity meter worn by workers. In total, 693 workers (male, 43.6%; mean age, 42.7 ± 11.3 years) were recruited from five offices in 2017. Sleep was measured over the period of 1 week by actigraphy. Workers’ attributes, lifestyle habits, and occupational stress were identified using a questionnaire, and the association of sleep efficiency with lifestyle, occupational stress, and attributes was explored by logistic regression analysis. A logistic regression analysis using attributes and occupational stress as adjustment variables revealed that “longer sleeping hours on weekends than on weekdays” [odds ratios (OR), 0.66; 95% confidence interval (CI), 0.47–0.94], “water ingestion at bedtime” [OR, 2.09; 95% CI, 1.28–3.41], and “smartphone use at bedtime” [OR, 1.90; 95% CI, 1.28–2.83] were associated with decreased sleep efficiency. This study found that lifestyle habits were associated with sleep efficiency among workers. It is necessary to verify whether intervention in these lifestyle habits would contribute to the improvement of sleep efficiency in future studies.
ISSN:0027-7622
2186-3326
DOI:10.18999/nagjms.84.3.554