Longitudinal change of sleep timing: association between chronotype and longevity in older adults.


Journal

Chronobiology international
ISSN: 1525-6073
Titre abrégé: Chronobiol Int
Pays: England
ID NLM: 8501362

Informations de publication

Date de publication:
09 2019
Historique:
pubmed: 23 7 2019
medline: 30 9 2020
entrez: 23 7 2019
Statut: ppublish

Résumé

Evening-oriented sleep timing preferences have been associated with risk of diabetes, cardiovascular diseases, obesity, psychiatric disorders, and increased mortality. This research aims to explore the relationship between diurnal preferences (chronotype), daily habits, metabolic health, and mortality, using longitudinal data from The University of Manchester Longitudinal Study of Cognition in Normal Healthy Old Age (6375 participants at inception, recruited in the North of England) with a long follow-up period (up to 35.5 years). Mixed models were used to investigate the influence of aging, socio-demographic, and seasonal factors on sleep timing. Results show that sleep timing shifted towards earlier time with aging. Test seasons influence chronotype of older adults but working schedules challenge seasonality of sleep timing. Moreover, the season of birth may set chronotype in adulthood. Individual chronotype trajectories were clustered using latent class analysis and analyzed against metabolic health and mortality. We observed a higher risk of hypertension in the evening-type cluster compared to morning-type individuals (Odds ratio = 1.88, 95%CI = 1.02/3.47,

Identifiants

pubmed: 31328571
doi: 10.1080/07420528.2019.1641111
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1285-1300

Subventions

Organisme : Medical Research Council
Pays : United Kingdom
Organisme : Biotechnology and Biological Sciences Research Council
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom

Auteurs

Altug Didikoglu (A)

a Division of Neuroscience & Experimental Psychology, School of Biological Sciences, The University of Manchester , Manchester , UK.

Asri Maharani (A)

a Division of Neuroscience & Experimental Psychology, School of Biological Sciences, The University of Manchester , Manchester , UK.

Antony Payton (A)

b Division of Informatics, Imaging & Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester , Manchester , UK.

Neil Pendleton (N)

a Division of Neuroscience & Experimental Psychology, School of Biological Sciences, The University of Manchester , Manchester , UK.

Maria Mercè Canal (MM)

a Division of Neuroscience & Experimental Psychology, School of Biological Sciences, The University of Manchester , Manchester , UK.

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Classifications MeSH