Sleep and cardiometabolic risk: a cluster analysis of actigraphy-derived sleep profiles in adults and children

Lisa Matricciani; Catherine Paquet; François Fraysse; Anneke Grobler; Yichao Wang; Louise Baur; Markus Juonala; Minh Thien Nguyen; Sarath Ranganathan; David Burgner; Melissa Wake; Tim Olds

doi:10.1093/sleep/zsab014

Sleep and cardiometabolic risk: a cluster analysis of actigraphy-derived sleep profiles in adults and children

Sleep. 2021 Jul 9;44(7):zsab014. doi: 10.1093/sleep/zsab014.

Authors

Lisa Matricciani¹, Catherine Paquet^{2

3}, François Fraysse¹, Anneke Grobler^{4

5}, Yichao Wang^{4

5}, Louise Baur⁶, Markus Juonala⁷, Minh Thien Nguyen^{4

5}, Sarath Ranganathan^{4

5

8}, David Burgner^{4

5

9

10}, Melissa Wake^{4

11

5}, Tim Olds¹

Affiliations

¹ Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia.
² Australian Centre for Precision Health, University of South Australia, Adelaide, SA, Australia.
³ Faculté des Sciences de l'Administration, Université Laval, Québec, QC, Canada.
⁴ Department of Paediatrics, The University of Melbourne, Parkville, VIC, Australia.
⁵ Murdoch Children's Research Institute, Parkville, VIC,Australia.
⁶ The University of Sydney, Sydney, NSW,Australia.
⁷ Department of Medicine, University of Turku, Turku, Finland and Division of Medicine, Turku University Hospital, Turku, Finland.
⁸ Respiratory Medicine, Royal Children's Hospital, Parkville, VIC, Australia.
⁹ Department of General Medicine, Royal Children's Hospital, Parkville, VIC, Australia.
¹⁰ Department of Paediatrics, Monash University, Clayton, VIC, Australia.
¹¹ The University of Auckland, Grafton, Auckland, New Zealand.

PMID: 33515457
DOI: 10.1093/sleep/zsab014

Abstract

Study objectives: Sleep plays an important role in cardiometabolic health. Although the importance of considering sleep as a multidimensional construct is widely appreciated, studies have largely focused on individual sleep characteristics. The association between actigraphy-derived sleep profiles and cardiometabolic health in healthy adults and children has not been examined.

Methods: This study used actigraphy-measured sleep data collected between February 2015 and March 2016 in the Child Health CheckPoint study. Participants wore actigraphy monitors (GENEActiv Original, Cambs, UK) on their nondominant wrist for 7 days and sleep characteristics (period, efficiency, timing, and variability) were derived from raw actigraphy data. Actigraphy-derived sleep profiles of 1,043 Australian children aged 11-12 years and 1,337 adults were determined using K-means cluster analysis. The association between cluster membership and biomarkers of cardiometabolic health (blood pressure, body mass index, apolipoproteins, glycoprotein acetyls, composite metabolic syndrome severity score) were assessed using Generalized Estimating Equations, adjusting for geographic clustering, with sex, socioeconomic status, maturity stage (age for adults, pubertal status for children), and season of data collection as covariates.

Results: Four actigraphy-derived sleep profiles were identified in both children and adults: short sleepers, late to bed, long sleepers, and overall good sleepers. The overall good sleeper pattern (characterized by adequate sleep period time, high efficiency, early bedtime, and low day-to-day variability) was associated with better cardiometabolic health in the majority of comparisons (80%).

Conclusion: Actigraphy-derived sleep profiles are associated with cardiometabolic health in adults and children. The overall good sleeper pattern is associated with more favorable cardiometabolic health.

Keywords: cardiometabolic health; children; profiles; sleep.

Publication types

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

MeSH terms

Actigraphy*
Adult
Australia
Cardiovascular Diseases*
Child
Cluster Analysis
Cross-Sectional Studies
Humans
Sleep