Literature DB >> 32771928

Sleep profiles of Australian children aged 11-12 years and their parents: sociodemographic characteristics and lifestyle correlates.

Lisa Matricciani1, Catherine Paquet2, François Fraysse3, Melissa Wake4, Tim Olds3.   

Abstract

BACKGROUND: Good sleep is a growing public health focus. Given the multidimensional nature of sleep, it is of interest to examine population sleep profiles and determine sociodemographic and lifestyle correlates.
METHODS: This study uses 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 non-dominant wrist for seven days and sleep characteristics (duration, efficiency, timing, and variability) were derived from raw actigraphy data. Sleep profiles of 1043 Australian children aged 11-12 years and their parents were determined using K-means cluster analysis. The association between cluster membership and potential sociodemographic and lifestyle correlates were assessed using Generalised Estimating Equations, adjusting for geographic clustering.
RESULTS: Four sleep profiles were identified: Short sleepers, Late to bed, Long sleepers, and Overall good sleepers. Compared to Overall good sleepers, Late to bed cluster were of lower socioeconomic position and had the least favourable diet and activity patterns. Compared to Overall good sleepers, those in the Late to bed cluster had higher sedentary time, lower levels of moderate-vigorous physical activity and a higher consumption of savoury snacks. In contrast, sugary drink consumption was higher in Late to bed children and Long sleeper adults.
CONCLUSION: Examining sleep profiles may provide a more holistic way of monitoring sleep at the population level. Future health promotion strategies may be best to consider sleep in terms of profiles, with emphasis on sleep timing and duration.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Children; Profiles; Sleep

Mesh:

Year:  2020        PMID: 32771928     DOI: 10.1016/j.sleep.2020.04.017

Source DB:  PubMed          Journal:  Sleep Med        ISSN: 1389-9457            Impact factor:   3.492


  1 in total

1.  Cardiovascular risks and sociodemographic correlates of multidimensional sleep phenotypes in two samples of US adults.

Authors:  Soomi Lee; Claire E Smith; Meredith L Wallace; Ross Andel; David M Almeida; Sanjay R Patel; Orfeu M Buxton
Journal:  Sleep Adv       Date:  2022-02-18
  1 in total

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