A cross-sectional cluster analysis of the combined association of physical activity and sleep with sociodemographic and health characteristics in mid-aged and older adults

Anna T. Rayward, Mitch J. Duncan*, Wendy J. Brown, Ronald C. Plotnikoff, Nicola W. Burton

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

20 Citations (Scopus)
4 Downloads (Pure)

Abstract

Objectives 

This study aimed to identify how different patterns of physical activity, sleep duration and sleep quality cluster together, and to examine how the identified clusters differ in terms of socio-demographic and health characteristics. 

Study design and outcome measures 

Participants were adults from Brisbane, Australia, aged 42–72 years who reported their physical activity, sleep duration, sleep quality, socio-demographic and health characteristics in 2011 (n = 5854). Two-step Cluster Analyses were used to identify clusters. Cluster differences in socio-demographic and health characteristics were examined using chi square tests (p < 0.05).

Results 

Four clusters were identified: ‘Poor Sleepers’ (31.2%), ‘Moderate Sleepers’ (30.7%), ‘Mixed Sleepers/Highly Active’ (20.5%), and ‘Excellent Sleepers/Mixed Activity’ (17.6%). The ‘Poor Sleepers’ cluster had the highest proportion of participants with less-than-recommended sleep duration and poor sleep quality, had the poorest health characteristics and a high proportion of participants with low physical activity. 

Conclusion 

Physical activity, sleep duration and sleep quality cluster together in distinct patterns and clusters of poor behaviours are associated with poor health status. Multiple health behaviour change interventions which target both physical activity and sleep should be prioritised to improve health outcomes in mid-aged adults.

Original languageEnglish
Pages (from-to)56-61
Number of pages6
JournalMaturitas
Volume102
DOIs
Publication statusPublished - Aug 2017
Externally publishedYes

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