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. 2017 Aug:102:56-61.
doi: 10.1016/j.maturitas.2017.05.013. Epub 2017 May 20.

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

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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 et al. Maturitas. 2017 Aug.

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.

Keywords: Exercise; Mental health; Physical activity; Sleep duration; Sleep quality.

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