- Title
- Patterns of physical activity, sitting time, and sleep in Australian adults: a latent class analysis
- Creator
- Duncan, Mitch J.; Oftedal, Stina; Rebar, Amanda L.; Murawski, Beatrice; Short, Camille; Rayward, Anna T.; Vandelanotte, Corneel
- Relation
- Sleep Health Vol. 6, Issue 6, p. 828-834
- Publisher Link
- http://dx.doi.org/10.1016/j.sleh.2020.04.006
- Publisher
- Elsevier
- Resource Type
- journal article
- Date
- 2020
- Description
- Objective: To identify the patterns of activity, sitting and sleep that adults engage in, the demographic and biological correlates of activity-sleep patterns and the relationship between identified patterns and self-rated health. Design and Setting: Online panel of randomly selected Australian adults (n = 2034) completing a cross-sectional survey in October-November 2013. Participants: Panel members who provided complete data on all variables were included (n = 1532). Measurements: Participants self-reported their demographic characteristics, height, weight, self-rated health, duration of physical activity, frequency of resistance training, sitting time, sleep duration, sleep quality, and variability in bed and wake times. Activity-sleep patterns were determined using latent class analysis. Latent class regression was used to examine the relationships between identified patterns, demographic and biological characteristics, and self-rated health. Results: A 4-class model fit the data best, characterized by very active good sleepers, inactive good sleepers, inactive poor sleepers, moderately active good sleepers, representing 38.2%, 22.2%, 21.2%, and 18.4% of the sample, respectively. Relative to the very active good sleepers, the inactive poor sleepers, and inactive good sleepers were more likely to report being female, lower education, higher body mass index, and lower self-rated health, the moderately active good sleepers were more likely to be older, report lower education, higher body mass index and lower self-rated health. Associations between activity-sleep pattern and self-rated health were the largest in the inactive poor sleepers. Conclusions: The 4 activity-sleep patterns identified had distinct behavioral profiles, sociodemographic correlates, and relationships with self-rated health. Many adults could benefit from behavioral interventions targeting improvements in physical activity and sleep.
- Subject
- physical activity; sitting; sleep quality; sleep timing; patterns
- Identifier
- http://hdl.handle.net/1959.13/1428769
- Identifier
- uon:38652
- Identifier
- ISSN:2352-7218
- Rights
- © 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
- Language
- eng
- Full Text
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