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    Brief Report: A Latent Class Analysis of Guideline Compliance Across Nine Health Behaviors

    83627.pdf (345.9Kb)
    Access Status
    Open access
    Authors
    Pettigrew, Simone
    Dana, Liyuwork
    McAleese, A.
    Bastable, A.
    Drane, Cathy
    Sapountsis, Nina
    Date
    2021
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Pettigrew, S. and Dana, L.M. and McAleese, A. and Bastable, A. and Drane, C. and Sapountsis, N. 2021. Brief Report: A Latent Class Analysis of Guideline Compliance Across Nine Health Behaviors. International Journal of Behavioral Medicine.
    Source Title
    International Journal of Behavioral Medicine
    DOI
    10.1007/s12529-021-09988-8
    ISSN
    1070-5503
    Faculty
    Faculty of Health Sciences
    Faculty of Business and Law
    School
    EnAble Institute
    School of Management and Marketing
    Remarks

    This is a post-peer-review, pre-copyedit version of an article published in International Journal of Behavioral Medicine. The final authenticated version is available online at: https://doi.org/10.1007/s12529-021-09988-8.

    URI
    http://hdl.handle.net/20.500.11937/83665
    Collection
    • Curtin Research Publications
    Abstract

    Background: Prevalence figures for health-related behaviors disguise the existence of behavioral clusters. A growing body of work indicates the potential effectiveness of using simultaneous (versus sequential) approaches to targeting health-related behaviors to make deeper inroads into addressing non-communicable diseases. To inform future interventions designed to simultaneously address multiple risk factors, the aim of the present study was to identify behavioral clusters including nine behaviors relating to smoking, alcohol consumption, nutrition, physical activity, and sleep.

    Method: A latent class analysis was applied to a nationally representative sample of 1849 adult Australians.

    Results: Of the four identified segments, one was characterized by a relatively healthy behavioral profile and another demonstrated poor results across multiple lifestyle domains. The other two groups comprised individuals who demonstrated healthy behaviors in some domains (e.g., substance use) but not in others (primarily physical inactivity and junk food consumption, respectively).

    Conclusions: Results suggest the opportunity to encourage individuals in the latter two groups to build on existing positive behaviors to achieve greater overall compliance with health recommendations. Particularly intensive interventions are likely needed for those in the unhealthiest group to address the potentially reinforcing effects of their multiple unhealthy behaviors.

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