Advertisement

Patterns of physical activity, sitting time, and sleep in Australian adults: A latent class analysis

  • Mitch J. Duncan
    Correspondence
    Corresponding author. School of Medicine & Public Health, Faculty of Health and Medicine, The University of Newcastle, University Drive, Callaghan NSW 2308, Australia.
    Affiliations
    School of Medicine & Public Health, Faculty of Health and Medicine, The University of Newcastle, University Drive, Callaghan, Australia

    Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, University Drive, Callaghan, Australia
    Search for articles by this author
  • Stina Oftedal
    Affiliations
    School of Medicine & Public Health, Faculty of Health and Medicine, The University of Newcastle, University Drive, Callaghan, Australia

    Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, University Drive, Callaghan, Australia
    Search for articles by this author
  • Amanda L. Rebar
    Affiliations
    Central Queensland University, Appleton Institute, Physical Activity Research Group, Rockhampton, Queensland, Australia
    Search for articles by this author
  • Beatrice Murawski
    Affiliations
    School of Medicine & Public Health, Faculty of Health and Medicine, The University of Newcastle, University Drive, Callaghan, Australia

    Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, University Drive, Callaghan, Australia
    Search for articles by this author
  • Camille E. Short
    Affiliations
    University of Melbourne, Faculty of Medicine, Dentistry, and Health Sciences, Parkville, Victoria, Australia
    Search for articles by this author
  • Anna T. Rayward
    Affiliations
    School of Medicine & Public Health, Faculty of Health and Medicine, The University of Newcastle, University Drive, Callaghan, Australia

    Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, University Drive, Callaghan, Australia
    Search for articles by this author
  • Corneel Vandelanotte
    Affiliations
    Central Queensland University, Appleton Institute, Physical Activity Research Group, Rockhampton, Queensland, Australia
    Search for articles by this author
Published:August 18, 2020DOI:https://doi.org/10.1016/j.sleh.2020.04.006

      Abstract

      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.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Sleep Health: Journal of the National Sleep Foundation
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • St-Onge M.-.P.
        • Grandner M.A.
        • Brown D.
        • Conroy M.B.
        • Jean-Louis G.
        • Coons M.
        • et al.
        Sleep duration and quality: impact on lifestyle behaviors and cardiometabolic health.
        Circulation. 2016; : e367-e386
        • Rhodes R.E.
        • Janssen I.
        • Bredin S.S.D.
        • Warburton D.E.R.
        • Bauman A
        Physical activity: health impact, prevalence, correlates and interventions.
        Psychol Health. 2017; 32: 942-975
        • Ekelund U.
        • Steene-Johannessen J.
        • Brown W.J.
        • et al.
        Does physical activity attenuate, or even eliminate the detrimental association of sitting time with mortality? A harmonised meta-analysis of data from more than one million men and women.
        Lancet. 2016; 388: 1302-1310
        • Stamatakis E.
        • Lee I.M.
        • Bennie J.
        • et al.
        Does strength-promoting exercise confer unique health benefits? A pooled analysis of data on 11 population cohorts with all-cause, cancer, and cardiovascular mortality endpoints.
        Am J Epidemiol. 2018; 187: 1102-1112
        • Oftedal S.
        • Smith J.
        • Vandelanotte C.
        • Burton N.W.
        • Duncan M.J
        Resistance training in addition to aerobic activity is associated with lower likelihood of depression and comorbid depression and anxiety symptoms: a cross sectional analysis of Australian women.
        Prev Med. 2019; 126105773
        • Buysse D.J
        Sleep health: can we define It? does it matter?.
        Sleep. 2014; 37: 9-17
        • Yu J.
        • Mahendran R.
        • Abdullah F.N.M.
        • Kua E.-.H.
        • Feng L
        Self-reported sleep problems among the elderly: a latent class analysis.
        Psychiatry Res. 2017; 258: 415-420
        • Magee C.A.
        • Reddy P.
        • Robinson L.
        • McGregor A
        Sleep quality subtypes and obesity.
        Health Psychology. 2016; 35: 1289-1297
        • Leigh L.
        • Hudson I.L.
        • Byles J.E
        Sleeping difficulty, disease and mortality in older women: a latent class analysis and distal survival analysis.
        J Sleep Res. 2015; 24: 648-657
        • Rod N.H.
        • Kumari M.
        • Lange T.
        • Kivimäki M.
        • Shipley M.
        • Ferrie J
        The joint effect of sleep duration and disturbed sleep on cause-specific mortality: results from the Whitehall II Cohort Study.
        PLoS ONE. 2014; 9: e91965
        • Hoevenaar-Blom M.P.
        • Spijkerman A.M.
        • Kromhout D.
        • van den Berg J.F.
        • Verschuren W.M
        Sleep duration and sleep quality in relation to 12-year cardiovascular disease incidence: the MORGEN study.
        Sleep. 2011; 34: 1487-1492
        • Chien K.L.
        • Chen P.C.
        • Hsu H.C.
        • et al.
        Habitual sleep duration and insomnia and the risk of cardiovascular events and all-cause death: report from a community-based cohort.
        Sleep. 2010; 33: 177-184
        • Rayward A.T.
        • Duncan M.J.
        • Brown W.J.
        • Plotnikoff R.C.
        • Burton N.W
        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.
        Maturitas. 2017; 102: 56-61
        • Xiao Q.
        • Keadle S.K.
        • Hollenbeck A.R.
        • Matthews C.E
        Sleep duration and total and cause-specific mortality in a large US cohort: interrelationships with physical activity, sedentary behavior, and body mass index.
        Am J Epidemiol. 2014; 180: 997-1006
        • Matricciani L.
        • Bin Y.S.
        • Lallukka T.
        • et al.
        Rethinking the sleep-health link.
        Sleep Health. 2018; 4: 339-348
        • Rayward A.T.
        • Burton N.W.
        • Brown W.J.
        • Holliday E.G.
        • Plotnikoff R.C.
        • Duncan M.J
        Associations between changes in activity and sleep quality and duration over two years.
        Med Sci Sports Exerc. 2018; 4: 339-348
        • Wennman H.
        • Kronholm E.
        • Heinonen O.J.
        • et al.
        Leisure time physical activity and sleep predict mortality in men irrespective of background in competitive sports.
        Prog Prev Med. 2017; 2: e0009
        • Kovacevic A.
        • Mavros Y.
        • Heisz J.J.
        • Fiatarone Singh M.A
        The effect of resistance exercise on sleep: a systematic review of randomized controlled trials.
        Sleep Med Rev. 2018; 39: 52-68
        • Yang Y.
        • Shin J.C.
        • Li D.
        • An R
        Sedentary behavior and sleep problems: a systematic review and meta-analysis.
        Int J Behav Med. 2016; 24: 481-492
        • Duncan M.J.
        • Kline C.E.
        • Rebar A.L.
        • Vandelanotte C.
        • Short C.E
        Greater bed- and wake-time variability is associated with less healthy lifestyle behaviors: a cross-sectional study.
        J Public Health. 2015; 24: 31-40
        • Haario P.
        • Rahkonen O.
        • Laaksonen M.
        • Lahelma E.
        • Lallukka T
        Bidirectional associations between insomnia symptoms and unhealthy behaviours.
        J Sleep Res. 2013; 22: 89-95
        • Australian Institute of Health and Welfare
        The Active Australia Survey: A Guide and Manual for Implementation, Analysis and Reporting.
        AIHW, Canberra2003
        • Australian Government
        Australia's Physical Activity and Sedentary Behaviour Guidelines.
        Australian Government, Canberra2014
        • Murawski B.
        • Plotnikoff R.C.
        • Rayward A.T.
        • Oldmeadow C.
        • Vandelanotte C.
        • Brown W.J.
        • et al.
        Efficacy of an m-health physical activity and sleep health intervention for adults: a randomized waitlist-controlled trial.
        Am J Prev Med. 2019; 57: 503-514
        • Chau J.Y.
        • van der Ploeg H.P.
        • Dunn S.
        • Kurko J.
        • Bauman A.E
        A tool for measuring workers' sitting time by domain: the Workforce Sitting Questionnaire.
        Br J Sports Med. 2011; 45: 1216-1222
        • Buysse D.J.
        • Reynolds C.F.
        • Monk 3rd, TH
        • Berman S.R.
        • Kupfer D.J
        The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research.
        Psychiatry Res. 1989; 28: 193-213
        • Hirshkowitz M.
        • Whiton K.
        • Albert S.M.
        • et al.
        National Sleep Foundation's sleep time duration recommendations: methodology and results summary.
        Sleep Health. 2015; 1: 40-43
        • Duncan M.J.
        • Kline C.E.
        • Vandelanotte C.
        • Sargent C.
        • Rogers N.L.
        • Di Milia L
        Cross-sectional associations between multiple lifestyle behaviors and health-related quality of life in the 10,000 Steps cohort.
        PLoS ONE. 2014; 9: e94184
        • Monk T.H.
        • Buysse D.J.
        • Kennedy K.S.
        • Pods J.M.
        • DeGrazia J.M.
        • Miewald J.M
        Measuring sleep habits without using a diary: the sleep timing questionnaire.
        Sleep. 2003; 26: 208-212
        • Soehner A.M.
        • Kennedy K.S.
        • Monk T.H
        Circadian preference and sleep-wake regularity: associations with self-report sleep parameters in daytime-working adults.
        Chronobiol Int. 2011; 28: 802-809
        • Grandner M.A
        Sleep, health, and society.
        Sleep Med Clin. 2017; 12: 1-22
        • Collins L.M.
        • Lanza S.T
        Latent Class and Latent Transition Analysis.
        John Wiley & Sons, Inc., 2010
      1. Vermunt J., Magidson J. Local Independence 2004 2018/11/17. In: The SAGE Encyclopedia of Social Science Research Methods [Internet]. Thousand Oaks Thousand Oaks, California: SAGE Publications, Inc. Available at: http://sk.sagepub.com/reference/socialscience. Accessed November 17, 2018.

        • DeSalvo K.B.
        • Bloser N.
        • Reynolds K.
        • He J.
        • Muntner P
        Mortality prediction with a single general self-rated health question. A meta-analysis.
        J Gen Intern Med. 2006; 21: 267-275
        • Keadle S.K.
        • Kravitz E.S.
        • Matthews C.E.
        • Tseng M.
        • Carroll R.J
        Development and testing of an integrated score for physical behaviors.
        Med Sci Sports Exerc. 2019; 51: 1759-1766
        • Buman M.P.
        • Epstein D.R.
        • Gutierrez M.
        • et al.
        BeWell24: development and process evaluation of a smartphone “app” to improve sleep, sedentary, and active behaviors in US Veterans with increased metabolic risk.
        Transl Behav Med. 2015; 6: 438-448
        • Bennie J.A.
        • Pedisic Z.
        • Timperio A.
        • et al.
        Total and domain-specific sitting time among employees in desk-based work settings in Australia.
        Aust New Zealand J Public Health. 2015; 39: 237-242
        • Theorell-Haglöw J.
        • Miller C.B.
        • Bartlett D.J.
        • Yee B.J.
        • Openshaw H.D.
        • Grunstein R.R
        Gender differences in obstructive sleep apnoea, insomnia and restless legs syndrome in adults – What do we know? A clinical update.
        Sleep Med Rev. 2018; 38: 28-38
        • Gordon S.
        • Vandelanotte C.
        • Rayward A.T.
        • Murawski B.
        • Duncan M.J
        Sociodemographic and behavioral correlates of insufficient sleep in Australian adults.
        Sleep Health. 2019; 5: 12-17
        • Hinz A.
        • Glaesmer H.
        • Brähler E.
        • et al.
        Sleep quality in the general population: psychometric properties of the Pittsburgh Sleep Quality Index, derived from a German community sample of 9284 people.
        Sleep Med. 2017; 30: 57-63
        • Clark B.K.
        • Kolbe-Alexander T.L.
        • Duncan M.J.
        • Brown W
        Sitting time, physical activity and sleep by work type and pattern-The Australian longitudinal study on women's health.
        Int J Environ Res Public Health. 2017; 14https://doi.org/10.3390/ijerph14030290
        • Deutskens E.
        • de Ruyter K.
        • Wetzels M.
        • Oosterveld P
        Response rate and response quality of internet-based surveys: an Experimental Study.
        Mark Lett. 2004; 15: 21-36
        • Pedersen M.J.
        • Nielsen C.V.
        Improving survey response rates in online panels: effects of low-cost incentives and cost-free text appeal interventions.
        Soc Sci Comput Rev. 2016; 34: 229-243
        • Van Mol C
        Improving web survey efficiency: the impact of an extra reminder and reminder content on web survey response.
        Int J Soc Res Methodol. 2017; 20: 317-327