Integrating sleep, sedentary behaviour, and physical activity research in the emerging field of time-use epidemiology: definitions, concepts, statistical methods, theoretical framework, and future directions


  • Željko Pedišić Institute of Sport, Exercise and Active Living (ISEAL), Victoria University, Melbourne, Australia
  • Dorothea Dumuid School of Health Sciences, University of South Australia, Adelaide, Australia
  • Timothy Stephen Olds School of Health Sciences, University of South Australia, Adelaide, Australia


Nearly 70 years of sleep, sedentary behaviour, physical activity, and time-use research has led to the recent development of time-use epidemiology. To conceptualise the emerging research field and provide a framework for its further development, this paper defines its position among established branches of science, explains its main concepts and defines associated terms, recommends suitable data analysis methods, proposes a theoretical model for future research, and identifies key research questions. Time-use epidemiology is defined as the study of determinants, incidence, distributions, and effects of health-related time-use patterns in populations, and methods for preventing unhealthy time-use patterns and achieving the optimal distribution of time for population health. As a theoretical model for future studies, this paper proposes The Framework for Viable Integrative Research in Time-Use Epidemiology (VIRTUE framework), acknowledging the compositional nature of time-use data and incorporating research on: 1) methods in time-use epidemiology; 2) outcomes of time-use composition; 3) optimal time-use balance and its prevalence in populations; 4) determinants and correlates of time-use composition; and 5) effectiveness of time-use interventions. It is likely that in total more deaths worldwide can be attributed to unhealthy time use than to smoking or obesity, potentially making it the most relevant modifiable behavioural and lifestyle risk factor of our time. We hope that governments and leading health organisations will recognise the enormous importance of healthy time use, and provide adequate support for future research in time-use epidemiology.


Aas, D. (1982). Designs for large scale time use studies of the 24 hour day. In Z. Staikov (Ed.), It’s about time: Proceedings of the International Research Group on Time Budgets and Social Activities (pp. 17-53). Sofia, Bulgaria: Institute of Sociology at the Bulgarian Academy of Sciences, Bulgarian Sociological Association.

Ainsworth, B.E., Haskell, W.L., Herrmann, S.D., Meckes, N., Bassett Jr, D.R., Tudor-Locke, C., . . . Leon, A.S. (2011). 2011 compendium of physical activities: A second update of codes and MET values. Medicine and Science in Sports and Exercise, 43(8), 1575-1581. doi: 10.1249/MSS.0b013e31821ece12

Aitchison, J. (1982). The statistical analysis of compositional data. Journal of the Royal Statistical Society. Series B (Methodological), 44(2), 139-177.

Aitchison, J. (1986). The statistical analysis of compositional data. London, UK: Chapman and Hall.

Aitchison, J. (2005). A concise guide to compositional data analysis. Retrieved on 16th May, 2017, from

Aitchison, J., Barceló-Vidal, C., Martín-Fernández, J.A., & Pawlowsky-Glahn, V. (2000). Logratio analysis and compositional distance. Mathematical Geology, 32(3), 271-275. doi: 10.1023/A:1007529726302

Aitchison, J., & Greenacre, M. (2002). Biplots of compositional data. Journal of the Royal Statistical Society. Series C: Applied Statistics, 51(4), 375-392. doi: 10.1111/1467-9876.00275

Aitchison, J., & Shen, S.M. (1980). Logistic-normal distributions: Some properties and uses. Biometrika, 67(2), 261-272. doi: 10.1093/biomet/67.2.261

Barnes, G.M., Hoffman, J.H., Welte, J.W., Farrell, M.P., & Dintcheff, B.A. (2007). Adolescents’ time use: Effects on substance use, delinquency and sexual activity. Journal of Youth and Adolescence, 36(5), 697-710. doi: 10.1007/s10964-006-9075-0

Bauman, A.E., Reis, R.S., Sallis, J.F., Wells, J.C., Loos, R.J.F., & Martin, B.W. (2012). Correlates of physical activity: Why are some people physically active and others not? The Lancet, 380(9838), 258-271.

Bear, J., & Billheimer, D. (2016). A logistic normal mixture model for compositional data allowing essential zeros. Austrian Journal of Statistics, 45(4), 3-23. doi: 10.17713/ajs.v45i4.117

Biddle, S.J.H., García Bengoechea, E., & Wiesner, G. (2017). Sedentary behaviour and adiposity in youth: A systematic review of reviews and analysis of causality. International Journal of Behavioral Nutrition and Physical Activity, 14(43), 1-21. doi: 10.1186/s12966-017-0497-8

Bin, Y.S., Marshall, N.S., & Glozier, N. (2012). Secular trends in adult sleep duration: A systematic review. Sleep Medicine Reviews, 16(3), 223-230. doi: 10.1016/j.smrv.2011.07.003

Bird, C.E., & Fremont, A.M. (1991). Gender, time use, and health. Journal of Health and Social Behavior, 32(2), 114-129.

Bixler, E.O., Kales, A., Soldatos, C.R., Kales, J.D., & Healey, S. (1979). Prevalence of sleep disorders in the Los Angeles metropolitan area. American Journal of Psychiatry, 136(10), 1257-1262.

Boyle, T., Vallance, J.K., Buman, M.P., & Lynch, B.M. (2017). Reallocating time to sleep, sedentary time, or physical activity: Associations with waist circumference and body mass index in breast cancer survivors. Cancer Epidemiology Biomarkers and Prevention, 26(2), 254-260. doi: 10.1158/1055-9965.EPI-16-0545

Buman, M.P., Winkler, E.A.H., Kurka, J.M., Hekler, E.B., Baldwin, C.M., Owen, N., . . . Gardiner, P.A. (2014). Reallocating time to sleep, sedentary behaviors, or active behaviors: Associations with cardiovascular disease risk biomarkers, NHANES 2005-2006. American Journal of Epidemiology, 179(3), 323-334.

Cappuccio, F.P., Cooper, D., Delia, L., Strazzullo, P., & Miller, M.A. (2011). Sleep duration predicts cardiovascular outcomes: A systematic review and meta-analysis of prospective studies. European Heart Journal, 32(12), 1484-1492.

Cappuccio, F.P., D’Elia, L., Strazzullo, P., & Miller, M.A. (2010a). Quantity and quality of sleep and incidence of type 2 diabetes: A systematic review and meta-analysis. Diabetes Care, 33(2), 414-420.

Cappuccio, F.P., D’Elia, L., Strazzullo, P., & Miller, M.A. (2010b). Sleep duration and all-cause mortality: A systematic review and meta-analysis of prospective studies. Sleep, 33(5), 585-592.

Carskadon, M.A., & Dement, W.C. (2011). Monitoring and staging human sleep. In M. H. Kryger, T. Roth & W. C. Dement (Eds.), Principles and practice of sleep medicine, 5th edition (pp. 16-26). St. Louis, US: Elsevier Saunders.

Carson, V., Tremblay, M.S., Chaput, J.P., & Chastin, S.F.M. (2016). Associations between sleep duration, sedentary time, physical activity, and health indicators among Canadian children and youth using compositional analyses. Applied Physiology, Nutrition and Metabolism, 41(6), S294-S302. doi: 10.1139/apnm-2016-0026

Caspersen, C.J. (1989). Physical activity epidemiology: Concepts, methods, and applications to exercise science. Exercise and Sport Sciences Reviews, 17(1), 423-473.

Caspersen, C.J., Powell, K.E., & Christenson, G. (1985). Physical activity, exercise and physical fitness: Definitions and distinctions for health-related research. Public Health Reports, 100(2), 126-131.

Chaput, J.P., Carson, V., Gray, C.E., & Tremblay, M.S. (2014). Importance of all movement behaviors in a 24 hour period for overall health. International Journal of Environmental Research and Public Health, 11(12), 12575-12581. doi: 10.3390/ijerph111212575

Chaput, J.P., Saunders, T.J., & Carson, T.J. (2017). Interactions between sleep, movement and other nonmovement behaviours in the pathogenesis of childhood obesity. Obesity Reviews, 18(Suppl. 1), 7-14.

Chastin, S.F.M., Buck, C., Freiberger, E., Murphy, M., Brug, J., Cardon, G., . . . Oppert, J.M. (2015). Systematic literature review of determinants of sedentary behaviour in older adults: A DEDIPAC study. International Journal of Behavioral Nutrition and Physical Activity, 12(127), 1-12. doi: 10.1186/s12966-015-0292-3

Chastin, S.F.M., Palarea-Albaladejo, J., Dontje, M.L., & Skelton, D.A. (2015). Combined effects of time spent in physical activity, sedentary behaviors and sleep on obesity and cardio-metabolic health markers: A novel compositional data analysis approach. PLoS ONE, 10(10), e0139984. doi: 10.1371/journal.pone.0139984

de Rezende, L.F.M., de Sá, T.H., Mielke, G.I., Viscondi, J.Y.K., Rey-López, J.P., & Garcia, L.M.T. (2016). All-cause mortality attributable to sitting time: Analysis of 54 countries worldwide. American Journal of Preventive Medicine, 51(2), 253-263. doi: 10.1016/j.amepre.2016.01.022

de Rezende, L.F.M., Lopes, M.R., Rey-Loṕez, J.P., Matsudo, V.K.R., & Luiz, O.D.C. (2014). Sedentary behavior and health outcomes: An overview of systematic reviews. PLoS ONE, 9(8), e105620. doi: 10.1371/journal.pone.0105620

Desha, L.N., & Ziviani, J.M. (2007). Use of time in childhood and adolescence: A literature review on the nature of activity participation and depression. Australian Occupational Therapy Journal, 54(1), 4-10. doi: 10.1111/j.1440-1630.2006.00649.x

Dumuid, D., Olds, T., Lewis, L.K., Martin-Fernández, J.A., Barreira, T., Broyles, S., . . . Maher, C. (2016). The adiposity of children is associated with their lifestyle behaviours: A cluster analysis of school-aged children from 12 nations. Pediatric Obesity. doi: 10.1111/ijpo.12196

Dumuid, D., Olds, T., Lewis, L.K., Martin-Fernández, J.A., Katzmarzyk, P.T., Barreira, T., . . . Maher, C. (2017). Health-related quality of life and lifestyle behavior clusters in school-aged children from 12 Countries. Journal of Pediatrics, 183(e2), 178-183. doi: 10.1016/j.jpeds.2016.12.048

Dumuid, D., Olds, T., Martín-Fernández, J.A., Lewis, L.K., Cassidy, L., & Maher, C. (2017). Academic performance and lifestyle behaviors in australian school children: A cluster analysis. Health Education & Behavior, 1-10. doi: 10.1177/1090198117699508

Dumuid, D., Pedišić, Ž., Stanford, T.E., Martín-Fernández, J.A., Hron, K., Maher, C., . . . Olds, T. (in press). The Compositional Isotemporal Substitution Model: A method for estimating changes in a health outcome for reallocation of time between sleep, sedentary behaviour, and physical activity. Statistical Methods in Medical Research.

Dumuid, D., Stanford, T.E., Martin-Fernandez, J.A., Pedišić, Ž., Maher, C.A., Lewis, L.K., . . . Olds, T. (2017). Compositional data analysis for physical activity, sedentary time and sleep research. Statistical Methods in Medical Research. doi: 10.1177/0962280217710835

Egozcue, J.J., & Pawlowsky-Glahn, V. (2005). Groups of parts and their balances in compositional data analysis. Mathematical Geology, 37(7), 795-828. doi: 10.1007/s11004-005-7381-9

Egozcue, J.J., Pawlowsky-Glahn, V., Mateu-Figueras, G., & Barceló-Vidal, C. (2003). Isometric logratio transformations for compositional data analysis. Mathematical Geology, 35(3), 279-300. doi: 10.1023/A:1023818214614

Eguchi, E., Iso, H., Tanabe, N., Wada, Y., Yatsuya, H., Kikuchi, S., . . . Tamakoshi, A. (2012). Healthy lifestyle behaviours and cardiovascular mortality among Japanese men and women: The Japan collaborative cohort study. European Heart Journal, 33(4), 467-477. doi: 10.1093/eurheartj/ehr429

Fairclough, S.J., Dumuid, D., Taylor, S., Curry, W., McGrane, B., Stratton, G., . . . Olds, T. (2017). Fitness, fatness and the reallocation of time between children’s daily movement behaviours: an analysis of compositional data. International Journal of Behavioral Nutrition and Physical Activity, 14(64), 1-12. doi: 10.1186/s12966-017-0521-z

Fanning, J., Porter, G., Awick, E.A., Ehlers, D.K., Roberts, S.A., Cooke, G., . . . McAuley, E. (2017). Replacing sedentary time with sleep, light, or moderate-to-vigorous physical activity: effects on self-regulation and executive functioning. Journal of Behavioral Medicine, 40(2), 332-342. doi: 10.1007/s10865-016-9788-9

Ferrie, J.E., Kumari, M., Salo, P., Singh-Manoux, A., & Kivimäki, M. (2011). Sleep epidemiology – a rapidly growing field. International Journal of Epidemiology, 40(6), 1431-1437. doi: 10.1093/ije/dyr203

Filzmoser, P., & Hron, K. (2009). Correlation analysis for compositional data. Mathematical Geosciences, 41(8), 905-919. doi: 10.1007/s11004-008-9196-y

Filzmoser, P., Hron, K., & Reimann, C. (2012). Interpretation of multivariate outliers for compositional data. Computers and Geosciences, 39(1), 77-85. doi: 10.1016/j.cageo.2011.06.014

Filzmoser, P., Hron, K., Reimann, C., & Garrett, R. (2009). Robust factor analysis for compositional data. Computers and Geosciences, 35(9), 1854-1861. doi: 10.1016/j.cageo.2008.12.005

Filzmoser, P., Hron, K., & Templ, M. (2012). Discriminant analysis for compositional data and robust parameter estimation. Computational Statistics, 27(4), 585-604. doi: 10.1007/s00180-011-0279-8

Foley, L., Maddison, R., Olds, T., & Ridley, K. (2012). Self-report use-of-time tools for the assessment of physical activity and sedentary behaviour in young people: Systematic review. Obesity Reviews, 13(8), 711-722. doi: 10.1111/j.1467-789X.2012.00993.x

Gomersall, S.R., Rowlands, A.V., English, C., Maher, C., & Olds, T.S. (2013). The Activitystat hypothesis: The concept, the evidence and the methodologies. Sports Medicine, 43(2), 135-149. doi: 10.1007/s40279-012-0008-7

Halim, I., & Omar, A.R. (2011). A review on health effects associated with prolonged standing in the industrial workplaces. International Journal of Recent Research and Applied Studies, 8(1), 14-21.

Hallal, P.C., Andersen, L.B., Bull, F.C., Guthold, R., Haskell, W., & Ekelund, U. (2012). Global physical activity levels: Surveillance progress, pitfalls, and prospects. The Lancet, 380(9838), 247-257.

Healy, G.N., Clark, B.K., Winkler, E.A.H., Gardiner, P.A., Brown, W.J., & Matthews, C.E. (2011). Measurement of adults’ sedentary time in population-based studies. American Journal of Preventive Medicine, 41(2), 216-227.

Healy, G.N., Dunstan, D.W., Salmon, J., Cerin, E., Shaw, J.E., Zimmet, P.Z., & Owen, N. (2007). Objectively measured light-intensity physical activity is independently associated with 2-h plasma glucose. Diabetes Care, 30(6), 1384-1389.

Heath, G.W., Parra, D.C., Sarmiento, O.L., Andersen, L.B., Owen, N., Goenka, S., . . . Wells, J.C. (2012). Evidence-based intervention in physical activity: Lessons from around the world. The Lancet, 380(9838), 272-281. doi: 10.1016/S0140-6736(12)60816-2

Helmerhorst, H.J.F., Brage, S., Warren, J., Besson, H., & Ekelund, U. (2012). A systematic review of reliability and objective criterion-related validity of physical activity questionnaires. International Journal of Behavioral Nutrition and Physical Activity, 9(103), 1-55.

Hron, K., Filzmoser, P., & Thompson, K. (2012). Linear regression with compositional explanatory variables. Journal of Applied Statistics, 39(5), 1115-1128. doi: 10.1080/02664763.2011.644268

Huang, W.Y., Wong, S.H.S., He, G., & Salmon, J. (2016). Isotemporal substitution analysis for sedentary behavior and body mass index. Medicine and Science in Sports and Exercise, 48(11), 2135-2141. doi: 10.1249/MSS.0000000000001002

International Epidemiological Association. (2014). A dictionary of epidemiology. Oxford, UK: Oxford University Press.

Jowsey, T., McRae, I.S., Valderas, J.M., Dugdale, P., Phillips, R., Bunton, R., . . . Yen, L. (2013). Time’s up. Descriptive epidemiology of multi-morbidity and time spent on health related activity by older Australians: A time use survey. PLoS ONE, 8(4), e59379. doi: 10.1371/journal.pone.0059379

Kang, M., & Rowe, D.A. (2015). Issues and challenges in sedentary behavior measurement. Measurement in Physical Education and Exercise Science, 19(3), 105-115. doi: 10.1080/1091367X.2015.1055566

Katzmarzyk, P.T. (2014). Standing and mortality in a prospective cohort of Canadian adults. Medicine and Science in Sports and Exercise, 46(5), 940-946.

Kepplinger, D. (2015). Package ‘complmrob’. Retrieved on 15th June, 2017, from

Knutson, K.L. (2013). Sociodemographic and cultural determinants of sleep deficiency: Implications for cardiometabolic disease risk. Social Science and Medicine, 79(1), 7-15. doi: 10.1016/j.socscimed.2012.05.002

Koski, P., Matarma, T., Pedišić, Ž., Kokko, S., Lane, A., Hartmann, H., . . . Savola, J. (2017). Sports Club for Health (SCforH) – updated guidelines for health-enhancing sports activities in a club setting. Helsinki, FI: Finnish Olympic Committee.

Lee, I.M., Shiroma, E.J., Lobelo, F., Puska, P., Blair, S.N., Katzmarzyk, P.T., . . . Wells, J.C. (2012). Effect of physical inactivity on major non-communicable diseases worldwide: An analysis of burden of disease and life expectancy. The Lancet, 380(9838), 219-229.

Lee, P.H. (2014). Should we adjust for a confounder if empirical and theoretical criteria yield contradictory results? A simulation study. Scientific Reports, 4(6085), 1-14. doi: 10.1038/srep06085

Lilienfeld, D.E. (1978). Definitions of epidemiology. American Journal of Epidemiology, 107(2), 87-90.

Lynch, B.M., & Owen, N. (2015). Too much sitting and chronic disease risk: Steps to move the science forward. Annals of Internal Medicine, 162(2), 146-147. doi: 10.7326/M14-2552

Mangham, L.J., Hanson, K., & McPake, B. (2009). How to do (or not to do)...Designing a discrete choice experiment for application in a low-income country. Health Policy and Planning, 24(2), 151-158. doi: 10.1093/heapol/czn047

Marshall, S.J., Biddle, S.J.H., Sallis, J.F., McKenzie, T.L., & Conway, T.L. (2002). Clustering of sedentary behaviors and physical activity among youth: A cross-national study. Pediatric Exercise Science, 14(4), 401-417.

Martín-Fernández, J.A., Barceló-Vidal, C., & Pawlowsky-Glahn, V. (1998). Measures of difference for compositional data and hierarchical clustering methods. In A. Buccianti, G. Nardi & R. Potenza (Eds.), Proceedings of IAMG’ 98: the fourth annual conference of the International Association for Mathematical Geology. Naples, Italy: International Association for Mathematical Geology.

Martín-Fernández, J.A., Daunis-I-estadella, J., & Mateu-Figueras, G. (2015). On the interpretation of differences between groups for compositional data. SORT, 39(2), 231-252.

Martín-Fernández, J.A., Hron, K., Templ, M., Filzmoser, P., & Palarea-Albaladejo, J. (2012). Model-based replacement of rounded zeros in compositional data: Classical and robust approaches. Computational Statistics and Data Analysis, 56(9), 2688-2704. doi: 10.1016/j.csda.2012.02.012

Martín-Ferńandez, J.A., Palarea-Albaladejo, J., & Olea, R.A. (2011). Dealing with zeros. In V. Pawlowsky-Glahn & A. Buccianti (Eds.), Compositional data analysis: Theory and applications (pp. 43-58). Chichester, UK: John Wiley & Sons, Ltd.

Mekary, R.A., Willett, W.C., Hu, F.B., & Ding, E.L. (2009). Isotemporal substitution paradigm for physical activity epidemiology and weight change. American Journal of Epidemiology, 170(4), 519-527. doi: 10.1093/aje/kwp163

Merriam-Webster Inc. (2017). Merriam-Webster’s online dictionary. Retrieved on 20th June, 2017, from

Merz, J. (2002). Time use research and time use data actual topics and new frontiers. Lüneburg, Germany: University of Lüneburg.

Michels, K.B. (2003). Nutritional epidemiology – Past, present, future. International Journal of Epidemiology, 32(4), 486-488. doi: 10.1093/ije/dyg216

Morris, J.N., Heady, J.A., Raffle, P.A.B., Roberts, C.G., & Parks, J.W. (1953). Coronary heart disease and physical activity of work. The Lancet, 262(6795), 1053-1057.

New Zealand Ministry of Health. (2017). Sit less, move more, sleep well: Physical activity guidelines for children and young people. Retrieved on 24th June, 2017, from

Ng, S.W., & Popkin, B.M. (2012). Time use and physical activity: A shift away from movement across the globe. Obesity Reviews, 13(8), 659-680.

Owen, N., Bauman, A., & Brown, W. (2009). Too much sitting: A novel and important predictor of chronic disease risk? British Journal of Sports Medicine, 43(2), 81-83.

Owen, N., Leslie, E., Salmon, J., & Fotheringham, M.J. (2000). Environmental determinants of physical activity and sedentary behavior. Exercise and Sport Sciences Reviews, 28(4), 153-158.

Page, A., Peeters, G., & Merom, D. (2015). Adjustment for physical activity in studies of sedentary behaviour. Emerging Themes in Epidemiology, 12(10), 1-4. doi: 10.1186/s12982-015-0032-9

Palarea-Albaladejo, J., & Martin-Fernandez, J.A. (2016). Package ‘zCompositions’. Retrieved on 15th June, 2017, from

Pate, R.R., O’Neill, J.R., & Lobelo, F. (2008). The evolving definition of "sedentary". Exercise and Sport Sciences Reviews, 36(4), 173-178.

Pawlowsky-Glahn, V., Egozcue, J.J., & Tolosana-Delgado, R. (2015a). Compositional data and their sample space. In V. Pawlowsky-Glahn, J. J. Egozcue & R. Tolosana-Delgado (Eds.), Modeling and analysis of compositional data (pp. 8-22). Chichester, UK: John Wiley & Sons, Ltd.

Pawlowsky-Glahn, V., Egozcue, J.J., & Tolosana-Delgado, R. (2015b). Modeling and analysis of compositional data. Chichester, UK: John Wiley & Sons, Ltd.

Pedišić, Ž. (2014). Measurement issues and poor adjustments for physical activity and sleep undermine sedentary behaviour research – The focus should shift to the balance between sleep, sedentary behaviour, standing and activity. Kinesiology, 46(1), 135-146.

Pedišić, Ž., & Bauman, A. (2015). Accelerometer-based measures in physical activity surveillance: current practices and issues. British Journal of Sports Medicine, 49(4), 219-223. doi: 10.1136/bjsports-2013-093407

Pentland, W., Harvey, A.S., & Walker, J. (1998). The relationships between time use and health and well‐being in men with spinal cord injury. Journal of Occupational Science, 5(1), 14-25. doi: 10.1080/14427591.1998.9686431

Ranasinghe, S., Al MacHot, F., & Mayr, H.C. (2016). A review on applications of activity recognition systems with regard to performance and evaluation. International Journal of Distributed Sensor Networks, 12(8). doi: 10.1177/1550147716665520

Ridley, K., Olds, T.S., & Hill, A. (2006). The Multimedia Activity Recall for Children and Adolescents (MARCA): Development and evaluation. International Journal of Behavioral Nutrition and Physical Activity, 3(10), 1-11. doi: 10.1186/1479-5868-3-10

Ryan, M., Bate, A., Eastmond, C.J., & Ludbrook, A. (2001). Use of discrete choice experiments to elicit preferences. Quality in Health Care, 10(Suppl. 1), i55-i60.

Sallis, J.F., Cervero, R.B., Ascher, W., Henderson, K.A., Kraft, M.K., & Kerr, J. (2006). An ecological approach to creating active living communities. Annual Review of Public Health, 27(1), 297-322. doi: 10.1146/annurev.publhealth.27.021405.102100

Sallis, J.F., Owen, N., & Fotheringham, M.J. (2000). Behavioral epidemiology: A systematic framework to classify phases of research on health promotion and disease prevention. Annals of behavioral medicine, 22(4), 294-298.

Sallis, J.F., Prochaska, J.J., & Taylor, W.C. (2000). A review of correlates of physical activity of children and adolescents. Medicine and Science in Sports and Exercise, 32(5), 963-975.

Sedentary Behaviour Research Network. (2012). Letter to the editor: Standardized use of the terms "sedentary" and "sedentary behaviours". Applied Physiology, Nutrition and Metabolism, 37(3), 540-542.

Shrestha, N., Kukkonen-Harjula, K.T., Verbeek, J.H., Ijaz, S., Hermans, V., & Bhaumik, S. (2016). Workplace interventions for reducing sitting at work. Cochrane Database of Systematic Reviews, 2016(3), 1-133. doi: 10.1002/14651858.CD010912.pub3

St George, A., Kite, J., Hector, D., Pedišić, Ž., Bellew, B., & Bauman, A. (2014). Beyond overweight and obesity – HEAL targets for overweight and obesity and the six HEAL objectives: A rapid review of the evidence. Sydney: NSW Ministry of Health.

Stamatakis, E., Rogers, K., Ding, D., Berrigan, D., Chau, J., Hamer, M., & Bauman, A. (2015). All-cause mortality effects of replacing sedentary time with physical activity and sleeping using an isotemporal substitution model: A prospective study of 201,129 mid-aged and older adults. International Journal of Behavioral Nutrition and Physical Activity, 12(121), 1-10. doi: 10.1186/s12966-015-0280-7

Stokols, D. (1992). Establishing and maintaining healthy environments: Toward a social ecology of health promotion. American Psychologist, 47(1), 6-22.

Stokols, D. (1996). Translating social ecological theory into guidelines for community health promotion. American Journal of Health Promotion, 10(4), 282-298.

Taylor, R.W., Williams, S.M., Farmer, V.L., & Taylor, B.J. (2013). Changes in physical activity over time in young children: A longitudinal study using accelerometers. PLoS ONE, 8(11), e81567. doi: 10.1371/journal.pone.0081567

Templ, M., Hron, K., & Filzmoser, P. (2017). Package ‘robCompositions’. Retrieved on 15th June, 2017, from

Thió-Henestrosa, S., & Comas, M. (2016). CoDaPack v2 user’s guide. Retrieved on 15th June, 2017, from

Thió-Henestrosa, S., & Martín-Fernández, J.A. (2005). Dealing with compositional data: The freeware CoDaPack. Mathematical Geology, 37(7), 773-793. doi: 10.1007/s11004-005-7379-3

Thraen-Borowski, K.M., Ellingson, L.D., Meyer, J.D., & Cadmus-Bertram, L. (2017). Nonworksite interventions to reduce sedentary behavior among adults: A systematic review. Translational Journal of the American College of Sports Medicine, 2(12), 68-77.

Tremblay, M.S., Aubert, S., Barnes, J.D., Saunders, T.J., Carson, V., Latimer-Cheung, A.E., . . . Chinapaw, M.J.M. (2017). Sedentary Behavior Research Network (SBRN) – Terminology consensus project process and outcome. International Journal of Behavioral Nutrition and Physical Activity, 14(75), 1-17. doi: 10.1186/s12966-017-0525-8

Tremblay, M.S., Carson, V., Chaput, J.P., Connor Gorber, S., Dinh, T., Duggan, M., . . . Zehr, L. (2016). Canadian 24-hour movement guidelines for children and youth: An integration of physical activity, sedentary behaviour, and sleep. Applied Physiology, Nutrition and Metabolism, 41(6), S311-S327. doi: 10.1139/apnm-2016-0151

Tremblay, M.S., Esliger, D.W., Tremblay, A., & Colley, R. (2007). Incidental movement, lifestyle-embedded activity and sleep: New frontiers in physical activity assessment. Applied Physiology, Nutrition and Metabolism, 32(Suppl. 2e), S208-S217. doi: 10.1139/H07-130

Trost, S.G., Owen, N., Bauman, A.E., Sallis, J.F., & Brown, W. (2002). Correlates of adults’ participation in physical activity: Review and update. Medicine and Science in Sports and Exercise, 34(12), 1996-2001.

Vallance, J.K., Buman, M.P., Lynch, B.M., & Boyle, T. (2017). Reallocating time to sleep, sedentary, and active behaviours in non-Hodgkin lymphoma survivors: associations with patient-reported outcomes. Annals of Hematology, 96(5), 749-755. doi: 10.1007/s00277-017-2942-9

van den Boogaart, G.K., & Tolosana-Delgado, R. (2013). Analyzing Compositional Data with R. Heidelberg, DE: Springer.

van den Boogaart, G.K., Tolosana, R., & Bren, M. (2015). Package ‘compositions’. Retrieved on 15th June, 2017, from

van der Ploeg, H.P., Chey, T., Ding, D., Chau, J.Y., Stamatakis, E., & Bauman, A.E. (2014). Standing time and all-cause mortality in a large cohort of Australian adults. Preventive Medicine, 69(1), 187-191. doi: 10.1016/j.ypmed.2014.10.004

van der Ploeg, H.P., Merom, D., Chau, J.Y., Bittman, M., Trost, S.G., & Bauman, A.E. (2010). Advances in population surveillance for physical activity and sedentary behavior: Reliability and validity of time use surveys. American Journal of Epidemiology, 172(10), 1199-1206.

Vézina-Im, L.A., Moreno, J.P., Nicklas, T.A., & Baranowski, T. (2017). Behavioral interventions to promote adequate sleep among women: Protocol for a systematic review and meta-analysis. Systematic Reviews, 6(95), 1-6. doi: 10.1186/s13643-017-0490-y

Waters, T.R., & Dick, R.B. (2015). Evidence of health risks associated with prolonged standing at work and intervention effectiveness. Rehabilitation Nursing, 40(3), 148-165. doi: 10.1002/rnj.166

Whitty, J.A., Burton, P., Kendall, E., Ratcliffe, J., Wilson, A., Littlejohns, P., & Scuffham, P.A. (2014). Harnessing the potential to quantify public preferences for healthcare priorities through citizens’ juries. International Journal of Health Policy and Management, 3(2), 57-62. doi: 10.15171/ijhpm.2014.61

Wijndaele, K., & Healy, G.N. (2016). Sitting and chronic disease: Where do we go from here? Diabtologia, 59(4), 688-691. doi: 10.1007/s00125-016-3886-7

Willett, W.C. (1998). Issues in analysis and presentation of dietary data. In W. C. Willett (Ed.), Nutritional epidemiology, 2nd edition (pp. 321-346). New York, NY: Oxford University Press.

Williams, S.M., Farmer, V.L., Taylor, B.J., & Taylor, R.W. (2014). Do more active children sleep more? A repeated cross-sectional analysis using accelerometry. PLoS ONE, 9(4), e93117. doi: 10.1371/journal.pone.0093117

World Health Organization. (2006). Constitution of the World Health Organization, 45th edition. Geneva, CH: World Health Organization.

Xi, B., He, D., Zhang, M., Xue, J., & Zhou, D. (2014). Short sleep duration predicts risk of metabolic syndrome: A systematic review and meta-analysis. Sleep Medicine Reviews, 18(4), 293-297. doi: 10.1016/j.smrv.2013.06.001

Yoong, S.L., Chai, L.K., Williams, C.M., Wiggers, J., Finch, M., & Wolfenden, L. (2016). Systematic review and meta-analysis of interventions targeting sleep and their impact on child body mass index, diet, and physical activity. Obesity, 24(5), 1140-1147. doi: 10.1002/oby.21459

Zhang, B. (2013). On compositional data modeling and its biomedical applications. (Doctoral thesis), Columbia University New York, NY.

Zhao, H., Yin, J.Y., Yang, W.S., Qin, Q., Li, T.T., Shi, Y., . . . Nie, S.F. (2013). Sleep duration and cancer risk: A systematic review and meta-analysis of prospective studies. Asian Pacific Journal of Cancer Prevention, 14(12), 7509-7515.

Zhu, W., Ainsworth, B., & Liu, Y. (2002). A comparison of urban black and white women’s physical activity patterns. Paper presented at the 2002 annual convention of the American Alliance for Health, Physical Education, Recreation and Dance, San Diego, California, USA.




How to Cite

Pedišić, Željko, Dumuid, D., & Olds, T. S. (2017). Integrating sleep, sedentary behaviour, and physical activity research in the emerging field of time-use epidemiology: definitions, concepts, statistical methods, theoretical framework, and future directions. Kinesiology, 49(2), 252–269. Retrieved from




Most read articles by the same author(s)