Selected publications relevant to time-use epidemiology:

Hallman, D. M., Mathiassen, S. E., van der Beek, A. J., Jackson, J. A., & Coenen, P. (2019). Calibration of self-reported time spent sitting, standing and walking among office workers: A compositional data analysis. International Journal of Environmental Research and Public Health, 16(17) doi:10.3390/ijerph16173111

Coenen P., Mathiassen S. E., van der Beek A. J., Hallman D. M. (2019). Correction of bias in self-reported sitting time among office workers – a study based on compositional data analysis. Scandinavian Journal of Work, Environment & Health, Epub ahead of print doi:10.5271/sjweh.3827

Chau, J. Y., Gomersall, S. R., Van Der Ploeg, H. P., & Milton, K. (2019). The evolution of time use approaches for understanding activities of daily living in a public health context. BMC Public Health, 19 doi:10.1186/s12889-019-6759-4

Dumuid, D., Wake, M., Clifford, S., Burgner, D., Carlin, J. B., Mensah, F. K., . . . Olds, T. (2019). The association of the body composition of children with 24-hour activity composition. Journal of Pediatrics, 208, 43-49.e9. doi:10.1016/j.jpeds.2018.12.030

Gupta, N., Korshøj, M., Dumuid, D., Coenen, P., Allesøe, K., & Holtermann, A. (2019). Daily domain-specific time-use composition of physical behaviors and blood pressure. International Journal of Behavioral Nutrition and Physical Activity, 16(1) doi:10.1186/s12966-018-0766-1

Mellow, M. L., Dumuid, D., Thacker, J. S., Dorrian, J., & Smith, A. E. (2019). Building your best day for healthy brain aging—The neuroprotective effects of optimal time use. Maturitas, 125, 33-40. doi:10.1016/j.maturitas.2019.04.204

Rasmussen, C. L., Palarea-Albaladejo, J., Korshøj, M., Gupta, N., Nabe-Nielsen, K., Holtermann, A., & Jørgensen, M. B. (2019). Is high aerobic workload at work associated with leisure time physical activity and sedentary behaviour among blue-collar workers? A compositional data analysis based on accelerometer data. PLoS ONE, 14(6) doi:10.1371/journal.pone.0217024

Taylor, R. W., Haszard, J. J., Farmer, V. L., Richards, R., Te Morenga, L., Meredith-Jones, K., & Mann, J. I. (2019). Do differences in compositional time use explain ethnic variation in the prevalence of obesity in children? analyses using 24-hour accelerometry. International Journal of Obesity, doi:10.1038/s41366-019-0377-1

Zhao, J., Mackay, L., Chang, K., Mavoa, S., Stewart, T., Ikeda, E., Donnellan, N., & Smith, M. (2019). Visualising Combined Time Use Patterns of Children’s Activities and Their Association with Weight Status and Neighbourhood Context. International Journal of Environmental Research and Public Health, 16(5), 897, https://doi.org/10.3390/ijerph16050897

Debache, I., Bergouignan, A., Chaix, B., Sneekes, E. M., Thomas, F., & Sueur, C. (2019). Associations of Sensor-Derived Physical Behavior with Metabolic Health: A Compositional Analysis in the Record Multisensor Study. International Journal of Environmental Research and Public Health, 16(5), doi.org/10.3390/ijerph16050741

Biddle, G. J. H., Edwardson, C. L., Henson, J., Davies, M. J., Khunti, K., Rowlands, A. V., & Yates, T. (2018). Associations of physical behaviours and behavioural reallocations with markers of metabolic health: A compositional data analysis. International Journal of Environmental Research and Public Health, 15(10) doi:10.3390/ijerph15102280

Chaput, J-P., Olds, T., & Tremblay, M.S. (2018). Public health guidelines on sedentary behaviour are important and needed: a provisional benchmark is better than no benchmark at all. British Journal of Sports Medicine, Epub ahead of print, doi: 10.1136/bjsports-2018-099964

Štefelová, N., Dygrýn, J., Hron, K., Gába, A., Rubín, L., & Palarea-Albaladejo, J. (2018). Robust compositional analysis of physical activity and sedentary behaviour data. International Journal of Environmental Research and Public Health, 15(10), doi:10.3390/ijerph15102248

Rodríguez-Gómez, I., Mañas, A., Losa-Reyna, J., Rodríguez-Mañas, L., Chastin, S. F. M., Alegre, L. M., . . . Ara, I. (2018). Associations between sedentary time, physical activity and bone health among older people using compositional data analysis. PLoS ONE, 13(10), doi:10.1371/journal.pone.0206013

Janurek, J., Hadi, S. A., Mojzisch, A., & Häusser, J. A. (2018). The association of the 24 hour distribution of time spent in physical activity, work, and sleep with emotional exhaustion. International Journal of Environmental Research and Public Health, 15(9), doi:10.3390/ijerph15091927

Duncan, S., Stewart, T., Mackay, L., Neville, J., Narayanan, A., Walker, C., Berry, S., Morton, S. (2018). Wear-Time Compliance with a Dual-Accelerometer System for Capturing 24-h Behavioural Profiles in Children and Adults. International Journal of Environmental Research and Public Health, 15(7), 1296. doi:10.3390/ijerph15071296

Lund Rasmussen, C., Palarea-Albaladejo, J., Bauman, A., Gupta, N., Nabe-Nielsen, K., Jørgensen, M.B., & Holtermann, A. (2018). Does Physically Demanding Work Hinder a Physically Active Lifestyle in Low Socioeconomic Workers? A Compositional Data Analysis Based on Accelerometer Data. International Journal of Environmental Research and Public Health, 15(7), 1306. doi:10.3390/ijerph15071306

Gupta, N., Dumuid, D., Korshøj, M., Jørgensen, M.B., Søgaard, K., & Holtermann, A. (2018). Is Daily Movement Behaviors’ Composition Related to Blood Pressure in Working Adults?. Medicine & Science in Sports & Exercise, doi:10.1249/MSS.0000000000001680

Gupta, N., Mathiassen, S. E., Mateu-Figueras, G., Heiden, M., Hallman, D. M., Jørgensen, M. B., & Holtermann, A. (2018). A comparison of standard and compositional data analysis in studies addressing group differences in sedentary behavior and physical activity. International Journal of Behavioral Nutrition and Physical Activity, 15(1) doi:10.1186/s12966-018-0685-1

Talarico, R., & Janssen, I. (2018). Compositional associations of time spent in sleep, sedentary behavior and physical activity with obesity measures in children. International Journal of Obesity, 1-7. doi:10.1038/s41366-018-0053-x

Winkler, E. A. H., Chastin, S., Eakin, E. G., Owen, N., Lamontagne, A. D., Moodie, M., . . . Healy, G. N. (2018). Cardiometabolic impact of changing sitting, standing, and stepping in the workplace. Medicine and Science in Sports and Exercise, 50(3), 516-524. doi:10.1249/MSS.0000000000001453

Dumuid, D., Lewis, L. K., Olds, T. S., Maher, C., Bondarenko, C., & Norton, L. (2018). Relationships between older adults’ use of time and cardio-respiratory fitness, obesity and cardio-metabolic risk: A compositional isotemporal substitution analysis. Maturitas, 110, 104-110. doi:10.1016/j.maturitas.2018.02.003

Dumuid, D., Maher, C., Lewis, L. K., Stanford, T. E., Martín Fernández, J. A., Ratcliffe, J., . . . Olds, T. (2018). Human development index, children’s health-related quality of life and movement behaviors: A compositional data analysis. Quality of Life Research, 27(6), 1473-1482. doi:10.1007/s11136-018-1791-x

Dumuid, D., Stanford, T. E., Pedišić, Ž., Maher, C., Lewis, L. K., Martín-Fernández, J. -., . . . Olds, T. (2018). Adiposity and the isotemporal substitution of physical activity, sedentary time and sleep among school-aged children: A compositional data analysis approach. BMC Public Health, 18(1) doi:10.1186/s12889-018-5207-1

Foley, L., Dumuid, D., Atkin, A. J., Olds, T., & Ogilvie, D. (2018). Patterns of health behaviour associated with active travel: A compositional data analysis. International Journal of Behavioral Nutrition and Physical Activity, 15(1) doi:10.1186/s12966-018-0662-8

Hunt, T., Williams, M. T., Olds, T. S., & Dumuid, D. (2018). Patterns of time use across the chronic obstructive pulmonary disease severity spectrum. International Journal of Environmental Research and Public Health, 15(3) doi:10.3390/ijerph15030533

Matricciani, L., Bin, Y. S., Lallukka, T., Kronholm, E., Wake, M., Paquet, C., . . . Olds, T. (2018). Rethinking the sleep-health link. Sleep Health, doi:10.1016/j.sleh.2018.05.004

Carson, V., Tremblay, M. S., & Chastin, S. F. M. (2017). Cross-sectional associations between sleep duration, sedentary time, physical activity, and adiposity indicators among canadian preschool-aged children using compositional analyses. BMC Public Health, 17 doi:10.1186/s12889-017-4852-0

Wong, M., Olds, T., Gold, L., Lycett, K., Dumuid, D., Muller, J., . . . Wake, M. (2017). Time-use patterns and health-related quality of life in adolescents. Pediatrics, 140(1) doi:10.1542/peds.2016-3656

Dumuid, D., Pedišić, Z., Stanford, T. E., Martín-Fernández, J. A., Hron, K., Maher, C., . . . Olds, T. (2017). 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, doi:10.1177/0962280217737805

Pedišić, Ž., Dumuid, D., & Olds, T. (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), 1-18.

Dumuid, D., Stanford, T. E., Martin-Fernandez, J. A., Pedisic, Z., 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

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

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:10.1177/10901981176995

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., 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

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

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

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

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

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.

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