How people use their time has been linked with their health. For example, spending more time being physically active is known to be beneficial for health, whereas long durations of sitting have been associated with unfavourable health outcomes. Accordingly, public health messages have advocated swapping strategies to promote the reallocation of time between parts of the time-use composition, such as "Move More, Sit Less", with the aim of achieving optimal distribution of time for health. However, the majority of research underpinning these public health messages has not considered daily time use as a composition, and has ignored the relative nature of time-use data. We present a way of applying compositional data analysis to estimate change in a health outcome when fixed durations of time are reallocated from one part of a particular time-use composition to another, while the remaining parts are kept constant, based on a multiple linear regression model on isometric log ratio coordinates. In an example, we examine the expected differences in Body Mass Index z-scores for reallocations of time between sleep, physical activity and sedentary behaviour.

College of Nursing and Health Sciences Flinders University Adelaide Australia

Department of Mathematical Analysis and Applications of Mathematics Palacký University Olomouc Czech Republic

Dept Informàtica Matemàtica Aplicada i Estadística Universitat de Girona Girona Spain

Institute of Sport Exercise and Active Living Victoria University Melbourne Australia

LBT Innovations Adelaide Australia

School of Health Sciences University of South Australia Adelaide Australia

School of Mathematical Sciences University of Adelaide Adelaide Australia

References provided by Crossref.org

Reallocating Time Between 24-h Movement Behaviors for Obesity Management Across the Lifespan: A Pooled Data Meta-Analysis of More Than 9800 Participants from Seven Countries

The interplay between lying, sitting, standing, moving, and walking on obesity risk in older adults: a compositional and isotemporal substitution analysis

Compositional functional regression and isotemporal substitution analysis: Methods and application in time-use epidemiology

Longitudinal reallocations of time between 24-h movement behaviours and their associations with inflammation in children and adolescents: the UP&DOWN study

Many different roads lead to Rome: equivalence of time-use for activity, sedentary and sleep behaviours and dietary intake profiles among adolescents

Your best day: An interactive app to translate how time reallocations within a 24-hour day are associated with health measures

Day-to-day pattern of work and leisure time physical behaviours: are low socioeconomic status adults couch potatoes or work warriors?

Replacing school and out-of-school sedentary behaviors with physical activity and its associations with adiposity in children and adolescents: a compositional isotemporal substitution analysis

Sedentary behavior patterns and adiposity in children: a study based on compositional data analysis

Are longitudinal reallocations of time between movement behaviours associated with adiposity among elderly women? A compositional isotemporal substitution analysis

Compositional Data Analysis in Time-Use Epidemiology: What, Why, How

Adiposity and changes in movement-related behaviors in older adult women in the context of the built environment: a protocol for a prospective cohort study