TY - JOUR
T1 - The compositional isotemporal substitution model
T2 - A method for estimating changes in a health outcome for reallocation of time between sleep, physical activity and sedentary behaviour
AU - Dumuid, Dorothea
AU - Pedisic, Zeljko
AU - Stanford, Tyman
AU - Martin-Fernandez, Josep-Antoni
AU - Hron, Karel
AU - Maher, Carol
AU - Lewis, Lucy
AU - Olds, Tim
PY - 2019/3/1
Y1 - 2019/3/1
N2 - 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.
AB - 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.
KW - compositional data
KW - Isotemporal substitution
KW - physical activity
KW - sedentary behaviour
KW - sleep
KW - time use
UR - http://www.scopus.com/inward/record.url?scp=85042110183&partnerID=8YFLogxK
U2 - 10.1177/0962280217737805
DO - 10.1177/0962280217737805
M3 - Article
SN - 0962-2802
VL - 28
SP - 846
EP - 857
JO - Statistical Methods in Medical Research
JF - Statistical Methods in Medical Research
IS - 3
ER -