When the outcome is compositional: A method for conducting compositional response linear mixed models for physical activity, sedentary behaviour and sleep research
Aaron Miatke, Ty Stanford, Tim Olds, Francois Fraysse, Carol Maher, Josep Antoni Martin-Fernandez, Dot Dumuid
TL;DR
This paper introduces a new statistical method to analyze how time is allocated among sleep, sedentary behavior, and physical activity in health research.
Contribution
A practical framework for compositional multivariate-response linear mixed models to analyze 24h movement-behavior composition.
Findings
The method accounts for covariances across and within response variables at multiple levels.
Results are invariant to the chosen log-ratio basis for constructing response variables.
The approach is demonstrated in a study on how children reallocate time across the school year.
Abstract
Time use is compositional in nature because time spent in sleep, sedentary behaviour and physical activity will always sum to 24 h/day meaning any increase in one behaviour will necessarily displace time spent in another behaviour(s). Given the link between time use and health, and its modifiable nature, public health campaigns often aim to change the way people allocate their time. However, relatively few studies have investigated how movement-behaviour compositions change longitudinally (with repeated measures), due to experimental design elements (e.g., intervention effects), or differences due to participant socio-demographic characteristics (e.g., sex, socio-economic status) within clustered sampling designs. This may be because most mixed-model packages that account for the random effects do not natively support a multivariate outcome such as movement-behaviour composition. In the…
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Taxonomy
TopicsPhysical Activity and Health · Psychometric Methodologies and Testing · Obesity, Physical Activity, Diet