Compositional data analysis in physical activity and health research: looking for the right balance

The time spent in different types of sleep, sedentary behaviour and physical activity during a day represents compositional data. Previous use of compositional analysis of daily activity data through orthonormal log-ratio coordinates in the form of pivot coordinates of four components (sleep, sedentary behaviour, light physical activity, moderate to vigorous physical activity) has facilitated critical comparison with and the resolution of contradicting reports of the influence of daily behaviour on health which had arisen from the use of standard statistical analysis. For example, there has been a long-standing debate about whether the effects of time spent sedentary are independent of the time spent in moderate to vigorous activity. However, daily activity may be usefully broken down into more categories, and other compositional analysis approaches may be relevant. Here we demonstrate the use of log-ratio balances to evaluate the association between daily activity broken into six components (sleep, short periods of sedentary behaviour, long periods of sedentary behaviour, standing, slow walking and fast walking) from a nationally representative sample of adults with health markers in obesity, lipidemia and glycemia. The balanced approach to compositional analysis of daily behaviour patterns offers a way to focus the statistical assessment and modelling on variables, representing meaningful contrasts of interest between behaviours. This is fully consistent with the view that actual effects on health are associated with exchanges between some classes of daily behaviours.