Fitness, fatness and the reallocation of time between children’s daily movement behaviours: an analysis of compositional data

Abstract

BackgroundMovement behaviours performed over a finite period such as a 24 h day are compositional data. Compositional data exist in a constrained simplex geometry that is incongruent with traditional multivariate analytical techniques. However, the expression of compositional data as log-ratio co-ordinate systems transfers them to the unconstrained real space, where standard multivariate statistics can be used. This study aimed to use a compositional data analysis approach to examine the adiposity and cardiorespiratory fitness predictions of time reallocations between children’s daily movement behaviours.MethodsThis study used cross-sectional data from the Active Schools: Skelmersdale study, which involved Year 5 children from a low-income community in northwest England (n = 169). Measures included accelerometer-derived 24 h activity (sedentary time [ST], light physical activity [LPA], moderate-to-vigorous physical activity [MVPA], and sleep), cardiorespiratory fitness determined by the 20 m shuttle run test, objectively measured height, weight and waist circumference (from which zBMI and percent waist circumference-to-height ratio (%WHtR) were derived) and sociodemographic covariates. Log-ratio multiple linear regression models were used to predict adiposity and fitness for the mean movement behaviour composition, and for new compositions where fixed durations of time had been reallocated from one behaviour to another, while the remaining behaviours were unchanged. Predictions were also made for reallocations of fixed durations of time using the mean composition of three different weight status categories (underweight, normal-weight, and overweight/obese) as the starting point.ResultsReplacing MVPA with any other movement behaviour around the mean movement composition predicted higher adiposity and lower CRF. The log-ratio model predictions were asymmetrical: when time was reallocated to MVPA from sleep, ST, or LPA, the estimated detriments to fitness and adiposity were larger in magnitude than the estimated benefits of time reallocation from MVPA to sleep, ST or LPA. The greatest differences in fitness and fatness for reallocation of fixed duration of MVPA were predicted at the mean composition of overweight/obese children.ConclusionsFindings reinforce the key role of MVPA for children’s health. Reallocating time from ST and LPA to MVPA in children is advocated in school, home, and community settings.Electronic supplementary materialThe online version of this article (doi:10.1186/s12966-017-0521-z) contains supplementary material, which is available to authorized users.

Compositional analysis of the associations between 24-h movement behaviours and cardio-metabolic risk factors in overweight and obese adults with pre-diabetes from the PREVIEW study: cross-sectional baseline analysis

“…This has in part been attributed to the relative contribution of each activity behaviour to the daily composition (24 h). For example, a 10-min reallocation represents a substantially larger relative change in MVPA than it does in ST or sleep [4,11,18]. This asymmetry demonstrates that reducing activity levels below the mean had a greater predicted detriment to cardiometabolic risk than the predicted benefit following an equivalent increase above the mean.…”

“…The isometric log-ratio multiple linear mixed models were used to predict cardio-metabolic health measures for the mean daily movement behaviour composition. Predicted values of each cardio-metabolic marker were then calculated for new compositions where fixed durations of time had been reallocated from one movement behaviour to another while the remaining behaviours were kept constant [18]. The new predicted values were then subtracted from the mean composition to find the difference in cardio-metabolic marker after the reallocation of time between behaviours [18].…”

“…Predicted values of each cardio-metabolic marker were then calculated for new compositions where fixed durations of time had been reallocated from one movement behaviour to another while the remaining behaviours were kept constant [18]. The new predicted values were then subtracted from the mean composition to find the difference in cardio-metabolic marker after the reallocation of time between behaviours [18]. Furthermore, a sensitivity analyses was performed to assess whether associations with cardio-metabolic markers differed between long and short sleepers using a median split.…”

“…There is a growing body of evidence supporting the use of compositional data analysis (CoDa) in studies of cardiometabolic risk markers and obesity in both adults [11,17] and children [4,16,18]. In a sample of adults at high risk of type 2 diabetes, Biddle and colleagues [19] found that stepping time was associated with markers of metabolic health relative to sleep, sitting and standing.…”

Utility of international normative 20 m shuttle run values for identifying youth at increased cardiometabolic risk

“…In youth, low CRF levels are associated with unhealthy cardiometabolic risk profiles, albeit weakly (Ekelund et al, 2007). Genetic factors influence the extent to which CRF can be developed (Bouchard, 2012), but recent findings have also demonstrated the mediating effects that moderate-vigorous physical activity (MVPA) (Carson, Tremblay, Chaput, & Chastin, 2016;Fairclough et al, 2017), total sedentary time (Carson et al, 2016) and specific sedentary patterns (Júdice et al, 2017) has upon measures of physical fitness and indicators of cardiometabolic risk. As such, providing opportunities for youth to increase their MVPA and CRF as well as limiting their sedentary behaviour seems prudent to ensure optimal health.…”