Cross-sectional associations between sleep duration, sedentary time, physical activity, and adiposity indicators among Canadian preschool-aged children using compositional analyses

Mark S Tremblay,Valerie Carson,Sebastien F M Chastin

doi:10.1186/s12889-017-4852-0

Abstract

BackgroundSleep duration, sedentary behaviour, and physical activity are three co-dependent behaviours that fall on the movement/non-movement intensity continuum. Compositional data analyses provide an appropriate method for analyzing the association between co-dependent movement behaviour data and health indicators. The objectives of this study were to examine: (1) the combined associations of the composition of time spent in sleep, sedentary behaviour, light-intensity physical activity (LPA), and moderate- to vigorous-intensity physical activity (MVPA) with adiposity indicators; and (2) the association of the time spent in sleep, sedentary behaviour, LPA, or MVPA with adiposity indicators relative to the time spent in the other behaviours in a representative sample of Canadian preschool-aged children.MethodsParticipants were 552 children aged 3 to 4 years from cycles 2 and 3 of the Canadian Health Measures Survey. Sedentary time, LPA, and MVPA were measured with Actical accelerometers (Philips Respironics, Bend, OR USA), and sleep duration was parental reported. Adiposity indicators included waist circumference (WC) and body mass index (BMI) z-scores based on World Health Organization growth standards. Compositional data analyses were used to examine the cross-sectional associations.ResultsThe composition of movement behaviours was significantly associated with BMI z-scores (p = 0.006) but not with WC (p = 0.718). Further, the time spent in sleep (BMI z-score: γsleep = −0.72; p = 0.138; WC: γsleep = −1.95; p = 0.285), sedentary behaviour (BMI z-score: γSB = 0.19; p = 0.624; WC: γSB = 0.87; p = 0.614), LPA (BMI z-score: γLPA = 0.62; p = 0.213, WC: γLPA = 0.23; p = 0.902), or MVPA (BMI z-score: γMVPA = −0.09; p = 0.733, WC: γMVPA = 0.08; p = 0.288) relative to the other behaviours was not significantly associated with the adiposity indicators.ConclusionsThis study is the first to use compositional analyses when examining associations of co-dependent sleep duration, sedentary time, and physical activity behaviours with adiposity indicators in preschool-aged children. The overall composition of movement behaviours appears important for healthy BMI z-scores in preschool-aged children. Future research is needed to determine the optimal movement behaviour composition that should be promoted in this age group.

Highlights

Sleep duration, sedentary behaviour, and physical activity are three co-dependent behaviours that fall on the movement/non-movement intensity continuum
The objectives of this study were to examine: 1) the combined associations of the composition of time spent in sleep, sedentary behaviour, light-intensity physical activity (LPA), and moderate- to vigorous-intensity physical activity (MVPA), with adiposity indicators; and 2) the association of the time spent in sleep, sedentary behaviour, LPA, or MVPA with adiposity indicators relative to the time spent in the other movement behaviours in a representative sample of Canadian preschool-aged children
LPA light-intensity physical activity, MVPA moderate- to vigorous-intensity physical activity, Sedentary time (SB) sedentary time significantly associated with body mass index (BMI) z-score (p = 0.006) but not with waist circumference (p = 0.718)

Summary

Introduction

Sedentary behaviour, and physical activity are three co-dependent behaviours that fall on the movement/non-movement intensity continuum. Recent research suggests there is no single monitoring device that can accurately capture all movement behaviours in the field [2]; technology continues to evolve and advance at a rapid pace in this area Another challenge is utilizing appropriate analytical methods to examine the associations between movement behaviours and health. Unlike traditional statistical techniques, which use open space (i.e., orthonormal) geometry where continuous numerical data can vary from negative infinity to positive infinity, compositional analyses deal with co-dependent data by using closed space (i.e., simplex) geometry where data are constrained (e.g., 24-h period) [4] This eliminates collinearity problems and deals with the co-dependence between time spent in different movement behaviours

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