Associations Among School Day Sedentary Behavior, Physical Activity, and Motor Skills: A Compositional Data Analysis

Abstract

PURPOSE: A novel analytic approach, Compositional Data Analysis (CoDa), has recently been used to analyze physical activity data. CoDa assumes co-dependence among physical activity compositional parts within a time-constrained data analytic framework, which makes it appropriate for assessing and analyzing physical activity behavior during school hours. The purpose of this study was to examine the relationships among school day sedentary times (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) with gross motor skills in children using Compositional Data Analysis (CoDa). METHODS: Participants were 409 children (Mean age = 8.4±1.8 years) recruited across five low-income schools. Gross Motor Skills were assessed using the Test of Gross Motor Development - 3rdEdition (TGMD-3) and physical activity was assessed using accelerometers. Isometric Log Ratio coordinates (ILRs) were calculated quantifying the relative proportion of percent of the school day (%) spent in SED, LPA, and MVPA. The associations of the ILRs with the TGMD-3 scores were estimated using general linear mixed effects models adjusted for age, BMI, and estimated VO2Peak. RESULTS: A higher proportion of the school day spent in %MVPA relative to %SED and %LPA significantly associated with higher TGMD-3 total scores (γMVPA= 14.44, P= 0.012). This relationship was also observed for the ball skills subtest scores (γMVPA= 16.12, P= 0.003). A 5% reallocation in % of time spent in SED and LPA to MVPA was independently associated with a 0.48 and 1.74-point increase in ball skills scores, respectively, after controlling for the potential confounders of age, BMI, and estimated VO2Peak. CONCLUSIONS: Replacing %SED and %LPA with %MVPA during school hours may an effective strategy for improving gross motor skills, specifically ball skills, in low-income elementary school-aged children.