DOI: 10.3886/e208741v1
title: Associations between Structured and Unstructured Activities in the Kindergarten on Children's Physical Fitness: A Compositional and Isotemporal Substitution Analysis

description: <b>Objective: </b>To adopt video observation and acceleration sensors
to measure structured and unstructured activity behaviors in kindergartens, and
to explore their relationship with children's physical fitness and the
isotemporal substitution effects on children's physical fitness using
compositional data models. 

<b>Methods: </b>Based on the principles of informed consent and
voluntariness, 358 children aged 3-6 years were recruited. Video observation,
the ActiGraph GT3X-BT acceleration sensor, and the "Evaluation Criteria
for Structured and Unstructured Physical Activity in Children" were used
to collect compositional data on nine in-kindergarten activity behaviors,
including S-SB (Structured Sedentary Behavior), S-LPA (Structured Light
Physical Activity), S-MVPA (Structured Moderate-to-Vigorous Physical Activity),
US-SB (Unstructured Sedentary Behavior), US-LPA (Unstructured Light Physical
Activity), US-MVPA (Unstructured Moderate-to-Vigorous Physical Activity), and
D-SP (Daytime Sleep). Physical fitness indicators of the children were
measured, and compositional data and isotemporal substitution analyses were
performed using R Studio (Version 4.2). 

<b>Results:</b> S-MVPA has a positive relationship with children's
body shape, physical fitness and total physical fitness score (P&lt;0.05).
US-LPA has a positive relationship with children's physical fitness
(P&lt;0.05), while S-LPA has a negatively correlated (P&lt;0.05). When S-MVPA
replaced S-LPA and S-SB for 10 minutes of equal time, children's body shape,
physical fitness, and total physical fitness scores significantly increased,
with the total physical fitness score increasing by 2.11 points and 1.29
points, respectively. The effect size increased with the substitution time.
Similarly, when US-LPA replaced S-LPA and S-SB for equal time, children's total
physical fitness scores also significantly increased. 

<b>Conclusion: </b>S-MVPA can effectively enhance children's physical
fitness, while the relationship between S-LPA and children's physical fitness
is opposite to that of US-LPA. Keeping the structured activity time constant,
increasing the relative proportion of MVPA and correspondingly reducing the
proportion of LPA or SB is an effective strategy to optimize children's
physical education programs and improve their physical fitness. On this basis,
isotemporally increasing the time for unstructured LPA can further promote
children's physical fitness improvement.
description: <b>Primary
 index</b>
 
 
 <b>Secondary
 index</b>
 
 
 <b>weight</b>
 
 
 
 
 <b>Body
 shape (30%)</b>
 
 
 Height (cm)
 
 
 0.20
 
 
 
 
 BMI (kg/m2)
 
 
 0.10
 
 
 
 
 <b>Physical
 fitness (70%)</b>
 
 
 Grip (kg)
 
 
 0.10
 
 
 
 
 Standing long jump (cm)
 
 
 0.10
 
 
 
 
 Sit forward bend (cm)
 
 
 0.10
 
 
 
 
 Double hop (s)
 
 
 0.15
 
 
 
 
 15-meter steeplechase (s)
 
 
 0.10
 
 
 
 
 Balance beam (s)
 
 
 0.15
description: Response Rates: 358 preschool children aged 3-6 were randomly stratified and signed informed consent. among which 1 sample was lost in video observation, 4 samples were invalid
in PA test, and 16 samples were missing in physical fitness test. A total of
337 valid samples were obtained, with an effective rate of 94.13% .
description: Presence of Common Scales: "Assessment
Criteria for Structured and Unstructured Physical Activity in Preschool
Children"<br> National
Physical Fitness Testing Standards (revised in 2023)" (children's part)
description: This
study adopted a stratified cluster sampling method and divided the samples into
three strata based on the per capita GDP ranking of cities in Jiangxi Province,
China, in 2021. One city was randomly selected from each stratum, totaling
three cities (Yingtan, Pingxiang, and Ganzhou). Three kindergartens were
selected from each city, totaling nine kindergartens.
description: Preschool children aged 3-6 in Jiangxi, China. Smallest Geographic Unit: Urban
description: coded video observation; cognitive assessment test; other;