Related Experiment Video
Updated: Apr 25, 2026

Physical Activity Measurement in Children Accepting Table Tennis Training
Published on: July 27, 2022
Correlates of sedentary time in children: a multilevel modelling approach
Thayse Natacha Gomes, Fernanda Karina dos Santos, Daniel Santos
1CIFI2D, Faculty of Sport, University of Porto, Rua Dr Plácido Costa, 91, Porto 4200-450, Portugal. jmaia@fade.up.pt.
Background:
Sedentary behaviour (SB) has been implicated as a potential risk factor for chronic disease. Since children spend most of their awake time in schools, this study aimed to identify individual- and school-level correlates of sedentary time using a multilevel approach, and to determine if these correlates have a similar effect in normal weight (NW) and overweight/obese (O/O) children.
Methods:
Sample comprised 686 Portuguese children aged 9-10 years from 23 schools that took part in the ISCOLE project. Actigraph GT3X + accelerometers were used 24 hours/day for 7 days to assess sedentary time (daily minutes <100 counts/min); BMI was computed and WHO cut-points were used to classify subjects as NW or O/O. Sex, BMI, number of siblings, family income, computer use on school days, and sleep time on school days were used as individual-level correlates. At the school level, school size (number of students), percentage of students involved in sports or physical activity (PA) clubs, school promotion of active transportation, and students' access to equipment outside school hours were used. All multilevel modelling analysis was done in SPSS, WINPEPI, and HLM.
Results:
School-level correlates explain ≈ 6.0% of the total variance in sedentary time. Results (β ± SE) showed that boys (-30.85 ± 5.23), children with more siblings (-8.56 ± 2.71) and those who sleep more (-17.78 ± 3.06) were less sedentary, while children with higher family income were more sedentary (4.32 ± 1.68). At the school level, no variable was significantly correlated with sedentary time. Among weight groups, variables related to sedentary time in NW were sex, sleep time and family income, while in O/O sex, number of siblings and sleep time were significant correlates. No school-level predictors were significantly associated in either of the weight groups.
Conclusion:
Notwithstanding the relevance of the school environment in the reduction of children's sedentary time, individual and family characteristics played a more relevant role than the school context in this study.
More Related Videos
06:52Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
Published on: September 17, 2019
05:59Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
Published on: March 7, 2019
Related Concept Videos
Correlations
Longitudinal Studies
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Observational Studies
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...
Mechanistic Models: Compartment Models in Individual and Population Analysis
Longitudinal Research