Predicting VO2max in Children and Adolescents Aged between 6 and 17 Using Physiological Characteristics and Participation in Sport Activities: A Cross-Sectional Study Comparing Different Regression Models Stratified by Gender

Abstract

Background: The aim of this study is to use different regression models to capture the association between cardiorespiratory fitness VO2max (measured in mL/kg/min) and somatometric characteristics and sports activities and making better predictions. Methods: multiple linear regression (MLR), quantile regression (QR), ridge regression (RR), support vector regression (SVR) with three different kernels, artificial neural networks (ANNs), and boosted regression trees (RTs) were compared to explain and predict VO2max and to choose the best performance model. The sample consisted of 4908 children (2314 males and 2594 females) aged between 6 and 17. Cardiorespiratory fitness was assessed by the 20 m maximal multistage shuttle run test and maximal oxygen uptake (VO2max) was calculated. Welch t-tests, Mann–Whitney-U tests, X2 tests, and ANOVA tests were performed. The performance measures were root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). All analyses were stratified by gender. Results: A comparison of the statistical indices for both the predicted and actual data indicated that in boys, the MLR model outperformed all other models in all indices, followed by the linear SVR model. In girls, the MLR model performed better than the other models in R2 but was outperformed by SVR-RBF in terms of RMSE and MAE. The overweight and obesity categories in both sexes (p < 0.001) and maternal prepregnancy obesity in girls had a significant negative effect on VO2max. Age, weekly football training, track and field, basketball, and swimming had different positive effects based on gender. Conclusion: The MLR model showed remarkable performance against all other models and was competitive with the SVR models. In addition, this study’s data showed that changes in cardiorespiratory fitness were dependent, to a different extent based on gender, on BMI category, weight, height, age, and participation in some organized sports activities. Predictors that are not considered modifiable, such as gender, can be used to guide targeted interventions and policies.

Impact of a Nyakaza Move-for-Health Intervention Programme among Adolescents in a Resource-Constrained South African Community

“…This is contrary to a recent research study [ 46 ] which revealed that six weeks of circuit training significantly increased the predicted VO 2 max of adolescents who participated in the intervention programme. Contrary to previous research studies [ 47 , 48 , 49 ], gender and age did not produce any significant influence on the VO 2 max of the treatment group. Therefore, future research should consider larger sample sizes, longer intervention durations, and control for additional confounding variables to better understand the determinants of VO 2 max changes in adolescents.…”

Functional Capacity Training for Improvement of VO2 Max in Football Players: Differences in The Effects of Circuit Training and Interval Training Models

“…The VO2max develops at a faster rate at the ages of 13 to 19 years due to higher levels of growth hormone, compared to individuals over 19 year old. As outlined in the Carayanni et al (2022) study, the growth and hormonal changes that occur during puberty significantly influence the VO2max development, along with other physical fitness parameters. These findings suggest that puberty in males is associated with an improvement in both heart and circulatory system abilities.…”