Structure of intra- and intergroup relationships among key parameters of physical development, physical fitness, and biological age in students aged 17–20

Background and Study Aim. The complex interrelations between physical development, physical fitness, and biological age can serve as important indicators for optimizing physical education programs and monitoring age-related changes in students. The aim of this study is to investigate the structure o...

Full description

Saved in:
Bibliographic Details
Main Authors: Oleksandr Pryimakov, Marek Sawczuk, Georgiy Korobeynikov, Stanislav Prysiazhniuk, Anatoly Skrypko, Nataliya Mazurok
Format: Article
Language:English
Published: IP Iermakov S.S. 2025-06-01
Series:Physical Education of Students
Subjects:
Online Access:https://sportedu.org.ua/index.php/PES/article/view/2287
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Background and Study Aim. The complex interrelations between physical development, physical fitness, and biological age can serve as important indicators for optimizing physical education programs and monitoring age-related changes in students. The aim of this study is to investigate the structure of intra- and intergroup relationships among the leading parameters of physical development, physical fitness, and biological age in students aged 17–20. Material and Methods. The study involved 153 students of the National Technical University aged 17–20, including 79 males and 74 females. Indicators from three sets related to students’ physical condition (PC) were recorded: physical development (PD), physical fitness (PF), and both chronological and biological age (BA). Methods of correlation, variance, regression, and canonical analysis were applied to process the experimental data. Results. The analysis of the interaction between variables of the three PC sets in students revealed that: a) there is a strong and roughly equal mutual positive influence between PD and PF variables; b) as PD and PF parameters increase, so do BA indicators, and vice versa: an increase in BA correlates with a higher level of PD and PF in students; c) the influence of PD and PF variables on BA indicators is more pronounced than the reverse impact of canonical BA variables on PD and PF variables. It was established that: a) 66.8% of the total variability in PF indicators and 69.21% in BA indicators is conditioned by the influence of PD variables; b) 68.3% of the total variability in PD indicators and 77.05% in BA indicators is due to the influence of the group of PF variables; c) 58.6% of the total variability in PF indicators and 50.19% in PD indicators is explained by the influence of the group of BA variables. In all cases, the relationships described demonstrated a high level of statistical significance. In the total variability of the variables of each set of students' PC, the most variable parameters were identified: a) in the group of PD parameters - variables of body fat volume and water content; b) in the group of PF parameters - variables of right and left hand muscle strength, strength index, and strength endurance; c) in the group of BA parameters - indicators of actual, proper BA, and the degree of aging. The increase in right and left hand muscle strength, strength endurance, fat mass volume, and body water content occurs in parallel with the increase in the actual BA and the degree of aging of 17–20-year-old students. Conclusions. As a result of the study, a comprehensive characterization of the relationship structure among PD, PF, and BA indicators of students was provided, including: a) pairwise intra- and intergroup relationships among individual indicators; b) intra- and intergroup relationships between variable sets and individual variables; c) intergroup relationships among different variable sets. Graphical and mathematical models reflect the structure of the relationships between PC parameters in students aged 17–20, as well as the cumulative and partial effects of key variables from the studied PC sets on dependent, highly variable indicators. These models can be used to forecast student PC variables depending on the possible variants of the ratio, share, cumulative, and interacting influence of the indicators of the developed models.
ISSN:2308-7250