Model characteristics of the structure and interrelations of integral parameters of students' physical condition

Abstract

Background and Study Aim. Understanding the physical condition parameters of students during physical education classes is essential in the context of modern education. This understanding contributes to the development of effective teaching strategies tailored to the specific needs of this demographic. The aim of the study is to investigate the structure and interrelations of physical condition (PC) parameters of students aged 17-19 years in the process of physical education classes. Material and Methods. The study involved 153 students aged 17-19 years old, and their physical development, functional, and physical fitness indices were recorded. The study analyzed intra- and intergroup correlations among 55 physical condition (PC) indices. It examined the correlations among integral components of students' structure, including somatic health (SH), adaptation potential (AP), aerobic physical work capacity (APWC), and biological age (BA). The study utilized factor analysis, correlation analysis, dispersion analysis, and regression analysis to examine the relationships and patterns within the collected data. Results. The analysis of intra- and intergroup relationships among the studied parameters revealed that the structure of physical condition (PC) is consistent between girls and boys. There are close linear dependencies, similarities, and differences in the interrelations of integral PC parameters, including somatic health (SH), adaptation potential (AP), aerobic physical work capacity (APWC), and biological age (BA), between boys and girls. The regression model coefficients indicate that for both genders, SH is influenced by APWC and AP. In girls, AP is dependent on SH and BA, while in boys, AP depends on SH, BA, and APWC. A strong relationship between APWC and resting heart rate (HR) was identified during testing, with boys demonstrating higher levels of APWC at lower initial HR values compared to girls. Conclusions. The study has provided valuable insights into the key components of the physical condition (PC) structure among 1st-year students. These components encompass physical development, adaptation potential, health, cardiorespiratory system functional capacities, speed-strength fitness, biological age, and degree of aging. Findings emphasize the significance of resting bradycardia as an informative marker and criterion for assessing APWC during moderate-intensity muscle activity. The developed mathematical models have proven effective in modeling and predicting students' PC, including the individual integral components (SH, AP, APWC, and BA). These models provide valuable tools for anticipating potential changes in these parameters.

Interrelations of physical state parameters and biological age of students in the process of physical education

“…One of our previous publications presents experimental material reflecting the interrelations of BA with the level of somatic health, physical work capacity, adaptation potential, i.e., integral parameters of the FS of the students' body [6]. However, both in our publication and those of a number of authors [2,5], the partial and total influence of individual FS parameters on students' BA is inadequately treated.…”

“…The biological age (BA) of students serves as an integral marker of their physical state (PS) and plays a crucial role in assessing body ontogenetic maturity, individual development, aging rates, and overall health status [1,2,3]. Numerous studies by various authors have highlighted the interconnectedness of BA with aerobic physical work capacity [4,5,6], somatic health [7,8], adaptation potential, and functional reserves of the human body [6,9,10]. Additionally, BA is influenced by physical development [11,12] and regular physical activity [8], both of which are integral components of human functional state (FS).…”

“…It is equally important to assess the extent of their partial and overall impact on BA, as well as the relationship between BV and the ratios and interrelations of the complex set of key parameters of human FS [6,8]. This necessitates the utilization of complex mathematical processing and analysis methods, such as multiple stepwise regression and analysis of variance [25].…”

“…In order to reveal the mechanisms of BA interaction, it is important to use, along with complex diagnostic methods, various methods of mathematical processing of multimodal information: multiple correlation, regression, factor, dispersion, and other statistical methods [6,25]. To determine BA, in the works of the majority of researchers relatively simple methods of biological parameters statistical processing were used [8,27].…”

“…The impact of different forms of motor activity, including sports activities, on BA, health status, aging, and life expectancy of an individual has been underinvestigated in the publications of researchers who have dealt with this problem [2,5]. Even though many publications confirm the important role of regular motor activity in reducing BA, improving somatic health, and increasing functional reserves of young people [5,6], they neither adequately treated the interrelationships of BA with somatic and vegetative parameters, nor identified the key FS indices and their interrelationships that determine the BA of men and women of different, including student, ages.…”