The Relationship between Body Composition and Physical Fitness Parameters in Children
Bibliographic record
Abstract
The aim of this study is to analyze the relationship between body composition and physical fitness parameters in children. 286 male and 311 female students have voluntarily participated in the study. Data on body composition have been obtained through the measurements of the students’ height, body weight, BMI, body fat percentage, length (sitting height, arm length, forearm length, leg length, thigh lengths), circumference (elbow, shoulder, biceps (flexion) , buttock, knee, waist, calf, ankle). For somatotype characteristics, the Heat-Carter somatotype grading method has been used. The Sit-Reach Flexibility Test (cm) has been used to determine the characteristic of flexibility; the 20 m. Speed Test (seconds) to determine speed; the 20 m. Sit-up test to determine endurance; Takkei hand dynamometer to determine right-left hand grip strength; Takkei back and lift dynamometer for leg strength and the Flamingo Balance Test for balance have been used. In the analysis of data, the SPSS 16 software has been used and T test and Pearson correlation test have been carried out (p<0.05). Between the body composition and physical fitness parameters of female and male students, a statistically significant relationship has been found with the exception of age, arm and waist measurements (p<0.05). In both genders, positive or negative relationships have been found between height, circumference measurements and somatotype characteristics and performance tests (p<0.05). It was found that there is a negative or positive relationship between the heights, circumference measurements and somatotype characteristics and their strength, endurance, speed, flexibility and balance characteristics of female and male children aged 10-12. As a result, it has been seen that the body composition of children aged 10-12 affects the physical fitness parameters. Children in this age group which is both a period of growth and development and skills selection period for numerous sports branches should regularly be followed by their physical education teachers, anthropometric measurements and performance tests should be carried out and the children should be directed towards suitable sports branches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".