Wyniki wyszukiwania - Biblioteka Nauki

Nowa wersja platformy, zawierająca wyłącznie zasoby pełnotekstowe, jest już dostępna.
Przejdź na https://bibliotekanauki.pl

Ograniczanie wyników

Znaleziono wyników: 3

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: anthropometric variables

Sortuj według:

Ogranicz wyniki do:

Profile of young handball players by playing position and determinants of ball throwing velocity

100%

Zapartidis I. , Kororos P. , Christodoulidis T. , Skoufas D. , Bayios I.

Journal of Human Kinetics

2011

tom 27

17-30

This study defined the differences in physical qualities and anthropometric characteristics among playing positions in young male handball players, and investigated the relationship between ball throwing velocity and all measured parameters.182 young male handball players, aged 14.3yrs, with playing experience of 4.5yrs, were classified as: back players, centre backs, pivots, wing players, and goalkeepers. Body height, body mass, BMI, arm span, hand length, standing long jump, 30m sprint, flexibility, VO2max and throwing velocity were measured.Significant differences were detected among individual positions for all measured variables, except for flexibility. Backs were tallest, while pivots showed the largest arm span and hand length. Wings were shortest, with the lowest weight and BMI. Backs and wings performed best in the standing long jump, 30m sprint, flexibility and VO2max. Goalkeepers underperformed in all motor abilities. Ball velocity significantly correlated to all variables except for BMI and flexibility. Anthropometric and physical differences exist among different positions in young male handball players. These parameters influence ball velocity.The findings suggest that a high performance level requires advanced physical qualities as well as anthropometric features for these ages, and coaches should apply specific training programs for each playing position.

Height and Body Composition Determine Arm Propulsive Force in Youth Swimmers Independent of a Maturation Stage

88%

Moura T. , Costa M. , Oliveira S. , Júnior M. B. , Ritti-Dias R. , Santos M.

Journal of Human Kinetics

2014

tom 42

nr 1

277-284

The aim of this study was to examine the relationship between anthropometric variables, body composition and propulsive force in swimmers aged 9-17 years. Anthropometric characteristics (body height and mass, sitting height, arm span, arm muscle area and body composition) and the propulsive force of the arm (tethered swimming test) were evaluated in 56 competitive male swimmers. Tanner’s stages of genital maturation (P1-5) were used. The data analysis included correlations and multiple linear regression. The propulsive force of the arm was correlated with body height (r = 0.34; p =0.013), arm span (r = 0.29; p =0.042), sitting height (r = 0.36; p =0.009), % body fat (r = 0.33; p =0.016), lean body mass (r = 0.34; p =0.015) and arm muscle area (r = 0.31; p =0.026). Using multiple linear regression models, the percent body fat and height were identified as significant predictors of the propulsive force of the arm after controlling for the maturation stage. This model explained 22% (R2 = 0.22) of associations. In conclusion, the propulsive force of swimmers was related to body height and percent body fat

Anthropometric Variables and PEFR

88%

Chandel R. , Shivhare G. , Bhagat A.

Central European Journal of Sport Sciences and Medicine

2022

tom 39

75-80

Peak expiratory flow rate (PEFR) varies with anthropometric variables like calendar age, body height, body weight, and body surface area in different regions. The present study aims at analyzing the relationship of PEFR with anthropometric variables to know a reference value in this region. We conducted the present study on healthy adult males aged eighteen to forty-five years engaged in works where they were un-exposed to pollutants in Patiala, India. Subgroups were made in each anthropometric variable category. PEFR recording was done using Mini Wright Peak Flow Meter. Results are expressed as mean PEFR ± standard deviation (mean ± S.D.), while the students' t-test was used to determine the differences between the means. We observed a linear increase in PEFR with all anthropometric variables. The correlation of PEFR with anthropometric variables was determined. PEFR is positively correlated with body height and body surface area (r =+0.20) and negatively correlated with calendar age (r = - 0.24) and body weight (r = - 0.02). We conclude that PEFR correlates best with body height (r = +0.48), and the result is highly significant (p < 0.01).