Relations between anthropometric parameters and motor skills of the preadolescent female students

Miroljub, Ivanović, Uglješa

Glasnik Antropološkog društva Srbije

52

17

28

1820-7936

10.5937/gads52-12773

http://scindeks.ceon.rs/article.aspx?query=ISSID%26and%2613599&page=0&so...

2017-2021/11/03/11:10:22

The aim of this research was to examine the relations between morphological markers and motor skills of preadolescent female students. In this cross-sectional study, the pertinent sample of N = 162 was represented by V grade elementary school female students (M= .11.24 years, SD= .86), while 16 measuring instruments were used for the evaluation of anthropometric characteristics, and the battery of 7 tests for motor skills evaluation. The findings have revealed that the two groups of the variables manifested are linearly correlated via one statistically significant canonical function which, explains 42% of the common variance proportion. The attained pair of canonical factors in anthropometric space has determined orthogonal linear combinations of the latent dimensions variables (subcutaneous fatty tissue, body voluminosity and body mass, transversal dimensionality of the skeleton and longitudinal dimensionality of the skeleton), while in the motor space it has been determined by the mechanism of female students' motor skills. The results have signaled that the participants who achieved higher scores on the motor skills tests (60 m sprint - crouch start, handstand against a vertical surface, 'scissors' high jump, forward shoulder roll on the dominant side, shot from the mark using basic technique, one-handed standing shot and ball bouncing on fingertips from the middle volleyball position) had lower canonical coefficients in the subcutaneous fatty tissue and body voluminosity measurements, and vice versa. Indicators of redundancy show that motor test variability depends on the variability of the anthropometric measurements, that is to say, that using the system of the anthropometric variables examined one can anticipate 15,23% of common motor variables variance, and using the system of motor variables 19,26% of motor variables variability.