The contribution of anthropometric characteristics to performance scores in elite female gymnasts.
BACKGROUND
Aims of this study were: a) to identify anthropometric variables correlated with gymnastic performance, and b) to predict performance scores from a combination of anthropometric dimensions.


METHODS



METHODS
correlational analysis and a stepwise multiple regression were used.


METHODS
Subjects were participants at the 24th World Championships Artistic Gymnastics, Rotterdam, The Netherlands, in 1987.


METHODS
A total of 168 female gymnasts (mean age: 16.5 +/- 1.8 years) were investigated. Each gymnast participated in all events.


METHODS
An extensive battery of anthropometric dimensions was taken on each athlete. The somatotype was estimated. Skeletal maturation of the hand-wrist was assessed. Competition scores for the four individual gymnastic events (balance beam, floor exercise, vault, uneven bars) and a composite score for each gymnast were the dependent variables.


RESULTS
Moderately high, significant correlations (p < 0.01) were observed between skinfolds and endomorphy, and gymnastics performance scores, r varying from -0.38 to -0.60, for biceps skinfold and the score on balance beam, and for endomorphy and the total score, respectively. The correlations suggest that gymnasts with more subcutaneous fat and higher endomorphy have lower performance scores. About 32% to 45% of the variance in gymnastic performance scores could be explained by anthropometric dimensions and/or derived variables, but endomorphy and chronological age are the most important predictors.


CONCLUSIONS
There is a relatively strong relationship between several anthropometric variables and gymnastic performance in a sample of elite female gymnasts, but the associations are not sufficiently high to predict performance scores on an individual basis.
Claessens
A L
AL
Department of Kinesiology, Katholieke Universiteit Leuven, Belgium.
Lefevre
J
J
Beunen
G
G
Malina
R M
RM
D000293:Adolescent; D000886:Anthropometry; D005260:Female; D006173:Gymnastics; D006801:Humans; D012044:Regression Analysis; D013008:Somatotypes; D013647:Task Performance and Analysis