Determining the influence of anthropometric indices on balance parameters in young female gymnasts

Background and Study Aim. It is increasingly important to know the influence of age characteristics on the development of motor skills necessary for gymnastics. Currently, this influence is taken into consideration in the training of young female gymnasts. This study aims to determine the anthropometric indices impact on static and dynamic balance parameters in young female gymnasts. Material and Methods. A group of 24 young gymnasts, from the Arad Municipal Sports Club of Romania, participated in this study. The athletes, aged 6-10 years, were divided into two groups: G1 (6-8 years, n=17) and G2 (9-10 years, n=7). Anthropometric indices were measured by means of Tanita scale. The following indices were monitored: Height (cm), Weight (kg), FATP (%), FATM (kg), FFM (kg), BMI (kg/m2). Balance was evaluated with the Sensamove MiniBoard platform. There were used tests as follows: Static Bipedal Balance (SBB), Lateral Bipedal Balance (LBB) and Vertical Bipedal Balance (VBB). Measured parameters: performance (%); front and back inside (LBB, %); left and right inside (VBB, %); front and back avg. deviation (grade); left and right avg. deviation (degrees). The influence of anthropometric indices on balance parameters was determined using Pearson correlation coefficient. Results. The comparative analysis between groups highlights: average age; relation between weight and height; values of body composition indices. The comparative analysis shows better performances by 2.23% in G1 at SBB and values smaller by 0.35 degrees at average vertical deviations. LBB has better performances in G1 by 10.05% and higher values by 1.79% at keeping inside the vertical space. There is a smaller difference between Confidence Limit of Mean (CLM). As for VBB, the performances are better by 0.41% in G2, keeping inside the space to the left in G1 and to the right in G2. The correlation analysis regarding SB reveals 20% strong connections, 83.3% positive connections with performance and 45.8% negative ones with average deviations in G1. The following were noticed in G2: lack of strong connections, 33.3% positive connections and 25% negative influences. In terms of LBB, G1 has no strong connections, but it has 72.2% positive connections and 45.8% negative connections. G2 is characterized as follows: 7.1% strong connections, absence of positive connections, 75% - negative connections. VBB presents the following values in G1: 28.6% - strong connections and 45.8% - negative connections. G2