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BACKGROUND: The biological maturity status plays an important role in sports, since it influences the performance level and the talent selection in various types of sport. More mature athletes are favorably selected for regional and national squads. Therefore, the biological maturity status should be considered during the talent selection process. In this context, the relative age effect (RAE), which exists when the relative age quarter distribution of selected sports groups shows a biased distribution with an over-representation of athletes born in the first months after the specific cut-off-date for the competition categories, represents another problem in the talent development. From an ethical point of view, discrimination of young talented kids does exist: the relatively younger athletes have little to no chance of reaching the elite level, despite their talents and efforts. The causal mechanisms behind the RAE are still unclear and have to be assessed. In this context, the biological maturation seems to be a possible influential factor for the existence of a RAE in sport, which has to be examined. Several methods for estimating the biological maturity status exist; however, they are often expensive and not practicable. Consequently, the aim of the present study was to assess the concordance of a simple, yet accurate method of estimating biological maturation (prediction equation of age at peak height velocity, APHV) of Mirwald and co-workers, and the gold standard method of estimating skeletal age (SA, the x-ray of the left wrist). METHODS: In total, 75 Austrian students (40♂, 35♀) aged 10 - 13 years, were examined. Thirty of the participants (17♂, 13♀) were students of a well-known Austrian ski boarding school, and 45 (23♂, 22♀) of a non-sportive secondary modern school of the same region. The participants included in the study had not experienced a rupture of the carpal bones of the left wrist. Parents and participants were informed of the study aims, requirements and risks before providing written informed consent. The study was performed according to the Declaration of Helsinki. The study was approved by the Board for Ethical Questions in Science (Nr.: 2/2014) and the Institutional Ethics Review Boards for Human Research. For the prediction equations, the body height, the body mass and the sitting height were examined 8. The actual CA at time of measurement, and the leg length as the difference between body height and sitting height were calculated. These parameters were used to predict MO as time before or after PHV for boys and girls using the prediction equations of Mirwald et al. 19. According to Malina and Koziel 8, the participants were classified as late, on time (average) or early maturing on the basis of their APHV relative to the sample mean and standard deviation separated by sex. Participants within plus/minus the standard deviation of the mean were considered on time; participants with APHV > mean + standard deviation were classified late, while those with APHV < mean - standard deviation were classified early. An expert in pediatric endocrinology evaluated the x-rays of the left-hand wrist with the Greulich-Pyle-Method for assessing SA, the most widely used method of determining SA 24. The difference between SA and CA were calculated (= difference SA-CA). Consistent with other studies, the participants were divided into three groups according to their maturity status: on time or average maturity status was a SA within ±1 year of CA, late maturating was a SA behind CA of more than 1 year, and early maturating was a SA in advance of CA of more than 1 year 5 19 25. The most accurate method used to compare two methods of measurement is the Bland-Altman plot and the 95 % limits of agreement 26 27 28. Bland-Altman plots of the difference between difference in APHV (from the literature mean) and difference SA-CA (y-axis) and the mean of difference in APHV and difference SA-CA (x-axis) were performed. Approximately 95 % of the points in the plot should lie within the limits; then the concordance between the two methods of measurement is given 28. Additionally, intraclass correlation coefficients (ICC(3,1); two-way-mixed, total agreement) were calculated between difference in APHV and difference SA-CA. Chi²-tests were used to assess the difference in the percentage of pupils classified as on time, early or late maturing between the classifications based on the SA and on APHV, respectively. The level of significance was set at p < 0.05 and for highly significant at p < 0.01. All of the calculations were performed using PASW Statistics V.21.0. RESULTS: Chi²-tests did not show any significant differences (p = 0.404) in the percentage of participants classified as on time, early or late maturing between the two classifications based on SA and on APHV, respectively, neither for the total sample, nor for the two groups ski racers and non-athletes. The Bland-Altman analysis showed that more than 95 % of the points in the plot lie within the limits; consequently, there is concordance between the two methods with regard to estimating biological maturation. The ICC(3,1) statistics showed a highly significant correlation: p = 0.002, ICC (95 % CI) = 0.48 (0.13 - 0.69). CONCLUSIONS: The prediction equations to determine APHV seem to be a valid method of assessing the biological maturity status of youths aged 10 - 13 years. The percentage of pupils classified as on time, early or late maturing did not differ significantly between the classifications based on the two methods. Also the Bland-Altman analysis proved the concordance between the two methods. The RAE could be influenced and strengthened by the biological age in sports in which advantages in maturity parameters are important. Athletes born early in the selection year, who are also at the same time advanced in maturity, might be advantaged in the selection process. However, since the prediction equations seem to be valid, this method can be used in the future in the talent selection process in order to not disadvantage late-maturing athletes, which in turn could result in the reduction of the occurrence of the RAE in various types of sports in the future. In talent selection processes the growth spurt and the implemented changes in proportions between core and the extremities are often not considered; although it was shown that during this period, athletes showed poor performances in physical fitness. Since physical fitness is an important criterion in talent selection processes, athletes who go through their individual peak growth spurt at the time of selection have disadvantages due to the diverse proportions. As a consequence, it seems important to know the athlete's APHV in order to consider the variations in physical performance caused by developmental changes. The prediction equations to determine APHV include the leg length and sitting height in order to consider the diverse proportions between core and extremities; hence, this method seems to be accurate and should be implemented in the talent selection process.
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