Physical Fitness Percentiles of German Children Aged 9-12 Years: Findings from a Longitudinal Study

被引:58
|
作者
Golle, Kathleen [1 ]
Muehlbauer, Thomas [1 ]
Wick, Ditmar [2 ]
Granacher, Urs [1 ]
机构
[1] Univ Potsdam, Res Focus Cognit Sci, Div Training & Movement Sci, Potsdam, Germany
[2] Univ Appl Sci Sport & Management, Potsdam, Germany
来源
PLOS ONE | 2015年 / 10卷 / 11期
关键词
CARDIORESPIRATORY FITNESS; METABOLIC RISK; FIELD-TESTS; LMS METHOD; VALUES; ADOLESCENTS; PERFORMANCE; STRENGTH; GROWTH; POWER;
D O I
10.1371/journal.pone.0142393
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background Generating percentile values is helpful for the identification of children with specific fitness characteristics (i. e., low or high fitness level) to set appropriate fitness goals (i. e., fitness/ health promotion and/or long-term youth athlete development). Thus, the aim of this longitudinal study was to assess physical fitness development in healthy children aged 9-12 years and to compute sex-and age-specific percentile values. Methods Two-hundred and forty children (88 girls, 152 boys) participated in this study and were tested for their physical fitness. Physical fitness was assessed using the 50-m sprint test (i. e., speed), the 1-kg ball push test, the triple hop test (i. e., upper-and lower-extremity muscular power), the stand-and-reach test (i. e., flexibility), the star run test (i. e., agility), and the 9-min run test (i. e., endurance). Age-and sex-specific percentile values (i. e., P-10 to P-90) were generated using the Lambda, Mu, and Sigma method. Adjusted (for change in body weight, height, and baseline performance) age-and sex-differences as well as the interactions thereof were expressed by calculating effect sizes (Cohen's d). Results Significant main effects of Age were detected for all physical fitness tests (d = 0.40-1.34), whereas significant main effects of Sex were found for upper-extremity muscular power (d = 0.55), flexibility (d = 0.81), agility (d = 0.44), and endurance (d = 0.32) only. Further, significant Sex by Age interactions were observed for upper-extremity muscular power (d = 0.36), flexibility (d = 0.61), and agility (d = 0.27) in favor of girls. Both, linear and curvilinear shaped curves were found for percentile values across the fitness tests. Accelerated (curvilinear) improvements were observed for upper-extremity muscular power (boys: 10-11 yrs; girls: 9-11 yrs), agility (boys: 9-10 yrs; girls: 9-11 yrs), and endurance (boys: 9-10 yrs; girls: 9-10 yrs). Tabulated percentiles for the 9-min run test indicated that running distances between 1,407-1,507 m, 1,479-1,597 m, 1,423-1,654 m, and 1,433-1,666 m in 9-to 12-year-old boys and 1,262-1,362 m, 1,329-1,434 m, 1,392-1,501 m, and 1,415-1,526 m in 9-to 12-year-old girls correspond to a "medium" fitness level (i. e., P-40 to P-60) in this population. Conclusions The observed differences in physical fitness development between boys and girls illustrate that age- and sex-specific maturational processes might have an impact on the fitness status of healthy children. Our statistical analyses revealed linear (e. g., lower-extremity muscular power) and curvilinear (e. g., agility) models of fitness improvement with age which is indicative of timed and capacity-specific fitness development pattern during childhood. Lastly, the provided age-and sex-specific percentile values can be used by coaches for talent identification and by teachers for rating/ grading of children's motor performance.
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