ABSTRACT
The relationship between body fat growth and physical fitness and motor ability development in school age children is not well understood. We determined the similarities and differences in body fat growth and physical fitness and motor ability development curves by applying cross correlation functions, and attempted to show the structure of growth and development between these attributes. The subjects were 647 boys aged 7 to 15 years. The measurements were height, weight, body mass index and body fat percentage as physical characters; and 20-m sprint, Pro Agility test, side steps, standing long jump, vertical jump, and rebound jump (RJ) index as physical fitness and motor ability. The wavelet interpolation method was applied to growth and distance values for physique, body fat and physical fitness and motor ability, and growth and development curves were derived. Cross correlation functions were then applied to the respective pairs of the compared velocity curves. There were large changes in the behavior of the growth velocity curve around the take off age for height, and so the relationship between body fat percentage and physical fitness and motor ability was investigated using the respective cross correlation functions around the take off age. Before the take off age, positive correlations were seen between body fat percentage and physical fitness and physical fitness and motor ability except for the RJ index. After the take off age, in contrast, there were negative correlations between body fat percentage and physical fitness and motor ability except for the RJ index. These results show the new finding that after the take off age in boys, there are contrary similarity between body fat and speed, agility, and instantaneous force.
ABSTRACT
In the present study we conducted a regression analysis of age at menarche against Maximum Peak Velocity (MPV) of height in non-athlete Korean girls which was derived with the wavelet interpolation method, and composed linear to quartic regression polynomials to obtain the best regression polynomial. We then applied the age at menarche and age at MPV of height of athletes to the best polynomial regression evaluation, and investigated the validity of a delayed menarche evaluation that we constructed. Moreover, the relation between delayed menarche and menstrual status was examined by investigating delayed menarche and menstrual pain in individuals for the first time. The subjects were 124 second year female students at a physical education high school in the suburbs of Pusan, South Korea. A questionnaire survey of these girls was conducted, from which their date of birth, age at menarche, and athletic activities in elementary, junior high, and high school were obtained. In addition, health check records were examined retrospectively, and longitudinal growth data for height were obtained from the 1st year of elementary school (7 years old) until the second year of high school (17 years old). Next, the same survey as above was also done for second year students at a general high school in the same area, as a control group. Three hundred forty-five non-athletes for whom all data were available were selected. As the results, the third order polynomial was found to be most suitable for the regression polynomial. When it was applied to individual female Korean athletes with respect to the regression evaluation, positive scores were obtained for many athletes and an overall delay in menarche was seen. Delayed menarche was not seen, however, in archery athletes. A strong delay in menarche was thus found in Korean athletes. And it was shown that 80% had moderate or greater menstrual pain and a close relation with menstrual abnormalities, the effectiveness of the delayed menarche evaluation was further validated.
ABSTRACT
A study was conducted to analyze the height growth velocity curve based upon the maturity rate. Ninety-eight longitudinal data points for height (for subjects aged 6 to 17 years) were obtained retrospectively from health examination records in 1983. Growth distance and growth velocity curves of each individual were described by the wavelet interpolation method, and PHV age was determined with the described graph using computer simulation. We classified the growth velocity curve by the maturity rate approximated according to the PHV age. As a result, it was shown that the after-growth spurt in early maturity and somewhat early maturity type appeared more than in the average and somewhat late maturity types, and that conversely, the mid-growth spurt in the late maturity and somewhat late maturity types appeared more than in the early maturity and somewhat early maturity types. Specifically, it was demonstrated that two mid-growth spurts appeared in the late maturity and somewhat late maturity types.