An examination regarding the velocity curve derived from mean growth distance curve in male student's physique

DOI Web Site Web Site 8 Citations

Bibliographic Information

Other Title
  • 男子体格の平均発育曲線から導き出される速度曲線の解析
  • ダンシ タイカク ノ ヘイキン ハツイク キョクセン カラ ミチビキダサレル

Search this article

Description

This study is designed to determine Maximum Peak Velocity age (MPV) and examine the relationship between the MPV ages of height and other physique (body mass, chest girth, sitting height and leg length) in the growth velocity curve which differentiated the mean growth distance curve approximated by the Wavelet Interpolation Method (WIM) in physique. Furthermore analyzed the mid-growth spurt and the after-growth spurt. Ninety-eight longitudinal data of male students aged 6 to 17 years in physique (height, weight, chest girth, sitting height, leg length) were obtained retrospectively from health examination records in 1983. Specifically, the growth curve constracted theoretically based upon the Multiresolution phenomenon (Self-similar phenomenon in the terminology of Fractal) was abstracted as human growth phenomena, and the abstracted growth curve was approximately described as the true growth curve by the WIM. The MPV ages of physique by identified by judging from the growth velocity curve simulated by the WIM, and the sequence in the MPV ages of physique was leg length (11.78), height (12.21), sitting height (12.57), weight (12.60), and chest girth (12.81) in early order of MPV age. Significant (P &lt 0.01) correlations were obtained between the MPV ages of height and other physical measurements. It was shown that differences between the MPV ages of height and physique except height had fixed tendency respectively. The mid-growth spurt was confirmed in the growth velocity curve of weight and chest girth, and the after-growth spurt was confirmed in those of height and leg length. Consequently, it was considered that the after-growth spurt of height was determined by that of leg length.

Journal

Citations (8)*help

See more

Keywords

Details 詳細情報について

Report a problem

Back to top