Purpose: Multiple regression equations that estimate the maturity offset for peak height velocity (PHV) have been used in studies regarding adolescents. However, to estimate the maturity of a Japanese population with characteristic proportions, a multiple regression equation developed using a sample of Japanese adolescents is necessary. This study aimed to develop a multiple regression equation that estimates the maturity offset for PHV that can be used for Japanese youth. Methods: Morphometry data of individuals (207 males and 209 females) aged 6 to 18 years were collected. Age at PHV was calculated from the change in the height of each individual, and a multiple regression equation was developed using morphometric data at each age (height, sitting height, lower limb length, and weight) and chronological age. The newly-developed multiple regression equation was compared with a previously-reported equation to determine if it is suitable for Japanese youth. Results: The coefficient of determination (R2) of the multiple regression equation was 0.948 for boys and 0.930 for girls. The differences between the estimated and measured maturity offsets obtained from the multiple regression equation in this study were −0.09 ± 0.81 years for boys and −0.28 ± 0.95 years for girls. In contrast, the differences between the estimated and measured maturity offsets obtained in previous studies were −1.25 ± 1.17 years for boys and −3.40 ± 1.59 years for girls. Conclusion: The newly-developed multiple regression equation is more accurate than previously-reported equations and accurately estimates the maturity offset of Japanese youth in a reliably and practically.
This study investigated the association between nutritional intake and indices of muscle mass or strength in 104 female Japanese university students who participated in sports activities during their junior and senior high school periods and had a high current physical activity level (PAL). Body composition was measured by the bioelectrical impedance method, and appendicular muscle mass (AMM) and skeletal muscle mass index (SMI) were evaluated as muscle mass. PAL was estimated using a factorial method and nutritional intake status was investigated using a food frequency questionnaire based on food groups (FFQg). Grip strength was measured as an index of muscle strength. According to the criteria for diagnosis of sarcopenia, four of the participants had low muscle mass and one also had low grip strength. Although there were no significant differences in body size or grip strength between participants with a high versus low SMI, participants with a low SMI had a significantly higher percentage of body fat (27.7 ± 4.7% vs. 23.3 ± 4.1%), and significantly lower AMM (16.0 ± 1.4 kg vs. 20.6 ± 1.5 kg), total energy intake (1770.4 ± 386.5 kcal/d vs. 2017.1 ± 389.9 kcal/d), and protein intake (57.3 ± 15.0 g/d vs. 67.0 ± 14.2 g/d), as well as a tendency to have a significantly lower carbohydrate intake (239.6 ± 49.3 g/d vs. 268.1 ± 54.4 g/d), than those with a high SMI. These results indicate that even some female university students with a high PAL have a lower muscle mass and might have a low dietary intake, mainly protein and carbohydrate. The results of multiple regression analysis of AMM, SMI, or grip strength with PAL and nutrient intake revealed that PAL and total energy intake or protein intake were significantly and positively associated with muscle mass and strength. These results suggest that a high PAL as well as total energy intake and protein intake among the macronutrients contribute to high muscle mass and muscle strength in young women.