The purpose of the study was to investigate the relationships between VO2(subscript max) among anthropometrical and physiological variables, including age, body height, weight, body composition, sub-maximal intensity exercise, and work rate. There were Ill males participated in this study, the average age, body height and weight were 29.63 ± 10.16 years, 171.20 ± 5.53cm, 69.04 ± 8.24kg,respectively. All subjects performed a maximal oxygen uptake testing and anthropometrical measurements. The physiological measurements were examined maximal cycling exercise and anthropometry, in which included percent body fat, and skinfold thickness. Heart rate and oxygen intake variables were measured during the experimental period. Anthropometrical data were recorded for data analysis. The findings of this study included that there was a significant relationship among VO2(subscript max), anthropometrical and physiological variables(r=-.71~7.8; p<.01). By the multiple regression analysis results, we established eleven maximal oxygen uptake predicted equations(R^2 =.49~.82, p<.0l). Those equations can be recommended to estimate VO2(subscript max) for normally active health subjects. According to those results of this study, the predicated equations can be classified as valid and reliable models for VO2(subscript max) prediction. The contribution of this study was to applie to estimate the physical-related fitness and the reference of planning exercise-training prescription for normally active health group.
The purpose of the study was to investigate the relationships between VO2(subscript max) among anthropometrical and physiological variables, including age, body height, weight, body composition, sub-maximal intensity exercise, and work rate. There were Ill males participated in this study, the average age, body height and weight were 29.63 ± 10.16 years, 171.20 ± 5.53cm, 69.04 ± 8.24kg,respectively. All subjects performed a maximal oxygen uptake testing and anthropometrical measurements. The physiological measurements were examined maximal cycling exercise and anthropometry, in which included percent body fat, and skinfold thickness. Heart rate and oxygen intake variables were measured during the experimental period. Anthropometrical data were recorded for data analysis. The findings of this study included that there was a significant relationship among VO2(subscript max), anthropometrical and physiological variables(r=-.71~7.8; p<.01). By the multiple regression analysis results, we established eleven maximal oxygen uptake predicted equations(R^2 =.49~.82, p<.0l). Those equations can be recommended to estimate VO2(subscript max) for normally active health subjects. According to those results of this study, the predicated equations can be classified as valid and reliable models for VO2(subscript max) prediction. The contribution of this study was to applie to estimate the physical-related fitness and the reference of planning exercise-training prescription for normally active health group.