The purpose of the present study was to examine the distribution of subcutaneous fat and to derive several equations to predict body density (BD) using an amplitude modulation type of ultrasonoscope (A-mode ultrasonoscope, FUKUDA FT-100). Subjects were 188 male physical education major college students ranging in age from 18 to 24 years. Fifty subjects who were randomly selected out of the 188 subjects were measured for BD by the underwater weighing technique and were used to derive the equation for estimating the BD. Four points (scapular, triceps, suprailiac, and thigh) of subcutaneous fat which had been commonly selected, height, and weight were measured. The four measurements of fat for the 188 subjects indicated rather small means and small standard deviations respectively. Further-more, histograms of those measurements tended to show a significant skewness for low values and deviated from the normal probability curve (p<0.01). Regarding the means, they were almost all the same except for suprailiac measurements. Suprailiac measurements showed more large values and were distributed rather more widely than the other measurements. Derivations of the multiple regression equations from anthropometric measurements were made using the Wherry-Doolittle test selection method (Clarke & Clarke, 1972). Four measure-ments (triceps, suprailiac, height, and weight) were selected by the Wherry-Doolittle method. The multiple regression equation based on these four measurements was as follows : BD = 1.03894 - 0.00541 1(X1) - 0.000891 (X2) + 0.000506(X3) - 0.000353(X4) · · · · · · · · · Formula(1) (R= 0.660, SEE= 0.00603) where BD : body density (g/cm³), X1 : triceps(mm). X2 : suprailiac(mm), X3 : height(cm), X4: weight(kg), R : multiple correlation coefficient, and SEE : standard error of estimation. On the other hand, a more simple equation based on only fat measurements was as follows : BD = I .10907 - 0.004085(X1 ) - 0.001295(X2) · · · · · · · · · Formula(2) (R=0.631, SEE=0.00624) Correlation coefficients of these formulas were not sufficiently high and SEES of the formulas were not so small. It was shown that derivation of equation to predict BD with high accuracy was not easy when physical education major students were selected as subjects. However, considering the homogeneous nature of the subjects examined in the present study, the present formula could be expected to be applicable when used with groups with similar characteristics.

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In order to examine the effect of acute respiratory acidosis induced by CO₂ inhalation prior to maximal exercise on blood lactate and physical performance, double determinations were carried out for each subject on separate days ; one day, after CO₂ inhalation and other day, after inhalation of room air. It was observed that in the untrained subjects the CO₂ inhalation prior to maximal treadmill exercise does not affect endurance time and maximum aerobic power, whereas blood lactate during recovery was lower in CO₂ breathing than that in room air. In addition, no significant difference of 200m sprint time in the athletes was noticed between CO₂ and room air while blood lactate after 200m sprint running was significantly lower in the CO₂ than that in room air. From these results, it was suggested that the effect of CO₂ inhalation prior to maximal exercise as applied here appeared to be mediate through metabolic rather than oxygen transport mechanism, but not related to physical performance.

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We investigated which attribute or what combination of attributes would best account for distance running performance of female runners. The subjects were 30 well-trained female distance runners, aged 19 to 23 years. Anthropometric and body composition characteristics, pulmonary function characteristics, blood properties, and cardiorespiratory function characteristics were measured at rest or during submaximal and maximal exercise. Analyses of the data showed that the relationship of oxygen uptake corresponding to lactate threshold (VO₂ @LT, ml·kg^-1min^-1) with each distance running performance was substantially higher as compared with the relationship of other independent variables inlcuding maximal oxygen uptake (VO₂max). Furthermore, multiple regression analysis indicated that running performances in 3, 000m, 5, 000m, and 10, 000m are best accounted for by a combination of VO₂@LT (X₁), fat-free weight (X₂), and/or mean corpuscular volume (X₃). A multiple regression equation for predicting the 5, 000m (Y, s) running performance was formulated as Y= -14.75X₁-3.03X2-5.79X₃ +2282.1. We suggest that VO₂max would not stand alone as a decisive factor of distance running success in female runners, and that the distance running performance could be better accounted for by a combination of several attributes relating to lactate threshold, body composition, and/or hematological status. The linear regression of the predicted running performance on the actually measured running performance can be accepted in the range of 986-1197s.

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