ABSTRACT
Biological age based on the assessment of various physiological factors measured in a resting state has been proposed as an appropriate index of aging. We have recently developed an equation for estimation of physical fitness age (PFA), which is composed of eight age-related physical fitness variables. These include oxygen uptake corresponding to lactate threshold (Vo<SUB>2</SUB>@LT), maximal oxygen uptake (Vo<SUB>2</SUB>max), side step, grip strength, vertical jump, foot balance with eyes closed, trunk extension, and trunk flexion. In this study, the validity of PFA as a critical index of physical health and/or aging status was investigated from a longitudinal standpoint on the assumption that exercise habituation does contribute to health promotion. The subjects were 14 Japanese middle-aged and elderly men, aged 50 to 70 years, all of whom were patients with coronary heart disease (CHD) . The subjects participated in a supervised exercise conditioning program for 90 to 120 min each session, 2 times weekly for 4 months. Analyses of the data indicated that the mean PFA of the subjects (66.0±9.0 yr) after conditioning was significantly (P<0.05) lower than the mean PFA (72.8±8.6 yr) obtained before conditioning. After the exercise program, significant increases were documented in Vo<SUB>2</SUB>@LT (17%), Vo<SUB>2</SUB>max (12%), side step (26%), trunk flexion (109%), trunk extension (7%), vertical jump (12%), and foot balance with eyes closed (31%) . Therefore, we conclude that our exercise conditioning program may alter the overall physical fitness of patients with CHD, and that PFA could be a valid physical health and/or aging index.
ABSTRACT
Principal component analysis was used to estimate the physical fitness age (PFA) of middle-aged and elderly men from eight physical fitness variables. The subjects were 184 Japanese men, aged 20 to 75 years, who were recruited in a series of physical fitness tests including oxygen uptake corresponding to lactate threshold (Vo<SUB>2</SUB>@LT) and maximal oxygen uptake (Vo<SUB>2</SUB>max) . The subjects were categorized into three groups : those (n=134) considered apparently healthy, those (n=35) employed as a cross-validation sample, and 15 patients with coronary heart disease (CHD) . The equation developed for estimation of PFA in healthy individuals (n=134) was PFA=-15.3 PFS+48.0+Z, PFS=0.021 X<SUB>1</SUB>+0.037 X<SUB>2</SUB>+0.020 X<SUB>3</SUB>+0.024 X<SUB>4</SUB>+0.017 X<SUB>5</SUB>+0.017 X<SUB>6</SUB>+0.008 X<SUB>7</SUB>+0.016 X<SUB>8</SUB>-4.92, Z =0.12 Age-5.8; where PFS=physical fitness score, X<SUB>1</SUB>=V<SUB>o2</SUB>max (m<I>l</I>/kg/min), X<SUB>2</SUB>=Vo<SUB>2</SUB>@LT (m<I>l</I>/kg/min), X<SUB>3</SUB>=grip strength (kg), X<SUB>4</SUB>=side step (reps/20s), X<SUB>5</SUB>=trunk extension (cm), X<SUB>6</SUB>=trunk flexion (cm), X<SUB>7</SUB>=foot balance with eyes closed (s), and X<SUB>8</SUB>=vertical jump (cm) . Analyses of the data revealed that healthy individuals had PFAs (47.7±17.5yr) similar to their chronological ages (CA: 48.0±15.3yr) . In the cross-validation sample, it was confirmed that no difference existed between PFA (51.5±13.8yr) and CA (52.1±11.8yr) . CHD patients, however, had PFAs approximately 15 years older than their CAs (57.7±11.5vs. 72.2±12.3yr) . Since independent variables of the above equation consisted of various physical fitness elements, we defined the score as an index of “physical fitness age”. The importance and usefulness of PFA were discussed in more detail.
ABSTRACT
The purpose of the present study was to construct an appropriate flexibility test battery for competitive swimmers.<BR>Twelve flexibility tests which have been validated to measure the flexibility of various parts of body were adminstrated to 153 skilled college swimmers.<BR>For the purpose mentioned above, factor analytic procedures were applied to the correlation matrix consisted of 12 flexibility measures and 5 variables derived from some of these 12 measures.<BR>As a result, the six factors were extracted and interpreted as follows : I) trunk rotation flexibility, II) trunk lateral flexibility, III) shoulder flexibility, IV) ankle extension and mobility flexibility, V) trunk flexion and extension flexibility, and VI) ankle flexion flexibility.<BR>Taking the factorial validity, reliability, and practicability of tests into consideration, the following 6 test items were chosen ; trunk rotation (right) (X<SUB>1</SUB>), trunk lateral flexion (right) (X<SUB>2</SUB>), shoulder extension (X<SUB>3</SUB>), ankle extension (X<SUB>4</SUB>), trunk flexion (X<SUB>5</SUB>), and ankle flexion (X<SUB>6</SUB>) .<BR>Then, the following conventional fomulas for estimating each flexibility factor score were developed ; FS<SUB>1</SUB>=0.9X<SUB>1</SUB>-79.1, FS<SUB>2</SUB>=1.9X<SUB>2</SUB> -49.6, FS<SUB>3</SUB>=0.7X<SUB>3</SUB>-98.9, FS<SUB>4</SUB>=1.8 X<SUB>4</SUB> -250.6, FS<SUB>5</SUB> =1.3X<SUB>5</SUB> -141.7, and FS<SUB>6</SUB> = 2.5X<SUB>6</SUB> -179.3.
ABSTRACT
Various studies have reported on VO<SUB>2</SUB>max differences in men, with or without respect to distance run performances, and demonstrated that VO<SUB>2</SUB>max was the most important factor in endurance work capacity. This study was undertaken to reveal whether VO<SUB>2</SUB>max would still be the best determinant of endurance work capacity (or distance run performances), comparing it with AT parameters using the technique of correlational analyses. Twenty-seven distance runners, 16-26 years of age including an Olympic runner, underwent a multistage-incremental treadmill test for the assessment of submaximal and maximal work capacity. ATs were subjectively evaluated and determined as the point of breakaway of gas exchange criterion parameters according to Davis et al.'s method, and also referring to Wasserman et al.'s method.<BR>The mean VO<SUB>2</SUB>max was 4.518 <I>l</I>/mmn (70.1 ml/kg⋅BW/min, 78.1 ml/kg . LBM/min), whilst the mean AT appeared to be 3.444 <I>l</I>/mmn (52.8 ml/kg/min, 75.60% of VO<SUB>2</SUB>max) . These results are in good agreement with previous results reported by others. Interestingly, all distance performances (i.e., 1-mile, 2-mile, and 3-mile) correlated highest with AT (ml/kg/min), secondly with exhaustion time, and thirdly with either VO<SUB>2</SUB>max or another AT parameter. AT (ml/kg/min) alone accounted for approximately 510, 73%, and 80% of the variance in the 1-mile, 2-mile, and 3-mile performances, respectively.<BR>Since absolute VO<SUB>2</SUB>max is known to be a function of body size (e.g., body weight), an attempt was made to evaluate the relationships between the metabolic parameters and the distance performances through partial correlations holding the influence of body weight or LBM statistically constant. As a result, the correlation of VO<SUB>2</SUB>max (<I>1</I>/mm) with the 3-mile performance increased considerably to r<SUB>p</SUB>=-0.781 ; however, the degree of the relationship was not greater than the zero-order correlation (r=-0.896) obtained between AT (ml/kg/min) and the performance. Furthermore, when entered into a forward selection multiple regression with the 3-mile performance as the dependent variable, AT (<I>l</I>/min) accounted for only an additional 0.8% of the variance. VO<SUB>2</SUB>max (<I>l</I>/min), true % 02, % body fat body weight, VO<SUB>2</SUB>max (ml/kg/min), and vital capacity also accounted for only an additional 0.1%, 0.4%, 0.5%, 0.8%, 1.8%, and 1.8% of the variance, respectively. These data indicate that, considering the sample studied and limitations within this study, AT (ml/kg/min) could be the most significant determinant of the 3-mile run performance and, though to a lesser extent, the 2-mil eand 1-mile run performances.