Body composition in paraplegic male athletes

The body composition and anthropometric characteristics of male paraplegic athletes (PARA, N = 22) were contrasted to an able-bodied ectomorphic (N = 22) and mesomorphic (N = 31) comparison group of moderately and highly trained male subjects. The validity of 12 body composition [density (Db)] prediction equations reported in the literature, 4 generalized, were determined (tested) on this special group of athletes (PARA). On the whole, the prediction equations over-predicted Db in PARA by 0.0039 to 0.0166 g X cm-3 (under-predicted relative fat by 1.8 to 7.4%). Five diameter, 11 circumference, and 7 skinfold measures were used in a SAS-STEPWISE multiple regression procedure with hydrostatically determined Db to develop several suitable Db prediction equations for the paraplegic athlete. Diameters were poor predictors (r = 0.60, SEE = 0.0164), while skinfolds, circumferences, or a combination of measures were acceptable, with the combined equation being best (r = 0.95, SEE = 0.0064). The findings of this study suggest that even generalized equations do not adequately predict Db in PARA and that paraplegic specific equations are presently best suited for predicting Db in paraplegic athletes. The results further indicate that although these equations meet many of the criteria of Lohman, the SEE and total error values are unusually high and make prediction of body composition using anthropometry in a heterogeneous group of PARA athletes slightly unreliable.     

Evaluation of a portable ultrasonoscope in assessing the body composition of college-age women

Subcutaneous fat tissue thickness was measured ultrasonically on 66 females between the ages of 18-26 yr by using a portable ultrasonoscope and by skinfold caliper. Measurements were obtained at seven sites: triceps, biceps, subscapula, suprailiac, abdomen, calf, and thigh. In addition, body density (Db) was measured by the underwater weighing technique. Mean Db was 1.0458 gm X cc-1, corresponding to a percent fat of 22.8% (range = 11.3-35.8%). Correlations between ultrasonic and skinfold measurements were significant (P less than 0.05) at all sites. The highest was noted at the suprailiac (r = 0.86) and the lowest was at the thigh (r = 0.75). Test-retest reliability for ultrasonic measurements, taken on separate days, ranged from r = 0.87 at the triceps to r = 0.99 at the biceps. Four significant regression equations for predicting Db were developed, two utilized skinfolds and two utilized ultrasonic measurements of tissue thickness. The equation with the greatest multiple correlation (R = 0.80) utilized the suprailiac, subscapula, and thigh skinfolds. The equation using ultrasonic measurements taken at the suprailiac and thigh sites demonstrated a multiple correlation of R = 0.78. This instrument is a reliable, portable, and non-invasive alternative to the skinfold caliper in obtaining field measurements of body composition.     

Prediction accuracy of body density, lean body weight, and total body volume equations

The purpose of this study was to determine the accuracy of percent fat estimates derived from regression equations with functions of predicting body density (BD), lean body weight (LBW), and total body volume (TBV) from anthropometric variables. BD, LBW, and TBV equations were derived from the data of 95 young, adult men (percent fat X = 13.4%). The multiple correlations for these equations were: BD, 0.86-0.83; LBW, 0.96-0.95; and TBV, 0.99. The zero order correlations between laboratory determined percent fat and percent fat derived by the BD, LBW, and TBV equations ranged from 0.80 to 0.86 with standard errors from 3.1% to 3.7%. This shows that BD, LBW, and TBV equations have similar accuracy when transformed to percent fat. The derived equations were cross validated with three additional, but diverse, samples (percent fat X = 5.1%; 16.7%; 27.1%). The cross validations results revealed that all equations exhibited similar accuracy. With samples differing in percent fat, systematic prediction errors occurred. The results further confirm population specificity of prediction equations.     

Validation of near-infrared interactance and skinfold methods for estimating body composition of American Indian women

PURPOSE: This study tested the predictive accuracy of the Jackson et al. skinfold (SKF) equations (sigma7SKF and sigma3SKF), a multi-site near-infrared interactance (NIR) prediction equation, and the Futrex-5000 NMR equation in estimating body composition of American Indian women (N = 151, aged 18-60 yr). METHODS: Criterion body density (Db) was obtained from hydrodensitometry at residual lung volume. RESULTS: Sigma7SKF significantly underestimated Db (P < 0.05). Sigma3SKF and Heyward's NIR equations significantly overestimated Db (P < 0.05). The Futrex-5000 NIR equation significantly underestimated percent of body fat (%BF) (P < 0.05). Prediction errors for SKF and multi-site NIR exceeded 0.0080 g x cc(-1). The SEE for Futrex-5000 was 5.5%BF. Thus, ethnic-specific SKF and NIR equations were developed. For the SKF model, the sigma3SKF (triceps, axilla, and suprailium) and age explained 67.3% of the variance in Db:Db = 1.06198316 -0.00038496(sigma3SKF) -0.00020362(age). Cross-validation analysis yielded r = 0.88, SEE = 0.0068 g x cc(-1), E = 0.0070 g x cc(-1), and no significant difference between predicted and criterion Db. For the NIR model, the hip circumference, sigma2AdeltaOD2 (biceps and chest), FIT index, age, and height explained 73.9% of the variance in Db:Db = 1.0707606 -0.0009865(hip circumference) -0.0369861(sigma2deltaOD2) + 0.0004167(height) + 0.0000866(FIT index) -0.0001894(age). Cross-validation yielded r = 0.85, SEE = 0.0076 g x cc(-1), E = 0.0079 g x cc(-1), and a small, but significant, difference between predicted and criterion Db. CONCLUSIONS: We recommend using the ethnic-specific SKF and NIR equations developed in this study to estimate Db of American Indian women.     

Anthropometry and bioelectrical impedance inconsistently predicts fatness in women with regional adiposity.

PURPOSE: This investigation examined the accuracy of several generalizable anthropometric (ANTHRO) and bioelectrical impedance (BIA) regression equations to estimate % body fat (%BF) in women with either upper body (UB) or lower body (LB) fat distribution patterns. METHODS: Thirty-six premenopausal women were individually matched for age (X = 38.6 +/- 6.6 yr), BMI (X = 25.5 +/- 4.2 kg x m(-2)) and %BF (30.3 +/- 8.1%; hydrostatic, [UWW]) and placed by waist to hip ratio (WHR) into two distinct groups: LB (N = 18; WHR < or = 0.73) and UB (N = 18; WHR > or = 0.80). Equations tested were ANTHRO: Jackson et al. (JPW-7 and 3 site), 1980; Durnin and Womersley (DW), 1974; Tran and Weltman (TW), 1989; and Vogel et al. (V), 1988; BIA: Lohman (L), 1992; Gray et al. (G), 1989; and VanLoan and Mayclin (VLM), 1987. Circumference and skinfold measures were made by a trained technician. BIA (Vallhalla, 1990B) measures were taken 4 h postprandially under controlled conditions of water intake and exercise. %BF by UWW (criterion) was not different between groups (UB = 30.8 +/- 8.2%; LB = 29.7 +/- 8%). RESULTS: In the UB group, three of five ANTHRO equations significantly overestimated %BF by approximately 6% (range = 3-8%) as compared with UWW. BIA overestimated %BF in UB by 5% using G and in both groups by about 6% using VLM, whereas L underestimated %BF in LB by about 4%. CONCLUSION: We conclude that ANTHRO and some BIA equations are accurate for predicting %BF in LB fat "shaped" women but are not appropriate for women with primarily abdominal fat patterning.     

Comparison of the BOD POD with the four-compartment model in adult females

PURPOSE: This study was designed to compare the accuracy and bias in estimates of total body density (Db) by hydrostatic weighing (HW) and the BOD POD, and percent body fat (%fat) by the BOD POD with the four-compartment model (4C model) in 42 adult females. Furthermore, the role of the aqueous and mineral fractions in the estimation of body fat by the BOD POD was examined. METHODS: Total body water was determined by isotope dilution ((2)H(2)0) and bone mineral was determined by dual-energy x-ray absorptiometry. Db and %fat were determined by the BOD POD and HW. The 4C model of Baumgartner was used as the criterion measure of body fat. RESULTS: HW Db (1.0352 g x cm(-3)) was not statistically different (P = 0.35) from BOD POD Db (1.0349 g x cm(-3)). The regression between Db by HW and the BOD POD significantly deviated from the line of identity (Db by HW = 0.90 x Db by BOD POD + 0.099; R(2) = 0.94). BOD POD %fat (28.8%) was significantly lower (P < 0.01) than %fat by the 4C model (30.6%). The regression between %fat by the 4C model and the BOD POD significantly deviated from the line of identity (%fat by 4C model = 0.88 x %fat by BOD POD + 5.41%; R(2) = 0.92). BOD POD Db and %fat showed no bias across the range of fatness. Only the aqueous fraction of the fat-free mass (FFM) had a significant correlation with the difference in %fat between the 4C model and the BOD POD. CONCLUSION: These data indicate that the BOD POD underpredicted body fat as compared with the 4C model, and the aqueous fraction of the FFM had a significant effect on estimates of %fat by the BOD POD.     

Prediction of segmental percent fat using anthropometric variables

AIM: This study aimed to develop a prediction equation for segmental percent fat from anthropometric measurements. METHODS: The subjects were 107 adults, consisting of 77 males and 30 females, aged from 21 to 82 years. Height, weight, waist circumference, hip circumference, body mass index, waist hip ratio and subcutaneous fat thickness (SFT) were used as anthropometric measurements. The SFTs were measured at 14 sites. Segmental percent fats in both arms (%SF(arms)), both legs (%SF(legs)) and trunk (%SF(trunk)) were measured by dual-energy absorptiometry (DXA) method, and these values were used as references. To predict the segmental percent fat measured by DXA, stepwise multiple regression analysis was conducted using sex, age and the anthropometric measurements as predictors. To examine the systematic error between the observed and predicted values, the error and the observed values were plotted based on Bland-Altman technique, and limits of agreement (LA) were also calculated. RESULTS: The R, SEE and range of LA values in each prediction equation was as follows: %SF(arms): R=0.919, SEE=3.333%, LA=6.5%; %SF(legs): R=0.915, SEE=3.468, LA=6.5%; %SF(trunk): R=0.858, SEE=4.944, LA=9.7%. These prediction equations used 5 to 7 predictors and met the necessary standards for predicting body fat. Although the prediction accuracy of %SF(trunk) was inferior than those of %SF(arms) and %SF(legs), it was superior to those found in previous study reports predicting abdominal visceral fat mass and fat mass at the trunk from anthropometric measurements. CONCLUSIONS: These prediction equations can be considered useful and practical for predicting segmental percent fat and assessing body fat distribution.     

上海市成年人体脂率推测公式研究

目的:建立上海市成年人体脂率推测公式,为中国人体脂率推测公式的研制提供理论依据。方法:2005年国民体质监测的上海市20～59岁7353名成年人,男性3662名,女性3691名。2007年从上海市杨浦区、虹口区、徐汇区等整群随机抽取240名20～59岁健康成年男女进行交叉验证和回代检验。测试的形态指标为身高、体重、胸围、臀围、腰围、上臂皮褶厚度、肩胛皮褶厚度、腹部皮褶厚度,按照2005年国民体质监测工作手册执行。身体成分指标为脂肪百分比,采用生物阻抗法(BIA)和双能X射线吸收测量法(DEXA)测试。通过测试、指标筛选及确定,建立以各年龄段男、女各三个参数为自变量、以欧姆龙生物阻抗法所测体脂率为因变量的回归方程,并对建立的回归方程进行回代检验和交叉验证。结果:成年女性体脂率推测公式:F%女20～29=0.163X3+0.132X2+0.451X5-20.055;F%女30～39=0.095X1+0.120X2+0.266X4+2.755;F%女40～49=0.105X1+0.121X2+0.227X4+6.058;F%女50～59=0.071X1+0.098X2+0.226X4+8.612。成年男性体脂率推测公式:F%男20～29=0.106X1+0.150X2+0.254X4-5.663;F%男30～39=0.110X1+0.107X2+0.271X4-5.473;F%男40～49=0.187X1+0.187X2+0.094X3+13.896;F%男50～59=0.092X1+0.167X2+0.161X4+5.472。(注:X1-肩胛皮褶厚度,X2-腹部皮褶厚度,X3-上臂皮褶厚度,X4-腰围,X5-臀围)。体脂率推测公式经回代检验和交叉验证均显示实测值与公式推算值相关性高(P<0.01)。结论:以2005年上海市全民体质测定数据为依据,采用多元线性逐步回归、回代检验和交叉验证,初步建立的上海市成年人体脂率推测公式可靠。     

Anthropometric, body composition and somatotype differences of Greek elite female basketball, volleyball and handball players

AIM: The aims of the present study were: a) to determine the anthropometric profile, body composition and somatotype of elite Greek female basketball (B), volleyball (V) and handball (H) players, b) to compare the mean scores among sports and c) to detect possible differences in relation to competition level. METHODS: A total of 518 female athletes, all members of the Greek first National League (A1 and A2 division) in B, V and H sport teams participated in the present study. Twelve anthropometric measures required for the calculation of body composition indexes and somatotype components were obtained according to the established literature. RESULTS: V athletes were the tallest (P<0.001) among the three groups of athletes, had the lowest values of body fat (P<0.001) and their somatotype was characterized as balanced endomorph (3.4-2.7-2.9). B athletes were taller (P<0.01) and leaner (P<0.001) than H players, with a somatotype characterized as mesomorph-endomorph (3.7-3.2-2.4). H athletes were the shortest of all (P<0.01), had the highest percentage of body fat (P<0.001) and their somatotype was mesomorph-endomorph (4.2-4.7-1.8). In comparison with their A2 counterparts the A1 division players were taller (P<0.001) and heavier (P<0.01), but at the same time leaner (P<0.001), and exhibited higher homogeneity in somatotype characteristics (P<0.05). CONCLUSIONS: Anthropometric, body composition and somatotype variables of Greek female elite teamball players varied among sports; selection criteria, hours of training and sport-specific physiological demands during the game could explain the observed differences. More data are certainly needed to define the anthropometric profile of B, V and H female athletes internationally.     

Wrestlers' minimal weight: anthropometry, bioimpedance, and hydrostatic weighing compared

The need for accurate assessment of minimal wrestling weight among interscholastic wrestlers has been well documented. Previous research has demonstrated the validity of anthropometric methods for this purpose, but little research has examined the validity of bioelectrical impedance (BIA) measurements. Comparisons between BIA systems has received limited attention. With these two objectives, we compared the prediction of minimal weight (MW) among 57 interscholastic wrestlers using three anthropometric methods (skinfolds (SF) and two skeletal dimensions equations) and three BIA systems (Berkeley Medical Research (BMR), RJL, and Valhalla (VAL]. All methods showed high correlations (r values greater than 0.92) with hydrostatic weighting (HW) and between methods (r values greater than 0.90). The standard errors of estimate (SEE) were relatively small for all methods, especially for SF and the three BIA systems (SEE less than 0.70 kg). The total errors of prediction (E) for RJL and VAL (E = 4.4 and 3.9 kg) were significantly larger than observed nonsignificant BMR and SF values (E = 2.3 and 1.8 kg, respectively). Significant mean differences were observed between HW, RJL, VAL, and the two skeletal dimensions equations, but nonsignificant differences were observed between HW, BMR, and SF. BMR differed significantly from the RJL and VAL systems. The results suggest that RJL and VAL have potential application for this subpopulation. Prediction equation refinement with the addition of selected anthropometric measurement or moderating variables may enhance their utility. However, within the scope of our study, SF and BMR BIA appear to be the most valid methods for determining MW in interscholastic wrestlers.     

Anthropometric dimensions to predict 1-RM bench press in untrained females

BACKGROUND: Previous research has indicated a strong relationship between anthropometric dimensions and strength in males. To date, little work has been done to explore this topic in females. The purpose of this study was to determine the relationships between selected anthropometric dimensions and 1-RM bench press in untrained college females. METHODS: Untrained college females (n = 113) were evaluated for 18 measured and seven derived anthropometric variables to predict 1-RM bench press strength. Triplicate measurements were averaged for five skinfolds, five circumferences, and six skeletal widths. Derived measurements included Body Mass Index, percent fat, fat-free mass (FFM), flexed arm cross-sectional area (CSA), shoulder width: hip width ratio, androgyny index, and somatotype. RESULTS: Highest zero-order correlations with bench press were arm CSA (r = 0.45), flexed arm circumference (r = 0.45), mesomorphy (r = 0.44), and forearm circumference (r = 0.42). First-order partial correlations holding constant body mass or FFM generally decreased most correlations with bench press (r < 0.30). Factor loadings were used to produce muscle, length, and fat components which were placed in a multiple regression analysis to predict bench press but resulted in only limited success (R = 0.58, SEE = +/- 5.6 kg). Coefficients of variation (SEE/Mean x 100) for the equations ranged from was 18.9% to 21.0%. CONCLUSIONS: Prediction of bench press strength from anthropometric dimensions does not appear to be practical or accurate in untrained females.     

Prediction of endurance running performance for middle-aged and older runners.

The purpose of this study was to develop regression equations that would sufficiently predict the endurance running performance (ERP) of middle-aged and older runners (n = 55, 43-79 years). Among many independent variables which were selected as possible predictors of the ERP, oxygen uptake corresponding to the lactate threshold (VO2@LT), or age was found to be the single best predictor. Some variables representing training habits correlated significantly but only moderately with the ERP. Linear multiple regression equations developed in this study were: V5km = 4.203 + 0.054X1 - 0.028X2 (r = 0.87) V5km = 4.436 + 0.045X1 - 0.033X2 + 0.005X3 (r = 0.89) V10km = 4.252 + 0.042X1 - 0.026X2 (r = 0.79) V10km = 4.371 + 0.037X1 - 0.031X2 + 0.005X3 (r = 0.82) VM = 3.207 + 0.048X1 - 0.022X2 (r = 0.91) VM = 3.707 + 0.038X1 - 0.031X2 + 0.005X3 (r = 0.93) where V5km, V10km and VM are the mean running velocity at 5 km, 10 km and marathon races, respectively, and X1 = VO2@LT (ml kg-1 min-1), X2 = age (year), and X3 = average running duration per workout (min). We suggest that the ERP of middle-aged and older runners can be predicted from a linear combination of VO2@LT and age or a combination of these variables plus average running duration per workout.     

Impact of total body water fluctuations on estimation of body fat from body density

The purpose was to investigate the possibility that variability in body weight in females due to water retention causes differences in body density (Db) values determined by hydrostatic weighing (HW). Determination of total body water (TBW) and Db were concurrently measured in seven females who experienced considerable fluctuations in body weight (1.5-4.5 kg) and seven males, ages 19-24. Females were measured when they felt they were at their lowest (LO) and highest (HI) body weights (BW) during a menstrual cycle. Males were randomly tested approximately 3 wk apart. Mean values of selected variables were compared in the LO vs HI testing sessions by paired t-tests. Significant mean differences were found in the females (P less than 0.01) for the following variables: BW (kg) (LO = 58.9, HI = 61.1), Db (g.cc-1) (LO = 1.0430, HI = 1.037), and percent body fat (%BF) as determined by HW alone (LO = 24.8%, HI = 27.6%). Variables significant at the P less than 0.05 level were TBW(l) (LO = 33.6, HI = 35.1) and %TBW of the fat-free body (LO = 74.5, HI = 75.9). However, changes in TBW could not entirely account for observed changes in Db. Only mean BW (kg) was significant (P less than 0.01) in the males (LO = 74.3, HI = 74.6). It is concluded that changes in TBW can in part result in significantly different Db values obtained from HW in females who did experience perceptible changes in BW during a menstrual cycle. The remaining differences may be due to changes in fat and protein content or methodological errors.     

Development of valid pulmonary function equations for trained athletes

The validity of commonly recommended pulmonary function prediction equations (Bulletin Européen de Physiopathologie Respiratoire, Clinical Respiratory Physiology) was tested with two samples (n1 = 156; n2 = 218) of well-trained athletes. Pulmonary function measures (FVC, TLC, RV, FEF25%-75%, FEV1.0, PEF, RV/TCL ratio, FEV1.0/FVC ratio) were typically very reliable but inaccurately predicted with recommended equations based upon anthropometric characteristics. Newly developed "unisex" regression equations were developed with "dummy" coding of gender (i.e., 0 = female; 1 = male), age, height, weight, and various interactions. The new equations were validated with a subsample of group one, cross-validated with the remaining portion of group one, and then cross-validated again with the 218 subjects from sample two. The newly created pulmonary function prediction equations are more valid for well-trained athletes than the equations in use for the general population.     

The psychobiological model and multiple discriminant function analysis of high-calibre oarsmen

Candidates for New Zealand rowing teams (N = 181) were given a battery of physiological, performance, anthropometric and psychological tests in order to test the psychobiological model for prediction of athletic success. A series of stepwise multiple discriminant function analyses were conducted on both separate sub-sets of variables and their combinations. The expectation that the model would not differentiate between the three age categories of oarsmen (Juniors, Colt and Senior) except for age-related factors was upheld. A more specific test of the model was an examination of the accuracy of discrimination within each age group between those who were selected for New Zealand teams and those who were not selected. The results indicated that such differentiation was best when the biological and psychological variables were used in concert. The major discriminators between selected and nonselected oarsmen on the psychobiological functions were certain anthropometric and psychological variables. Further support for the notion of the existence of a rowing stereotype was provided by testing the Senior discriminant function on the other two groups. It was concluded that the results were in accordance with the multidisciplinary psychobiological model.     

Prediction of maximal oxygen uptake in boys, ages 7-15 years.

Predictions of Vo2max (1 min-1 and ml kg-1 min-1) were obtained via multiple regression procedures from a sample of 100 boys, ages 6.7-14.8 years. Prediction equations for Vo2max (1 min-1) were obtained from the subjects' height, and the Vo2 (1 min-1) and heart rate observed during the third min of a treadmill walk (R = 0.95; CV = +/- 9.3%). A similar prediction was obtained when the subjects' age, height and weight were used (R = -0.94; CV = +/- 9.7%). Vo2max (ml kg-1 min-1) was predicted with similar accuracy (CV = +/- 8.4%) from age, and heart rate, VCO2(1 min-1), Vo2 (ml kg min-1), or from simply age, height and weight (CV = +/- 9.2%). Cross-validation of the equations with another sample of 39 boys demonstrated that the prediction equations based on laboratory data were quite stable, % errors approximately 1-2 +/- 9%. However, the equations based on age, height and weight underestimated the Vo2max slightly, both in 1 min (X = -0.091 min) and ml kg min (X = -2.2 ml kg min, P less than 0.05). The results indicate that reasonably reliable and accurate estimates of Vo2max for children may be obtained from either laboratory data, or simply from their age, height and weight.     

Athletic amenorrhea: lack of association with body fat

The most commonly tested hypothetical cause of athletic amenorrhea has been low body fat. Test results have conflicted because of mixed groups of athletes and methodologic problems. In this study, we measured body fat only in distance runners (greater than 53 km X wk-1) of the same somatotype who clearly had regular menses or secondary amenorrhea; this permitted more valid group comparison of body fat using hydrostatic weighing. The regularly menstruating group (N = 7) had 12 periods X yr-1 at intervals of 26.5 +/- 1.0 (SE) days with a duration of 4.1 +/- 0.4 days. In the athletic amenorrhea group (N = 7), menstrual periods had been absent for 1 to 10 yr (average = 3.9 +/- 1.3 yr); they were gynecologically evaluated to restrict the group to those with athletic amenorrhea. The groups were similar in a number of categories: weight, height, age, menarcheal age, weekly training mileage, days/week training, years of training, and maximum oxygen uptake. Percent body fat for the two groups was the same: 17.7 +/- 2.1% for the amenorrheic athletes and 17.4 +/- 1.2% for the regularly menstruating athletes (P = 0.91). These data do not support the idea that low body fat per se causes athletic amenorrhea.     

Estimation of VO2max from a one-mile track walk, gender, age, and body weight

The purpose of this investigation was to explore an alternative field test to estimate maximal oxygen consumption (VO2max) using a one-mile walk test. VO2max was determined in 343 healthy adult (males = 165, females = 178) subjects 30 to 69 yr using a treadmill protocol (mean +/- SD: VO2max = 37.0 +/- 10.7 ml X kg-1 X min-1). Each subject performed a minimum of two, one-mile track walks as fast as possible. The two fastest walks (T1, T2) with elapsed times within 30 s were used for subsequent analyses. Heart rates were monitored continuously and recorded every one-quarter mile. Multiple regression analysis (best sub-sets) to estimate VO2max (l X min-1) yielded the following predictor variables: track walk-1 time (T1); fourth quarter heart rate for track walk-1 (HR 1-4); age (yr); weight (lb); and sex (1 = male, 0 = female). The best equation (N = 174) was: VO2max = 6.9652 + (0.0091*WT) - (0.0257*AGE) + (0.5955*SEX) - (0.2240*T1) - (0.0115*HR1-4); r = 0.93, SEE = 0.325 l X min-1. Comparing observed and estimated VO2max values in a cross-validation group (N = 169) resulted in r = 0.92, SEE = 0.355 l X min-1. Generalized and sex-specific equations to estimate VO2max (ml X kg-1 X min-1) were also generated. The accuracy of estimation as expressed by SEE was similar among the equations. The results indicate that this one-mile walk test protocol provides a valid sub-maximum assessment for VO2max estimation.     

Validity of anthropometric equations for determination of changes in body composition in adult males during training

Twenty-six males (26.5 +/- 6.0 yr; X +/- SD) were studied before and after a fourteen week endurance training program to determine the validity of anthropometric equations for estimating changes in body composition (BC). Anthropometric measures included skinfolds (SF), circumferences, and diameters. Body density (BD) was determined by underwater weighing corrected for residual lung volume. Training resulted in an increase in BD (1.061 +/- 0.002 to 1.067 +/- 0.002 g/ml; X +/- SEM) and decreases in body weight (73.0 +/- 2.1 to 71.4 +/- 2.0 kg), relative fat (16.6 +/- 0.9 to 14.1 +/- 0.8%), fat weight (12.4 +/- 1.0 to 10.2 +/- 0.8 kg), and seventeen of the anthropometric measures (p less than 0.05). Cross-validation of twenty-four equations revealed validity coefficients (r2) and total error in relative fat (RFE) of r2 = 0.40-0.77 and RFE = 2.60-10.15% before training and r2 = 0.14-0.61 and RFE = 2.62-9.45% after training. Linear and base 10 logarithmic (log10) equations using primarily SF measures tended to have higher r2 and lower RFE than equations based on quadratic and natural logarithmic (loge) models and other anthropometric measures. Paired t-tests revealed that of these equations with higher r2 and lower RFE, only the linear equation by Forsyth & Sinning (BD = 1.10647--0.00162(scapSF)--0.00144(abdSF)--0.00077(triSF++ +) + 0.00071(midaxSF] was a stable predictor of BD during training. These results suggest that many existing equations may not be accurate predictors of changes in BC during training.