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1.
Accurate measurement of head volume is indispensable for precise assessments of body composition determined by hydrostatic weighing without head submersion. The purpose of this study was to establish a prediction equation for head volume measured by the immersion method from multiple regression analysis using head parameters (head circumference, head length, head breadth, neck girth and head thickness) as independent variables. The participants were 106 Japanese young adults (55 males and 51 females) aged 17?–?27 years. Intra-class correlation coefficients (ICCs) for each head parameter and head volume in males and females were very high (ICC = 0.993?–?0.999, 0.992?–?0.998). Head circumference was closely related to head volume measured by the immersion method (r = 0.719, 0.861, P <?0.05), and was the most important parameter for the prediction equation in both sexes. Head breadth was related poorly (r = 0.475, 0.500, P <?0.05) and showed a small individual difference. It was, therefore, excluded from the independent variables. The prediction equation for males was predicted head volume = 122.10X 1 + 106.19X 3 + 37.16X 4 - 89.46X 5 - 4754.93, R = 0.909, SEE = 121.75?ml, and that for females was predicted head volume = 213.83X 1 + 45.24X 3 + 36.85X 4 - 74.34X 5 - 8912.43, R = 0.913, SEE = 136.26?ml (where X 1 = head circumference, X 3 = head length, X 4 = neck girth, X 5 = head thickness, and SEE = standard error of the estimate). The limits of agreement for predicted and measured head volume were –?234.5 to 234.1?ml for males, and ??261.0 to 261.0?ml for females. In cross-validation groups of both sexes, there were no significant differences between measured head volume and predicted head volume. The correlation coefficients between measured head volume and predicted head volume in males and females were 0.894 and 0.908, respectively. The predicted head volume from prediction equations was considered to have high reliability and validity.  相似文献   

2.
This study examined a method of predicting body density based on hydrostatic weighing without head submersion (HWwithoutHS). Donnelly and Sintek (1984) developed a method to predict body density based on hydrostatic weight without head submersion. This method predicts the difference (D) between HWwithoutHS and hydrostatic weight with head submersion (HWwithHS) from anthropometric variables (head length and head width), and then calculates body density using D as a correction factor. We developed several prediction equations to estimate D based on head anthropometry and differences between the sexes, and compared their prediction accuracy with Donnelly and Sintek's equation. Thirty-two males and 32 females aged 17-26 years participated in the study. Multiple linear regression analysis was performed to obtain the prediction equations, and the systematic errors of their predictions were assessed by Bland-Altman plots. The best prediction equations obtained were: Males: D(g) = -164.12X1 - 125.81X2 - 111.03X3 + 100.66X4 + 6488.63, where X1 = head length (cm), X2 = head circumference (cm), X3 = head breadth (cm), X4 = head thickness (cm) (R = 0.858, R2 = 0.737, adjusted R2 = 0.687, standard error of the estimate = 224.1); Females: D(g) = -156.03X1 - 14.03X2 - 38.45X3 - 8.87X4 + 7852.45, where X1 = head circumference (cm), X2 = body mass (g), X3 = head length (cm), X4 = height (cm) (R = 0.913, R2 = 0.833, adjusted R2 = 0.808, standard error of the estimate = 137.7). The effective predictors in these prediction equations differed from those of Donnelly and Sintek's equation, and head circumference and head length were included in both equations. The prediction accuracy was improved by statistically selecting effective predictors. Since we did not assess cross-validity, the equations cannot be used to generalize to other populations, and further investigation is required.  相似文献   

3.
Abstract

The purpose of this study was to examine the accuracy and reliability of whole-body volume, body density, and percent body fat calculated from body volume without the head (V NH), as assessed by hydrostatic weighing without head submersion and predicted head volume (pV H) based on head parameters, as compared with standard hydrostatic weighing. Participants comprised 29 males and 27 females aged 17–26 years. Head volume was predicted from anthropometric head parameters using a prediction equation. Underwater weights with/without head submersion were measured five times. The reliability of underwater weighing without head submersion was very good (intraclass correlation coefficient: males=0.998, females=0.998) as was that for traditional head submersion. The relationship between the sum of V NH and pV H and the whole-body volume measured by hydrostatic weighing was very high (males=0.998, females=0.999), and their values were very similar with an error range of 300–400 ml. Although percent body fat assessed from the sum of V NH and pV H showed a slight scatter of 2–3% from the identity line of percent body fat assessed by hydrostatic weighing, the relationships for both sexes were very strong (males=0.918, females=0.957). The errors (2 standard deviations) as determined by Bland-Altman plots between the two methods were ?3.2 to 2.6% in males and ?2.3 to 2.8% in females. There was no significant bias in percent body fat estimated by the two methods (hydrostatic weighing with/without head submersion), and the sum of V NH and pV H could validly estimate body composition, regardless of physical size. It is suggested that hydrostatic weighing without head submersion is a valid and convenient alternative technique.  相似文献   

4.
The purpose of this study was threefold: to determine (a) the test-retest reliability of the 20-m shuttle test (20 MST) (number of laps), (b) the concurrent validity of the 20 MST (number of laps), and (c) the validity of the prediction equation for VO2max developed by Léger, Mercier, Gadoury, and Lambert (1988) on Canadian children for use with American children 12-15 years old. An intraclass coefficient of .93 was obtained on 20 students (12 males; R = .91 and 8 females; R = .87) who completed the test twice, 1 week apart (MT1 = 47.80 +/- 20.29 vs. MT2 = 50.55 +/- 22.39 laps; p > or = .13). VO2peak was obtained by a treadmill test to volitional fatigue on 48 subjects. The number of laps run correlated significantly with VO2peak in males (n = 22; r = .65; F [1, 20] = 14.30 p < or = .001), females (n = 26; r = .51; F [1, 24] = 8.34; p < or = .01), and males and females = (r = .69; F [1, 46] = 42.54, p < or = .001). When the measured VO2peak (M = 49.97 +/- 7.59 ml.kg-1.min-1) was compared with the estimated VO2max (M = 48.72 +/- 5.72 ml.kg-1.min-1) predicted from age and maximal speed of the 20 MST (Léger et al., 1988) no significant difference was found, t (47) = -1.631; p > or = .11, between the means; the r was .72 and SEE was 5.26 ml.kg-1.min-1.(ABSTRACT TRUNCATED AT 250 WORDS)  相似文献   

5.
The purpose of this study was to assess the accuracy of three recommended anthropometric equations for women and then develop an updated prediction equation using dual energy x-ray absorptiometry (DXA). The percentage of body fat (%BF) by anthropometry was significantly correlated (r = .896-.929; p < .01) with DXA, but each equation underestimated %BF (3.2-5.6 %BF; p < .01). The following DXA criterion (DC) equation was created: %BF= -6.40665 + 0.41946(S3SF) - 0.00126(S3SF)2 + 0.12515(hip) + 0.06473 (age); (S3SF = sum of triceps, suprailiac, thigh; hip = circumference in cm; age = years). The predicted residual sum of squares (PRESS) R2 was high (0.86), and the PRESS standard error of estimate (SEE) was low (2.5 %BF) for our sample of 150 women. The DC equation was further crosschecked on a separate sample of women (n = 25) and again showed excellent agreement. The DC equation appears to be a more accurate estimation of %BF in women.  相似文献   

6.
There is a large residual volume (RV) error when assessing percent body fat by means of hydrostatic weighing. It has generally been measured before hydrostatic weighing. However, an individual's maximal exhalations on land and in the water may not be identical. The aims of this study were to compare residual volumes and vital capacities on land and when immersed to the neck in water, and to examine the influence of the measurement error on percent body fat. The participants were 20 healthy Japanese males and 20 healthy Japanese females. To assess the influence of the RV error on percent body fat in both conditions and to evaluate the cross-validity of the prediction equation, another 20 males and 20 females were measured using hydrostatic weighing. Residual volume was measured on land and in the water using a nitrogen wash-out technique based on an open-circuit approach. In water, residual volume was measured with the participant sitting on a chair while the whole body, except the head, was submerged . The trial-to-trial reliabilities of residual volume in both conditions were very good (intraclass correlation coefficient > 0.98). Although residual volume measured under the two conditions did not agree completely, they showed a high correlation (males: 0.880; females: 0.853; P < 0.05). The limits of agreement for residual volumes in both conditions using Bland-Altman plots were -0.430 to 0.508 litres. This range was larger than the trial-to-trial error of residual volume on land (-0.260 to 0.304 litres). Moreover, the relationship between percent body fat computed using residual volume measured in both conditions was very good for both sexes (males: r = 0.902; females: r = 0.869, P < 0.0001), and the errors were approximately -6 to 4% (limits of agreement for percent body fat: -3.4 to 2.2% for males; -6.3 to 4.4% for females). We conclude that if these errors are of no importance, residual volume measured on land can be used when assessing body composition.  相似文献   

7.
The aims of this study were to determine the validity of fat mass of the trunk as a predictor for visceral fat area at the umbilicus level and to develop equations to predict visceral fat mass at the umbilicus level using fat mass of the trunk measured by dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA). The participants were 121 normal Japanese adults (69 males, 52 females). Another 60 volunteer adults (34 males, 26 females) were recruited for examination of cross-validity. Altogether, 41 adults (15 males, 26 females) in the original group and 19 adults (7 males, 12 females) in the cross-validity group received BIA measurement. We measured fat mass by DXA and the BIA system, which was a single-frequency BIA with 8-point contact electrodes, and visceral fat area by computed tomography. We observed significant correlations for visceral fat area in waist circumference (0.56) and fat mass of the trunk measured by DXA (0.64). There was no significant difference in fat mass of the trunk between the DXA and BIA systems, but the BIA system tended to provide an underestimate compared with DXA. With combined fat mass of the trunk measured by DXA and waist circumference as predictors, visceral fat area was estimated by equation (1) (R = 0.87, R(2) = 0.76, standard error of the estimate = 20.9 cm(2)). When substituting fat mass of the trunk measured by BIA into equation (1), there was no significant difference in visceral fat area between the reference and predicted values. An equation using fat mass of the trunk measured by BIA (equation 2) was obtained (R = 0.89, R(2) = 0.78, standard error of the estimate = 20.7 cm(2)), but a systematic error was found for the males. There was cross-validity in both equations. In conclusion, fat mass of the trunk is an effective predictor for the visceral fat area at the umbilicus level. Fat mass of the trunk measured by BIA might be a valid method to predict visceral fat, although further studies with larger samples taking into account the extent and type of obesity are required.  相似文献   

8.
The purpose of this study was to develop a submaximal, 1.5-mile endurance test for college-aged students using walking, jogging, or running exercise. College students (N = 101: 52 men, 47 women), ages 18-26years, successfully completed the 1.5-mile test twice, and a maximal graded exercise test. Participants were instructed to achieve a "somewhat hard" exercise intensity (rating of perceived exertion = 13) and maintain a steady pace throughout each 1.5-mile test. Multiple linear regression generated the following prediction equation: VO2 max = 65.404 + 7.707 x gender (1 = male; 0 =female) - 0.159 x body mass (kg) - 0.843 x elapsed exercise time (min; walking, jogging orrunning). This equation shows acceptable validity (R = .86, SEE = 3.37 ml x kg(-1) min(-1)) similar to the accuracy of comparable field tests, and reliability (ICC = .93) is also comparable to similar models. The statistical shrinkage is minimal (R(press) = 0.85, SEE(press) = 3.51 ml x kg(-) x min(-1)); hence, it should provide comparable results when applied to other similar samples. A regression model (R =.90, and SEE = 2.87 ml x kg(-1) min(-1)) including exercise heart rate was also developed: VO2 max = 100.162 +/- 7.301 x gender(1 = male; 0 =female) - 0.164 x body mass (kg) - 1.273 x elapsed exercise time -0.156 x exercise heart rate, for those who have access to electronic heart rate monitors. This submaximal 1.5-mile test accurately predicts maximal oxygen uptake (VO2max) without measuring heart rate and is similar to the 1.5-mile run in that it allowsfor mass testing and requires only a flat, measured distance and a stopwatch. Further, it can accommodate a wide range of fitness levels (from walkers to runners).  相似文献   

9.
The aim of the present study was to develop and cross-validate anthropometrical prediction equations for segmental lean tissue mass (SLM). One hundred and seventeen young healthy Caucasians (67 men and 50 women; mean age: 31.9 ± 10.0 years; Body Mass Index: 24.3 ± 3.2 kg · m(-2)) were included. Body mass (BM), stretch stature (SS), 14 circumferences (CC), 13 skinfolds (SF) and 4 bone breadths (BB) were used as anthropometric measurements. Segmental lean mass of both arms, trunk and both legs were measured by dual energy X-ray absorptiometry as the criterion method. Three prediction equations for SLM were developed as follows: arms = 40.394(BM) + 169.836(CCarm-tensed) + 399.162(CCwrist) - 85.414(SFtriceps) - 39.790(SFbiceps) - 7289.190, where Adj.R (2) = 0.97, P < 0.001, and standard error of estimate (SEE) = 355 g;trunk = 181.530(BM) + 155.037(SS) + 534.818(CCneck) + 175.638(CCchest) - 88.359(SFchest) - 147.232(SFsupraspinale) - 46522.165, where Adj.R(2) = 0.97, P < 0.001, and SEE = 1077g; and legs = 55.838(BM) + 88.356(SS) + 235.579(CCmid-thigh) + 278.595(CCcalf) + 288.984(CCankle) - 84.954(SFfront-thigh) - 53.009(SFmedial calf) - 28522.241, where Adj.R (2) = 0.96, P < 0.001, and SEE = 724 g. Cross-validation statistics showed no significant differences (P < 0.05) between observed and predicted SLM. Root mean squared errors were smallest for arms (362 g), followed by legs (820 g) and trunk (1477 g). These new prediction equations allow an accurate estimation of segmental lean mass in groups of young adults, but estimation errors of 8 to 14% can occur in certain individuals.  相似文献   

10.
Non-exercise equations developed from self-reported physical activity can estimate maximal oxygen uptake (VO(2)max) as well as submaximal exercise testing. The International Physical Activity Questionnaire (IPAQ) is the most widely used and validated self-report measure of physical activity. This study aimed to develop and test a VO(2)max estimation equation derived from the IPAQ-Short Form (IPAQ-S). College-aged males and females (n = 80) completed the IPAQ-S and performed a maximal exercise test. The estimation equation was created with multivariate regression in a gender-balanced subsample of participants, equally representing five levels of fitness (n = 50) and validated in the remaining participants (n = 30). The resulting equation explained 43% of the variance in measured VO(2)max (SEE = 5.45 ml·kg(-1)·min(-1)). Estimated VO(2)max for 87% of individuals fell within acceptable limits of error observed with submaximal exercise testing (20% error). The IPAQ-S can be used to successfully estimate VO(2)max as well as submaximal exercise tests. Development of other population-specific estimation equations is warranted.  相似文献   

11.
The purpose of this study was to develop a regression equation to predict maximal oxygen uptake (VO2max) based on nonexercise (N-EX) data. All participants (N = 100), ages 18-65 years, successfully completed a maximal graded exercise test (GXT) to assess VO2max (M = 39.96 mL x kg(-1) x min(-1), SD = 9.54). The N-EX data collected just before the maximal GXT included the participant's age; gender; body mass index (BMI); perceived functional ability (PFA) to walk, jog, or run given distances; and current physical activity (PA-R) level. Multiple linear regression generated the following N-EX prediction equation (R = .93, SEE = 3.45 mL x kg(-1) x min(-1), % SEE = 8.62): VO2max (mL x kg(-1) x min(-1)) = 48.0730 + (6.1779 x gender; women = 0, men = 1) - (0. 2463 x age) - (0.6186 x BMI) + (0.7115 x PFA) + (0.6709 x PA-R). Cross validation using PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage (R(p) = .91 and SEE(p) = 3.63 mL x kg(-1) x min(-1)); thus, this model should yield acceptable accuracy when applied to an independent sample of adults (ages 18-65 years) with a similar cardiorespiratory fitness level. Based on standardized beta-weights, the PFA variable (0.41) was the most effective at predicting VO2max followed by age (-0.34), gender (0.33), BMI (-0.27), and PA-R (0.16). This study provides a N-EX regression model that yields relatively accurate results and is a convenient way to predict VO2max in adult men and women.  相似文献   

12.
Book reviews     
Thigh muscle volume is a useful determinant of functional fitness. However, anthropometric prediction of muscle content is influenced by the variability of adipose tissue accumulation. The aims of this study were to predict thigh muscle and adipose tissue volumes from anthropometry and to assess the validity of the method by examining the various components of the measurements and the assumptions involved. The 19 participants (9 men, 10 women; age 23-49 years) varied in adiposity. They all underwent magnetic resonance imaging (MRI) of the upper leg and the eight men and two women with the lowest adiposity underwent detailed anthropometry involving girths and skinfolds. Using MRI as the reference method, muscle volume was predicted from anthropometry using a circular concentric model, and the assumptions inherent in the method were tested further using the MRI data alone. Muscle volume was best predicted by anthropometry in the 10 leanest participants using a five-slice truncated cone model that overestimated the mean MRI value by 30% ( R 2 = 0.95; standard error of estimate = 288 cm 3 ; P ? 0.001). A single skinfold plus girth measurement at the mid-thigh almost matched its predictive ability, but with an increased bias. Measurements of leg circumference by means of the two techniques agreed well. The assumption of a circular cross-section was valid. In contrast, the agreement between skinfold thickness measured by caliper and superficial adipose tissue thickness by MRI was poor, contributing to the scatter of fat and lean area comparisons. An anterior skinfold thickness measurement underestimated the area of superficial adipose tissue at that level, particularly at the most proximal and distal sites. Although these limitations increase the uncertainties of muscle volume determination by anthropometry, they do not prevent its valid prediction in leaner individuals. The prediction of superficial adipose tissue was poorer.  相似文献   

13.
The purpose of this study was to develop and cross-validate anthropometric body composition equations for the elderly (i.e., ≥ 65 years old). This was undertaken due to a lack of accurate and reliable body composition equations for the elderly. One-hundred fifty male (n = 75) and female (n = 75; mean age = 70 years, SD = 3.71 years) elderly were randomly assigned to either an equation development sample (n = 50) or an equation validation sample (n = 25), respectively. The male and female development and validation sample groups, respectively, were joined to make combined development (n = 100) and validation (n = 50) samples. Hydrodensitometry was used to determine participant body density, percent fat, fat-free mass, and fat weight for use as the criterion variables by which prediction equations could be developed and validated. The equations presented are for the prediction of body density [body density = 1.0554 + .0142 (gender) + .0267 (height) - .00022 (midaxillary) - .00086 (hip circumference)], percent fat [% fat = .1688 (body mass index) + .542 (hip circumference) -.1639 (weight) -5.7033 (gender) -7.9498], fat-free mass [fat-free mass = 30.3769 + 8.0108 (height) + .824 (weight) - .1355 (suprailiac) - .5419 (hip circumference)], and fat weight [fat weight = .2449 (weight) + .5218 (hip circumference) - .076 (thigh circumference) - 4.0299 (gender) - 37.8619]. The equations provided estimates that were not statistically different from the hydrostatically determined criterion variables but were statisfically different from estimates derived from other published "elderly" body composition equations.  相似文献   

14.
BackgroundMuscular strength can be conceptually determined by two components: muscle activation and size. Muscle activation by the central nervous system can be measured by surface electromyography (sEMG). Muscular size reflects the amount of contractile protein within a skeletal muscle and can be estimated by anthropometric measurements. The purpose of this study was to determine the relative contributions of size parameters and muscle activation to the prediction of maximal voluntary isometric elbow flexion strength.MethodsA series of anthropometric measurements were taken from 96 participants. Torque and root-mean-square (RMS) of the sEMG from the biceps brachii were averaged across three maximal voluntary isometric contractions. A multiple linear regression analysis was performed based on a Pearson's correlation matrix.ResultsBody weight (BW) accounted for 39.1% and 27.3% in males and females, respectively, and was the strongest predictor of strength for males. Forearm length (L3) was the strongest predictor of strength in females (partial R2 = 0.391). Elbow circumference (ELB) accounted for a significant (p < 0.05) amount of variance in males but not females. The addition of sEMG RMS as a third variable accounted for an average of 10.1% of the variance excluding the equation of BW and L3 in females. The strongest prediction equation included BW, L3, and ELB accounting for 55.6% and 58.5% of the variance in males and females, respectively.ConclusionAnthropometrics provide a strong prediction equation for the estimation of isometric elbow flexion strength. Muscle activation, as measured by sEMG activity, accounted for a significant (p < 0.05) amount of variance in most prediction equations, however, its contribution was comparable to an additional anthropometric variable.  相似文献   

15.
Thigh muscle volume is a useful determinant of functional fitness. However, anthropometric prediction of muscle content is influenced by the variability of adipose tissue accumulation. The aims of this study were to predict thigh muscle and adipose tissue volumes from anthropometry and to assess the validity of the method by examining the various components of the measurements and the assumptions involved. The 19 participants (9 men, 10 women; age 23-49 years) varied in adiposity. They all underwent magnetic resonance imaging (MRI) of the upper leg and the eight men and two women with the lowest adiposity underwent detailed anthropometry involving girths and skinfolds. Using MRI as the reference method, muscle volume was predictedfrom anthropometry using a circular concentric model, and the assumptions inherent in the method were tested further using the MRI data alone. Muscle volume was best predicted by anthropometry in the 10 leanest participants using a five-slice truncated cone model that overestimated the mean MRI value by 30% (R2 = 0.95; standard error of estimate = 288 cm3; P < 0.001). A single skinfold plus girth measurement at the mid-thigh almost matched its predictive ability, but with an increased bias. Measurements of leg circumference by means of the two techniques agreed well. The assumption of a circular cross-section was valid. In contrast, the agreement between skinfold thickness measured by caliper and superficial adipose tissue thickness by MRI was poor, contributing to the scatter of fat and lean area comparisons. An anterior skinfold thickness measurement underestimated the area of superficial adipose tissue at that level, particularly at the most proximal and distal sites. Although these limitations increase the uncertainties of muscle volume determination by anthropometry, they do not prevent its valid prediction in leaner individuals. The prediction of superficial adipose tissue was poorer.  相似文献   

16.
During the 1997 Federation Internationale des Sociétés d'Aviron (FISA) World Junior Rowing Championships, the anthropometric characteristics of 245 female junior rowers aged 17.5 +/- 0.8 years (mean +/- s) were assessed. Twenty-seven body dimensions (body mass, 6 heights or lengths, 4 breadths, 10 girths and 6 skinfolds) were measured in total. The elite female junior rowers were taller (174.5 +/- 6.2 cm) and heavier (69.5 +/- 6.2 kg), with greater length, breadth and girth dimensions, but lower skinfold thicknesses than a representative sample of Flemish (Belgian) girls of the same chronological age. An anthropometric profile chart was constructed that was rowing-specific and norms were established. Compared with scullers, sweep rowers were heavier (+4.2 kg) and taller (+2.8 cm), with greater length, breadth (except for femur width) and girth dimensions (except for calf girth). Sweep rowers also had greater skinfold thicknesses (except for the thigh and calf skinfolds). Finalists were heavier (+3.6 kg) and taller (+3.9 cm), with greater length, breadth (except for femur width) and girth dimensions (except for calf girth) than non-finalists. No significant differences were found for skinfold thicknesses between finalists and non-finalists.  相似文献   

17.
Previous investigators evaluated running economy (RE) with participants running at the same speed by examining the oxygen consumption (VO2) variance. This study was designed to examine the influence of running speed (RS), exercise intensity, body composition, stride length, and gender on RE. Physical characteristics (mean ± standard deviation) of 22 male and 21 female participants were: age (years) = 27.3 ± 3.5 and 26.0 ± 4.0, and VO2peak (ml · kg-1 · min-1) = 53.9 ± 7.7 and 41.2 ± 5.4, respectively. Participants ran 6 min in duration (0% grade) at an estimated 75% of VO2peak. Multiple regression determined which variables accounted for a significant proportion of RE variance. The following equation defined RE: VO2 (ml · kg-1 · min-1) = (RS2 [m/min] x 0.00048) + (HR% x 0.158) + 7.692. The equation resulted in an R2 of .917 and a standard error of estimate (SEE) of 1.8 ml · kg-1 · min-1. Nonsignificance of regression slope and intercept revealed the RE model could be used for men and women. When cross-validated on a separate sample of physically active participants, the derived model was also highly accurate for evaluating RE (R2 = .901, SEE = 2.3 ml · kg-1 · min-1).  相似文献   

18.
Thirty-eight female subjects (M +/ SD = 33 +/- 3.0 years) had VO2max measured on the cycle ergometer (M +/- SD = 37.3 +/- 6.4 ml.kg-1.min-1) and on the treadmill (M +/- SD = 41.3 +/- 6.6 ml.kg-1.min-1). VO2max was estimated for each subject from heart rate (HR) at submaximal workloads on the cycle ergometer using the Astrand-Rhyming nomogram (A/R) and the extrapolation method (XTP). VO2max was also estimated from three field tests: 1.5-mile run (RUN) (independent variable [IV] = time), mile walk (WALK) (IV = time, age, HR, gender, body weight), and the Queens College Step Test (ST) (IV = HR during 5-20 s recovery). Repeated measure ANOVA revealed significant mean differences between the criterion cycle ergometer VO2max versus A/R and XTP (20 and 12% overestimation). The WALK, RUN, and ST VO2max values were not significantly different from the criterion treadmill VO2max. The correlation between criterion VO2max estimated from the WALK and RUN were r = .73 (SEE = 4.57 ml,kg-1.min-1) and r = .79 (SEE = 4.13 ml.kg-1.min-1), respectively. The ST, A/R, and XTP had higher SEEs (13-13.5% of the mean) and lower r s (r = .55 to r = .66). These results suggest both the WALK and RUN tests are satisfactory predictors of VO2max in 30 to 39-year-old females.  相似文献   

19.
Abstract

The aims of this study were to determine the validity of fat mass of the trunk as a predictor for visceral fat area at the umbilicus level and to develop equations to predict visceral fat mass at the umbilicus level using fat mass of the trunk measured by dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA). The participants were 121 normal Japanese adults (69 males, 52 females). Another 60 volunteer adults (34 males, 26 females) were recruited for examination of cross-validity. Altogether, 41 adults (15 males, 26 females) in the original group and 19 adults (7 males, 12 females) in the cross-validity group received BIA measurement. We measured fat mass by DXA and the BIA system, which was a single-frequency BIA with 8-point contact electrodes, and visceral fat area by computed tomography. We observed significant correlations for visceral fat area in waist circumference (0.56) and fat mass of the trunk measured by DXA (0.64). There was no significant difference in fat mass of the trunk between the DXA and BIA systems, but the BIA system tended to provide an underestimate compared with DXA. With combined fat mass of the trunk measured by DXA and waist circumference as predictors, visceral fat area was estimated by equation (1) (R = 0.87, R 2 = 0.76, standard error of the estimate = 20.9 cm2). When substituting fat mass of the trunk measured by BIA into equation (1), there was no significant difference in visceral fat area between the reference and predicted values. An equation using fat mass of the trunk measured by BIA (equation 2) was obtained (R = 0.89, R 2 = 0.78, standard error of the estimate = 20.7 cm2), but a systematic error was found for the males. There was cross-validity in both equations. In conclusion, fat mass of the trunk is an effective predictor for the visceral fat area at the umbilicus level. Fat mass of the trunk measured by BIA might be a valid method to predict visceral fat, although further studies with larger samples taking into account the extent and type of obesity are required.  相似文献   

20.
This study sought to develop a modified submaximal cycle ergometer test designed to predict maximal oxygen consumption (VO2max) obtained on a treadmill. Volunteers (N = 156; women = 80, men = 76) with ages from 18 to 39 years old successfully performed a submaximal cycle protocol on a stationary cycle ergometer and a maximal graded exercise test (GXT) on a treadmill. Open circuit calorimetry was used during the GXT to measure VO2max. Multiple linear regression resulted in the following prediction equation: VO2max = 85.447 + 9.104 χSex (0 = women; 1 = men) - 0.2676 χAge (year) - 0.4150 χBody Mass (kg) + 0.1317 χPower Output (W) - 0.1615 χHeart Rate (bpm), which had acceptable validity (r = .88, standard error of estimate [SEE] = 3.12 ml· kg-1 · min-1). Selected participants (n = 34) performed the submaximal cycle ergometer test twice (within a 5-day period), yielding a test-retest intraclass reliability coefficient of r = .95 for VO2max estimations across days. The reliability of VO2max estimates for women (r = .93) was greater than that for men (r = .74). Cross-validation results were also acceptable using predicted residual sum of squares (PRESS; rPRESS = .87, SEEPRESS = 3.24 ml · kg-1 min-1), which suggests that the new equation should yield acceptable accuracy when it is applied to a similar, but independent sample of adults. In summary, the modified cycle ergometer test developed in this study yields relatively accurate estimates of treadmill VO2max in young adults, requires only a moderate level of exertion, and appears to be a convenient and time-efficient means of estimating cardiorespiratory fitness.  相似文献   

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