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Ninety-one percent (n = 182) of the female members of South Australian representative squads in 14 sports volunteered to act as subjects. Twenty-seven percent of them had represented Australia. The underwater weighing method together with the measurement of residual volume (RV) by helium dilution were used to determine body density (BD); the percent body fat (% BF) was then computed according to Siri. A stepwise multiple regression analysis yielded a correlation coefficient (R) of 0.863 between the criterion (BD) and the best weighted sum of predictors (anthropometric variables): BD (g X cm-3) = 1.14075-0.04959 (log10 sigma triceps, subscapular, supraspinale and calf skinfolds in mm) + 0.00044 (age in decimal years)-0.000612 (waist girth in cm) + 0.000284 (height in cm)-0.000505 (gluteal girth in cm) + 0.000331 (breast girth in cm). Only those predictors which resulted in a statistically significant increase in R (p less than or equal to 0.05) were included. The standard error of estimate of 0.00597 g X cm-3 was equivalent to 2.7% BF at the mean. This equation was shown to be largely population specific. There was a range of 7.6-35.8% of BF and the overall mean 18.5% was significantly lower (p less than 0.001) than that of 23.4% obtained on a moderately active reference sample of similar age (n = 135). If group sizes of only one or two are regarded as too small for meaningful comparison, then the lowest mean of 13.5% was achieved by the long-distance runners (n = 14). The highest averages were registered by the heavyweight rowers (24.2%; n = 7) and soccer players (22.0%; n = 11). The overall average for games players (n = 107) was 19.4%.  相似文献   

3.
This study was designed to examine the reliability and validity of the bioelectrical impedance method (BIA) of measuring body composition and compare its accuracy with the results obtained by standard anthropometric methods BIA, skinfold fat, and hydrostatically measured percent fat (% fat) were obtained on 44 women and 24 men. Each subject was tested four times by two testers on two different days. Generalizability theory was used to estimate reliability and measurement error that considered both day-to-day and intertester error. The BIA, skinfold fat, and hydrostatic methods were all found to be reliable (Rxx = 0.957-0.987) with standard errors ranging from 0.9 to 1.5% fat. An additional 26 men (n = 50) and 38 women (n = 82) were tested once and combined with the data used for the reliability analysis to cross-validate BIA estimates of % fat with hydrostatically determined % fat. The cross-validation correlations for the BIA determinations of % fat ranged from 0.71 to 0.76, which were significantly lower than that obtained with the sum of seven (sigma 7) skinfolds equations (rxy = 0.92 for men and 0.88 for women). The correlations between the weight-to-height ratio body mass index (BMI) and hydrostatically determined % fat were 0.75 and 0.74 for men and women, respectively. The standard errors of estimate for the two BIA models ranged from 4.6 to 6.4% fat compared with 2.6 and 3.6% fat for the sigma 7 equations. The BIA method for measuring body composition was comparable to the BMI method, with height and weight accounting for most of the variance in the BIA equation.  相似文献   

4.
The aim of this study was to validate noninvasive models, retrieved from the literature, estimating body fat in white women. The cohort used for the validation consisted of 277 postmenopausal women, and the reference method was dual-energy X-ray absorptiometry (DXA). Five models were retrieved containing anthropometric measurements such as bicep and tricep skinfolds, waist circumference (WC), height, and body weight. Models including only BMI were found to be less biased and more valid than others including skinfolds and circumferences. The model by Visser et al., estimating body density (BD = 0.0226 × sex - 0.0022 × BMI + 1.0605) with the subsequent use of Brozek's (and not Siri's) equation to estimate body fat percentage (%BF), was found to be more valid than the other models for this cohort. In conclusion, it seems that Visser's et al. model, including only BMI, with Brozek's equation, is a fast, noninvasive, and valid method to assess body composition in white postmenopausal women in clinical practice and research.  相似文献   

5.
This study compared body composition by dual-energy X-ray absorptiometry (DEXA; Lunar DPX-L) with that via a four-compartment (4C; water, bone mineral mass, fat, and residual) model. Relative body fat was determined for 152 healthy adults [30.0 +/- 11.1 (SD) yr; 75.10 +/- 14.88 kg; 176.3 +/- 8.7 cm] aged from 18 to 59 yr. The 4C approach [20.7% body fat (%BF)] resulted in a significantly (P < 0.001) higher mean %BF compared with DEXA (18.9% BF), with intraindividual variations ranging from -2.6 to 7.3% BF. Linear regression and a Bland and Altman plot demonstrated the tendency for DEXA to progressively underestimate the %BF of leaner individuals compared with the criterion 4C model (4C %BF = 0.862 x DEXA %BF + 4.417; r(2) = 0.952, standard error of estimate = 1.6% BF). This bias was not attributable to variations in fat-free mass hydration but may have been due to beam-hardening errors that resulted from differences in anterior-posterior tissue thickness.  相似文献   

6.
In 45 physically active men (ages 35-67 yr) who underwent hydrostatic weighing to determine body composition, multiple regression equations were developed for the prediction of body density (D), lean body weight (LBW), fat body weight (FBW), and % fat using selected anthropometric measurements. The prediction accuracy for these parameters using several previously generated anthropometric regression equations was also determined. With equations developed from the present data a substantially higher correlation was obtained between measured and predicted LBW (r = 0.95) than between measured and predicted D (r = 0.85), FBW (r = 0.88), or % fat (r = 0.84). When previously developed equations were applied to the present sample, correlations between measured and predicted values were considerably lower (4-42%) than in the original studies; this reduction was least in the case of LBW. Analysis of previous data indicated that in selected populations total body weight can account for a relatively large fraction of the variance in LBW. LBW may be estimated quite accurately (r greater than or equal to 0.90) in physically active men with one of several regression equations which include total body weight as an independent variable.  相似文献   

7.
Objective: To develop accurate and reliable equations from simple anthropometric parameters that would predict percentage of total body fat (%BF), total abdominal fat (TAF), subcutaneous abdominal adipose tissue (SCAT), and intra‐abdominal adipose tissue (IAAT) with a fair degree of accuracy. Methods and Procedures: Anthropometry, %BF by dual‐energy X‐ray absorptiometry (DXA) in 171 healthy subjects (95 men and 76 women) and TAF, IAAT, and SCAT by single slice magnetic resonance imaging (MRI) at L3–4 intervertebral level in 100 healthy subjects were measured. Mean age and BMI were 32.2 years and 22.9 kg/m2, respectively. Multiple regression analysis was used on the training data set (70%) to develop equations, by taking anthropometric and demographic variables as potential predictors. Predicted equations were applied on validation data set (30%). Results: Multiple regression analysis revealed the best equation for predicting %BF to be: %BF = 42.42 + 0.003 × age (years) + 7.04 × gender (M = 1, F = 2) + 0.42 × triceps skinfold (mm) + 0.29 × waist circumference (cm) ? 0.22 × weight (kg) ? 0.42 × height (cm) (R 2 = 86.4%). The most precise predictive equation for estimating IAAT was: IAAT (mm2) = ?238.7 + 16.9 × age (years) + 934.18 × gender (M = 1, F = 2) + 578.09 × BMI (kg/m2) ? 441.06 × hip circumference (cm) + 434.2 × waist circumference (cm) (R 2 = 52.1%). SCAT was best predicted by: SCAT (mm2) = ?49,376.4 ? 17.15 × age (years) + 1,016.5 × gender (M = 1, F = 2) +783.3 × BMI (kg/m2) + 466 × hip circumference (cm) (R 2 = 67.1). Discussion: We present predictive equations to quantify body fat and abdominal adipose tissue sub‐compartments in healthy Asian Indians. These equations could be used for clinical and research purposes.  相似文献   

8.
The purpose of this investigation was to predict body density of young and middle-aged women and to determine if the use of a greater variety of variables, particularly those for fat in the bust and hip regions, increases the predictability of body density. Body density determined by the hydrostatic technique (dependent variable) was obtained from 83 volunteer young women and 60 middle-aged women ranging from 18 to 22 and 33 to 50 yr of age, respectively. Independent variables included 8 skinfold, 13 girth, and 7 diameter measures; age; height; weight; and bra and cup sizes. Mean body density for young women was 1.043 g/ml (SD plus or minus 0.014) and percent fat, 24.8 (SD plus or minus 6.4); 1.031 g/ml (SD plus or minus 0.015) and 29.8% (SD plus or minus 6.7) for middle aged subjects. Percent fat was calculated by the formula of Siri. Factor analysis was used to examine the dimensions measured by the independent variables as a function of age. A multiple regression model was used to develop predictions of body density from the independent variables. The best combination of four variables for predicting body density was skinfold thigh, skinfold suprailiac, cup size, skinfold suprailiac, girth waist, and skinfold thigh (R = 0.89) for middle-aged women. The data showed that the highest predictons were found by using combinations of skinfold, girth, and diameter variables; cup size also supported the need for different regression equations for different age groups.  相似文献   

9.
The 5K handicap (5KH), designed to eliminate the body weight (BW) and age biases inherent in the 5K run time (RT), yields an adjusted RT (RTadj) that can be compared between runners of different BW and age. As hypothesized in a validation study, however, not all BW bias may be removed, because of the influences of body fatness (BF) and effort (run speed; essentially the inverse as measured by rating of perceived exertion (RPE)). This study's purpose was to determine the effects of BF and RPE on BW bias in the 5KH. For 99 male runners in a regional 5K race (age = 43.9 +/- 12.1 years; BW = 83.4 +/- 12.9 kg), BF was determined via sum of three skinfolds just before the race. RPE, on the 20-point Borg scale, was used to assess overall race effort on race completion. Multiple regression analysis was used to develop a new adjusted RT (NRTadj, the RTadj corrected for BF and RPE), which was computed for each runner and then correlated with BW to determine bias. Indicative of slight bias, BW was correlated with RTadj (r = 0.220, p = 0.029). Both BF (p = 0.00002) and RPE (p = 0.0005) were significant, independent predictors of RTadj. NRTadj was not significantly correlated with BW (r = 0.051, p = 0.61), but BF explained 90%, and RPE explained only 6%, of the remaining BW bias evidenced in the 5KH. The previous finding that the 5KH does not remove all BW bias is apparently accounted for by BF and not RPE. Because no handicap should be awarded for higher BF, this finding suggests that the 5KH, for men, appropriately adjusts for the age and BW vs. RT biases previously noted.  相似文献   

10.
The purposes of this study were to develop and cross-validate the "best" prediction equations for estimating fat-free body mass (FFB) from bioelectrical impedance in children and youth. Predictor variables included height2/resistance (RI) and RI with anthropometric data. FFB was determined from body density (underwater weighing) and body water (deuterium dilution) (FFB-DW) and from age-corrected density equations, which account for variations in FFB water and bone content. Prediction equations were developed using multiple regression analyses in the validation sample (n = 94) and cross-validated in three other samples (n = 131). R2 and standard error of the estimate (SEE) values ranged from 0.80 to 0.95 and 1.3 to 3.7 kg, respectively. The four samples were then combined to develop a recommended equation for estimating FFB from three regression models. R2 and SEE values and coefficients of variation from these regression equations ranged from 0.91 to 0.95, 2.1 to 2.9 kg, and 5.1 to 7.0%, respectively. As a result of all cross-validation analyses, we recommend the equation FFB-DW = 0.61 RI + 0.25 body weight + 1.31, with a SEE of 2.1 kg and adjusted R2 of 0.95. This study demonstrated that RI with body weight can predict FFB with good accuracy in Whites 10-19 yr old.  相似文献   

11.
Scrotal circumference as an index of testes size, along with body weight, wither height, heart girth and body condition score were measured fortnightly for 114 Menz ram lambs from weaning (91+/-7 SD days) until puberty, which was defined as age at first collection of an ejaculate with 50 x 10(6) spermatozoa and 10% motility. The animals were maintained on poor (n=28), low (n=29), medium (n=29) or high (n=28) levels of nutrition through grazing and supplementation. Further, half the lambs in each group were drenched for endoparasites. Daily gains in live weight, wither height, heart girth and scrotal circumference were 48.5+/-1.6 g, 0.05+/-0.01 cm, 0.07+/-0.01 cm and 0.07+/-0.03 cm, respectively for the period from weaning to puberty and varied with level of nutrition (P<0.05 to 0.001) but not with drenching or its interaction with nutrition level (P>0.10). Scrotal circumference increased linearly and was strongly correlated with age, body weight, wither height, and heart girth (r = 0.83 to 0.85, P<0.001), and lamb weight could be predicted by the equation: 6.35 + 0.53 scrotal circumference (R(2) = 0.73). Mean age, body weight and condition score at puberty were 288+/-6 days, 19.3+/-0.4 kg and 2.6+/-0.06, respectively, and varied due to season of birth, level of nutrition and weaning weight (P<0.01 to 0.001). The nutrition level also influenced (P<0.001) scrotal circumference at puberty, averaging 21.5+/-0.3 cm. It was concluded that postweaning nutrition management had a strong influence on lamb weight gain, which in turn was related to testicular growth and puberty onset in Menz ram lambs. The suitability of scrotal size measurement as a criterion for early selection of tropical ram lambs is emphasised.  相似文献   

12.
BACKGROUND: This field-based investigation examined the congruence between skinfolds and bioelectrical impedance in assessing body composition in children. METHODS: Subjects were 162 female and 160 male children 10-15 years of age. Skinfold measures obtained at the triceps and medial calf and a leg-to-leg bioelectrical impedance system were used to determine percent fat using child-specific equations. Pearson product moment correlations were performed on the percent fat values obtained using skinfolds and bioelectric impedance for the entire data set. Separate correlations were also conducted on gender and age/gender subsets. Dependent t tests were used to compare the two techniques. RESULTS: Percent fat did not differ between skinfolds and bioelectrical impedance for the total subject pool. Bioelectrical impedance overestimated percent fat in girls by 2.6% and underestimated percent fat in boys by 1.7% (p < 0.01). Correlations between skinfolds and bioelectrical impedance ranged from r = 0.51 to r = 0.90. CONCLUSIONS: Leg-to-leg bioelectrical impedance may be a viable alternative field assessment technique that is comparable to skinfolds. The small differences in percent fat between the two techniques may have limited practical significance in school-based health-fitness settings.  相似文献   

13.
A cross-sectional study of 502 Bengalee boys aged 10-16 years of Nimta, North 24 Parganas, West Bengal, India, was undertaken to study regional adiposity, body composition and central body fat distribution. The subjects were classified into seven age groups: 10-10.9 years (n = 74), 11-11.9 (n = 53), 12-12.9 (n = 87), 13-13.9 (n = 116), 14-14.9 (n = 58), 15-15.9 (n = 57), 16-16.9 (n = 57). In general, there was a significant linear increasing trend from 10 to 16 years for all the anthropometric variables. There was a net increase of 30.5 cm and 22.8 kg in mean height and weight, respectively, between 10 and 16 years of age. Mean BMI increased by 3.7 kg/m2 during the same period. Among circumferences, the largest increase was in hip followed by chest while the smallest increase was in mid upper arm, between 10 and 16 years of age. Subscapular skinfold showed the largest increase followed by abdomen and suprailiac skinfolds, while the increase was least in forearm skinfold. Significant linear increasing trend was observed for all the body composition measures. The largest increase in percent of body fat (PBF) was observed between ages 10 and 11 years while mean fat mass (FM), fat free mass (FFM) and fat mass index (FMI) increased the most between 14 to 15 years. However, an overall decreasing trend was observed, in mean waist-to-hip ratio (WHR) from 10 to 16 years. Boys aged 10 years had the highest mean WHR while those aged 15 years had the lowest mean WHR. There was an increase in mean WHR among 16 years old boys.  相似文献   

14.
In recent studies, a relationship between both low body fat and low thicknesses of selected skinfolds has been demonstrated for running performance of distances from 100 m to the marathon but not in ultramarathon. We investigated the association of anthropometric and training characteristics with race performance in 63 male recreational ultrarunners in a 24-hour run using bi and multivariate analysis. The athletes achieved an average distance of 146.1 (43.1) km. In the bivariate analysis, body mass (r = -0.25), the sum of 9 skinfolds (r = -0.32), the sum of upper body skinfolds (r = -0.34), body fat percentage (r = -0.32), weekly kilometers ran (r = 0.31), longest training session before the 24-hour run (r = 0.56), and personal best marathon time (r = -0.58) were related to race performance. Stepwise multiple regression showed that both the longest training session before the 24-hour run (p = 0.0013) and the personal best marathon time (p = 0.0015) had the best correlation with race performance. Performance in these 24-hour runners may be predicted (r2 = 0.46) by the following equation: Performance in a 24-hour run, km) = 234.7 + 0.481 (longest training session before the 24-hour run, km) - 0.594 (personal best marathon time, minutes). For practical applications, training variables such as volume and intensity were associated with performance but not anthropometric variables. To achieve maximum kilometers in a 24-hour run, recreational ultrarunners should have a personal best marathon time of ~3 hours 20 minutes and complete a long training run of ~60 km before the race, whereas anthropometric characteristics such as low body fat or low skinfold thicknesses showed no association with performance.  相似文献   

15.
This investigation examined the accuracy of the BOD POD on a group of Division I collegiate track and field female athletes (N = 30). Hydrostatic weighing (HW) was used as the gold standard method. Body density (Db) values obtained from the BOD POD (Db BP) were compared with those determined by HW (Db HW). Both Db values were converted to percent body fat (%BF) using the Siri equation for comparison. Percent body fat values obtained from the BOD POD (BF BP) were also compared with those obtained from dual-energy X-ray absorptiometry (DXA, BF DXA) and skinfold (SF, BF SF). The validity of the BOD POD was assessed using repeated-measures analysis of variance (ANOVA), and the relationship between the methods was examined through Pearson correlation. Average Db BP was 0.00890 g x cm(-3) lower (p < 0.05) than Db HW, resulting in a significant overestimation of %BF (p < 0.05) by the BOD POD. Values for BFDXA and BFBP also differed significantly (p < 0.05). On the other hand, BFSF and BF BP were not significantly different. The correlation between percent body fat values obtained from HW (BFHW) and BF BP was good (r = 0.88, SEE = 2.30) as well as between BF SF and BF BP (r = 0.85, SEE = 2.05). Conversely, the correlation between BFDXA and BF BP was poor (r = 0.25, SEE = 5.73). The strong correlation between BF BP and BF HW presented here suggests that the BOD POD has the potential to be used as a body composition analysis tool for female athletes. The advantages of the BOD POD over HW encourage further investigation of this instrument. However, the fact that the BOD POD and SF results did not differ significantly might suggest that the SF could be used in its place until a better rate of accuracy for this instrument is established.  相似文献   

16.
Ponderal somatograms evaluate body size and shape by converting muscular (shoulders, chest, biceps, forearm, thigh, calf) and nonmuscular (abdomen, hips, knee, ankle, wrist) girths into ponderal equivalent (PE) values. Anthropometric measurements, including stature, body mass, girths, and percent body fat by densitometry were collected in 54 Division III football players in preseason camp (fall) and at the beginning (winter) and end (spring) of the team strength and conditioning program. PE values were calculated for each girth as PE, kg = (girth, cm / k)(2) x stature, dm, where k = k constant from Behnke's reference man. PE values were compared to body mass to indicate overdevelopment (PE > body mass) and underdevelopment (PE < body mass) at specific girth sites. From fall to winter, body mass (+1.6 kg), percent fat (+1.3%), fat mass (+1.6 kg), nonmuscular abdominal and hip girths (+2.1 cm, +1.5 cm), and PE values (+5.3 kg, +2.6 kg) increased significantly (p < 0.05). From winter to spring, percent fat (-1.5%), fat mass (-1.4 kg), nonmuscular abdominal girth (-1.0 cm), and PE value (-2.5 kg) decreased significantly (p < 0.05). Fat-free mass (+1.5 kg), muscular biceps girth (+0.4 cm), and PE value (+2.6 kg) increased significantly (p < 0.05) from winter to spring. Ponderal somatogram muscular components were generally overdeveloped, with the greatest overdevelopment at the biceps in fall (+14.7 kg), winter (+14.9 kg), and spring (+17.4 kg). Nonmuscular components generally were underdeveloped, except abdomen and hips that were overdeveloped. The abdomen remained the greatest nonmuscular overdevelopment in fall (+6.8 kg), winter (+10.5 kg), and spring (+7.9 kg). Ponderal somatograms provide a relatively simple, practical method to track specific changes in body size and shape over time.  相似文献   

17.
The aim of this study was to determine the accuracy of dual‐energy X‐ray absorptiometry (DXA)‐derived percentage fat estimates in obese adults by using four‐compartment (4C) values as criterion measures. Differences between methods were also investigated in relation to the influence of fat‐free mass (FFM) hydration and various anthropometric measurements. Six women and eight men (age 22–54 years, BMI 28.7–39.9 kg/m2, 4C percent body fat (%BF) 31.3–52.6%) had relative body fat (%BF) determined via DXA and a 4C method that incorporated measures of body density (BD), total body water (TBW), and bone mineral mass (BMM) via underwater weighing, deuterium dilution, and DXA, respectively. Anthropometric measurements were also undertaken: height, waist and gluteal girth, and anterior‐posterior (A‐P) chest depth. Values for both methods were significantly correlated (r2 = 0.894) and no significant difference (P = 0.57) was detected between the means (DXA = 41.1%BF, 4C = 41.5%BF). The slope and intercept for the regression line were not significantly different (P > 0.05) from 1 and 0, respectively. Although both methods were significantly correlated, intraindividual differences between the methods were sizable (4C‐DXA, range = ?3.04 to 4.01%BF) and significantly correlated with tissue thickness (chest depth) or most surrogates of tissue thickness (body mass, BMI, waist girth) but not FFM hydration and gluteal girth. DXA provided cross‐sectional %BF data for obese adults without bias. However, individual data are associated with large prediction errors (±4.2%BF). This error appears to be associated with tissue thickness indicating that the DXA device used may not be able to accurately account for beam hardening in obese cohorts.  相似文献   

18.
This study evaluated the validity and reliability of the BodyMetrix™ BX2000 A-mode ultrasound for estimating percent body fat (%BF) in athletes by comparing it to skinfolds and the BOD POD. Forty-five (22 males, 23 females) National Collegiate Athletic Association (NCAA) Division-I athletes volunteered for this study. Subjects were measured once in the BOD POD then twice by two technicians for skinfolds and ultrasound. A one-way repeated-measures ANOVA revealed significant differences between body composition methods (F = 13.24, p < 0.01, η² = 0.24). This difference was further explained by a sex-specific effect such that the mean difference between ultrasound and BOD POD was large for females (~ 5% BF) but small for males (~ 1.5% BF). Linear regression using the %BF estimate from ultrasound to predict %BF from BOD POD resulted in an R2 = 0.849, SEE = 2.6% BF and a TE = 4.4% BF. The inter-rater intraclass correlation (ICC) for skinfold was 0.966 with a large 95% confidence interval (CI) of 0.328 to 0.991. The inter-rater ICC for ultrasound was 0.987 with a much smaller 95% CI of 0.976 to 0.993. Both skinfolds and ultrasound had test-retest ICCs ≥ 0.996. The BX2000 ultrasound device had excellent test-retest reliability, and its inter-rater reliability was superior to the skinfold method. The validity of this method is questionable, particularly for female athletes. However, due to its excellent reliability, coaches and trainers should consider this portable and easy to use A-mode ultrasound to assess body composition changes in athletes.  相似文献   

19.
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. Furthermore, histograms of those measurements tended to show a significant skewness for low values and deviated from the normal probability curve (p less than 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 measurements (triceps, suprailiac, height, and weight) were selected by the Wherry-Doolittle method.  相似文献   

20.
The objectives of this study were to assess for elderly Germans the validity of existing equations for predicting body cell mass (BCM) and to develop from single- and multifrequency bioimpedance (SFBIA, MFBIA) models new prediction equations. In a data-splitting approach, validation and cross-validation were performed in 160 healthy elderly (60- to 90-yr) subjects. BCM was determined using a tetrapolar bioimpedance analyzer (800 microA; 4 fixed frequencies: 1, 5, 50, and 100 kHz; electrodes placed to hand, wrist, ankle, and foot) and whole body (40)K counting as a reference method. New prediction equations were derived by multiple stepwise regression analysis. The Bland-Altman procedure was used for methods comparison. Relative to whole body counting, the manufacturer's equation overestimated BCM by 9% in men (P < 0.0001, paired t-test) and 4% in women (P = 0.002). Compared with the manufacturer's equation, the newly derived equations (r = 0.92, RMSE = 6-9%) improved accuracy (pure error = 13 vs. 7-8%) and reduced bias and limits of agreement. SFBIA and MFBIA equations did not differ in precision or accuracy. We conclude that the newly derived equations improved BCM estimates in the elderly compared with existing equations. There was no advantage of MFBIA over SFBIA equations.  相似文献   

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