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1 Exercise and Sports Science Department, Vanguard University of Southern California, Costa Mesa, California 92626; and 2 Center for Exercise and Applied Human Physiology, University of New Mexico, Albuquerque, New Mexico 87131
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ABSTRACT |
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 TOP
 ABSTRACT
 INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Commonly used two-component model conversion formulas
that estimate relative body fat (%BF) from body density (Db) were
cross-validated on a heterogeneous sample of black men
(n = 30; age = 19-45 yr). A four-component
model was used to obtain criterion measures of %BF, and linear
regression and analysis of individual residual scores were conducted to
assess the predictive accuracy of the formulas under investigation. The
two-component formula commonly used to estimate %BF of black men
(Schutte JE, Townsend EJ, Hugg J, Shoup RF, Malina RM, and Blomqvist
CG. J Appl Physiol 56: 1647-1649, 1984)
significantly (P 
0.01) and systematically (87% of
sample) overestimated %BF (
1.28%); thus we developed the following
two-component Db conversion formula: %BF = [(4.858/Db) 4.394] × 100. Because our formula was derived from a four-component
model and a larger, more heterogeneous sample than the commonly used
two-component formula, we recommend using it to convert Db to %BF for
black men. Additionally, there was good agreement between dual-energy X-ray absorptiometry and the four-component model, making this a
suitable alternative for estimating the %BF of black men.
multicomponent body composition; African American; race; ethnicity
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INTRODUCTION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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BLACK MEN HAVE EXHIBITED an increased risk for obesity-related chronic diseases, including cardiovascular disease, cerebrovascular disease, diabetes, and osteoarthritis (10, 15). Additionally, body composition measurements are often used to recommend desirable body weights for athletes, and black men constitute a large portion of today's collegiate and professional athletic population. Furthermore, some jobs, such as those in the military and law enforcement, require employees to maintain certain body fat standards. Therefore, an accurate body composition assessment may be pertinent to the health, athletic performance, and employment of black males.
Traditionally, the classic two-component (2-C) models of Siri (24) and Brozek et al. (3), which separate the body mass (BM) into fat mass and fat-free mass, have been used to obtain reference measures of body composition. These models assume that the density of the fat-free body (FFBd) is 1.100 g/ml, and the proportions and densities of the components that constitute the fat-free mass (water, protein, and minerals) are constant for all individuals (3). However, these assumptions were derived from cadaver analysis of a small sample of white men (3), and it is now widely recognized that these assumptions do not hold true for black men. Numerous differences in body composition exist between black and white men, most notably a greater protein content, bone mineral content (BMC), and bone mineral density (BMD) for black men (12, 26). These differences result in a greater FFBd for black men and, therefore, a systematic underestimation of relative body fat (%BF) when the 2-C conversion equations of Siri or Brozek et al. are used.
Schutte et al. (22) calculated a greater FFBd (1.113 g/ml)
for black men and developed the following 2-C model formula to convert
body density (Db) to %BF for this population: %BF = [(4.374/Db) 3.928] × 100. This conversion formula has been
recommended (7) and is generally used for estimating the
%BF from Db for black men. However, its validity and generalizability
are suspect because 1) the conversion formula has not been
cross-validated, 2) total body water (TBW), rather than a
complete multicomponent model, was used as the reference method for
estimating %BF, and 3) the conversion formula was based on
data from a small, homogeneous sample of young, black, college-aged men
(n = 15).
Therefore, the purpose of this study was to cross-validate the Schutte et al. (22) equation for black men by using a four-component (4-C) body composition model that estimates %BF from total Db corrected for relative TBW and total body bone mineral (TBBM). Additionally, the validity of the 2-C conversion formulas of Siri (24) and Brozek et al. (3), as well as the Pace and Rathbun (16) formula for estimating %BF from TBW, and the %BF estimate obtained from dual-energy X-ray absorptiometry (DXA) were evaluated on this sample of black men.
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METHODS |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Subjects and preliminary procedures. Thirty black men, ages 19-45 yr, volunteered to participate in this study. Subjects were recruited from the Albuquerque area via word-of-mouth, newspaper advertisements, flyers distributed throughout the University and to health/fitness clubs, major corporations, churches, community centers, and at major public events. Each participant completed questionnaires on health history, physical activity (18), ethnic background, and socioeconomic data for descriptive purposes. Subjects had to self-report that both parents were black to be enrolled in this study. All subjects underwent a physical examination by a physician and were deemed to be in good health. The participants were informed of the purpose, procedures, risks, and benefits of the study before signing an informed consent. To control for the influence of physical activity and food and drug intake on body composition measures, subjects stayed overnight and were given a controlled dinner in the General Clinical Research Center of the University Hospital. The Human Research Review Committees of the University Hospital and the University of New Mexico approved this study.
BM and height. With the men in briefs only, BM was measured twice, to the nearest 0.01 kg, on a calibrated electronic scale (Bod Pod, Life Measurement Instruments, Concord, CA), and the average of the two values was used for subsequent calculations. Height was measured twice, to the nearest 0.1 cm, by using a stadiometer (Holtain, Crymych, Dyfed Wales, UK), with the average of the two measurements recorded. This measurement was taken with participants at midinspiration, standing erect, and arms hanging freely at the sides.
Deuterium oxide dilution. TBW was determined by using the deuterium oxide (D2O) dilution technique (20). Schoeller (19) reported the accuracy of the isotope dilution method for measuring TBW to be ~1%, and the precision when using isotope ratio mass spectrometry, as was done in this study, to be between 1% and 2%.
After an overnight fast (7-h postprandial), subjects gave a 1.0-ml saliva sample to establish baseline D2O levels. Each participant then ingested a 10-g dose of D2O mixed in 300 ml of deionized water, as described by Khaled et al. (9). As recommended by Schoeller et al. (20), there was a 4-h D2O equilibration period, after which a second 1.0-ml saliva sample was collected. In the interim between saliva samples, the subjects completed the other body composition assessments included in this study. Research shows that there is not a statistically significant difference in TBW when measured from saliva, serum, or urine (20). The saliva samples were frozen (20°C) for later analysis. The
absorption of D2O was determined by using isotope ratio
mass spectrometry (21). It was assumed that the
D2O dilution space was 4% larger than TBW, due to the
proton exchange between tracer and proteins and carbohydrates in the
body (20); thus the value obtained from the mass
spectrometry analysis was divided by 1.04 to obtain the corrected TBW
value. This corrected TBW value was used in the multicomponent model
(4) and to estimate %BF from TBW using the 2-C model
equation of Pace and Rathbun (16).
DXA. TBBM was determined by scanning the subjects with a pencil-beam DXA (Lunar DPX, Lunar Radiation, Madison, WI). Johnson and Dawson-Hughes (8) studied the precision of DXA for measuring TBBM. The coefficients of variation for immediate retest and long-term precision, measured 9 mo later, were 0.8 and 1.2%, respectively.
The DXA was calibrated daily with the manufacturer's "standard block" bone-simulating substance of known composition and attenuating capacity and weekly with an aluminum spine phantom. A licensed radiologic technologist performed all scans. From a supine position, the men were scanned using the medium speed scan mode (20 min), unless body thickness exceeded 27 cm, as measured with an anthropometer from the supine position. In such cases, the slow speed scan (40 min) was used. The DXA measurement is thought to represent bone ash, so TBBM was calculated by dividing the DXA value by 0.9582, the assumed fraction of bone mineral comprising ash (3). The nonosseous mineral-to-bone ash ratio was assumed to be 0.23048, and TBBM was subsequently calculated as the sum of the bone mineral and nonosseous components (3). Lunar software (version 3.6Z) also provided an estimate of %BF based on an extrapolation of fatness from the ratio of soft tissue attenuation of two X-ray energies in pixels not containing bone (13).Hydrodensitometry. Total body volume and Db were calculated from measures of BM and underwater mass using hydrostatic weighing (HW) at residual lung volume (RV). RV was estimated by using a helium dilution technique (14) via closed-circuit spirometry, with a 9-liter Collins helium analyzer (Warren E. Collins, Braintree, MA), with the participant seated out of the water. A minimum of three trials was done, with the two closest readings within 100 ml being averaged and used to correct total body volume measured from HW. To minimize error, the same experienced technician conducted all lung volume measurements and performed all RV calculations.
A load cell system (Precision Biomedical, State College, PA), integrated to an analog signal acquisition system (Biopac Systems, Goleta, CA) and a personal computer, was used to measure underwater weight. The analog signal was acquired at 200 Hz and processed using commercially available software (AcqKnowledge, Biopac Systems, Goleta, CA). For this assessment, the men assumed a hands and knees position on the load cell platform. A forced expiratory reserve volume maneuver was performed as the participant lowered his head below the surface of the water to be completely submerged. The underwater weight was obtained by averaging the flattest region of the waveform over ~1 s after complete expiration. Three trials within 100 g of each other were averaged and used as the underwater weight for calculation of total body volume and Db (2).Statistical analysis.
Before the study was conducted, a power analysis was performed to
determine the number of participants needed to appropriately assess the
validity of the equations under cross-validation. It was estimated that
a sample size of 30 was adequate to distinguish a difference of 1.85%
BF between equations (e.g., Schutte et al. vs. 4-C) with 80% power and
level of significance (
) = 0.05. After data collection,
the power analysis was performed again. The correlation between
%BF4-C and %BFSchutte was higher than expected (r = 0.97), allowing for a mean difference of
0.9% BF to be detected with 80% power and = 0.05.
0.80) and shared variance
(r2) should exist between the criterion and
predicted %BF. 3) The SE of estimate (SEE) and total error
(E) of the equation should not exceed 3.5% BF. 4)
There should be no systematic prediction error across levels of body
fatness, as evidenced by the correlation (ry,res) between the reference measure and the
residual scores (e.g., %BF4-C %BFSchutte). 5) The slope of the regression
line should not differ significantly from 1.0, and the intercept should not be significantly different from zero.
Additionally, residual scores (e.g., %BF4-C %BFSchutte) were analyzed by using a modified Bland and
Altman (1) plot to determine the percentage of
participants whose predicted score was correctly estimated within
±3.5% BF. The Bland and Altman method is typically used to represent
the amount of data that falls between ±2 SD from the mean. However,
rather than plot the data as means ± 2 SD, we represented the
number of subjects who were estimated within ±3.5% BF of the 4-C
model, as this value corresponds to Lohman's (11) SEE
criteria for acceptability. For this analysis, the reference score and
predicted score were averaged and plotted against each participant's
residual score (e.g., %BF4-C %BFSchutte).
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RESULTS |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Descriptive characteristics.
The physical characteristics of the sample (n = 30) are
presented in Table 1. All variables were
normally distributed with no potential outliers
(z-scores < 3.29); therefore, all subjects were
included in subsequent analysis. As evidenced by the data in the table,
the sample was rather heterogeneous. The subjects ranged in age from 19 to 45 yr (mean age of 31.97 ± 7.71 yr), with an average height
and BM of 180.32 ± 7.47 cm and 84.15 ± 14.98 kg,
respectively. The %BF4-C of the sample ranged from 3.52 to
36.60% (mean of 15.79 ± 6.96%).
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Cross-validation results.
Results of the cross-validation analyses are presented in Table
2. The relationships between the 4-C
model and all formulas were strong (P 0.01), but DXA was
the only method for which the average %BF did not differ significantly
from the criterion measure. Because the HW formulas are simply linear
transformations of the Db to %BF and there is a perfect correlation
between them, they all share the same relationship (r = 0.98) and SEE (1.56% BF) with the 4-C model but have different slopes
and intercepts. The relationships of the %BF estimated from the 2-C
model HW conversion formulas and the %BF obtained from the 4-C model
are depicted in Fig. 1, A-C.
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0.01). On average, the Schutte et al.
(22) formula overestimated %BF by 1.28%, whereas the
Siri (24) and Brozek et al. (3) formulas
underestimated %BF by 1.94% and 1.75%, respectively. Close
inspection of the individual residual scores (Fig.
2, A-C) revealed that the
%BF of 87% of the sample was overestimated by the Schutte et al.
(22) formula, with the same percentage of individuals
underestimated by the Siri formula (24) and 90%
underestimated with the Brozek et al. formula (3). Most of
these residuals were small, with only two subjects being overestimated
by >3.5% BF using the Schutte et al. formula and three and four
subjects being underestimated by >3.5% BF with the Brozek et al. and
Siri formulas, respectively. Nevertheless, there was a consistent trend
for overestimation of %BF for black men using the Schutte et al.
formula and underestimation of %BF for black men using the Siri and
Brozek et al. formulas.
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0.01) overestimated %BF in this
sample by an average of 1.71%. Although 90% of the sample was
accurately estimated within ±3.5% BF, 87% of the subjects had
negative residual scores (%BF4-C %BFTBW) indicating a trend for overestimating the %BF of
black men with this conversion formula (Fig. 2D).
The relationship between the %BF estimated from DXA and that obtained
from the 4-C model is illustrated in Fig.
3. The mean difference in %BF between
these two methods was small (0.28%) and not significant. DXA
accurately estimated 87% of the subjects within ±3.5% BF, with an
equal number of subjects being over- and underestimated (Fig.
4).
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DISCUSSION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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The Friedl et al. (4) 4-C model equation {%BF = [(2.559/Db) 0.734 (TBW/BM) + 0.983 (TBBM/BM) 1.841] × 100} was used as the criterion measure of %BF in this
study. Although there are several published multicomponent models, this
one was chosen because it includes TBBM in the equation rather than
total body mineral that requires an extra estimation calculation. We
were able to use the same DXA model and method of calculating TBBM as
Friedl et al. Friedl et al. noted that the results obtained from their
equation were very similar to those from other 4-C models. The
potential exists for the propagation of errors from multiple
measurements when using 4-C models. However, Friedl et al.
(4) showed that the improved accuracy of measuring, rather than estimating, TBW and TBBM values exceeds the additive measurement errors, thus improving the accuracy of estimating fat over traditional 2-C models.
As expected, the Siri (24) and Brozek et al. (3) formulas consistently underestimated the %BF of the black men in this study. The derivation of these formulas for converting Db to %BF was based on assumptions about the proportions and densities of the FFB of white men. A FFBd of 1.100 g/ml was assumed. However, it is well documented that the BMC, BMD, and protein content of black men may be greater than that of white men, resulting in a greater FFBd (12, 26). If the FFBd of black men is indeed >1.100 g/ml, then an underestimation in %BF using either of these formulas is to be expected.
The conversion formula of Schutte et al. (22) was an attempt at correcting for the greater FFBd of black men and the subsequent underestimation of %BF when Db was applied to 2-C conversion formulas appropriate for white men (3, 24). However, the results from this study indicate that the %BF of black men is consistently overestimated using that formula. Thus the actual FFBd of black men is likely to be somewhere between the 1.100 g/ml assumed for white men and the 1.113 g/ml Schutte et al. (22) estimated for black men.
In the present sample, the average relative TBW, total body mineral,
and total body protein of the FFB were 71.73, 6.81, and 21.46%,
respectively. Whereas the water and mineral components were obtained by
isotope dilution and DXA, respectively, the protein portion was simply
estimated as the remainder of the FFB [protein = 100% (water% + mineral%)]. Using the respective densities for water,
mineral, and protein, the overall FFBd was estimated to be 1.10570 g/ml
in the present sample. Assuming the density of fat is 0.9007 g/ml and
the average FFBd is 1.10570 g/ml, the following conversion formula was
derived for black men: %BF = [(4.858/Db) 4.394] × 100. This formula produced a mean difference of only 0.03% BF compared
with %BF4-C. Furthermore, 97% of the subjects were
accurately estimated within ±3.5% BF, and there was no systematic
error or prediction bias
(ry,res = 0.23) for this
race-specific conversion formula (Fig.
5). However, accuracy of this new 2-C
model may be inflated because it was derived from the 4-C model values
to which it was compared; thus we strongly emphasize that this new
conversion formula should be cross-validated on an independent sample.
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Inserting the mean Db of this sample (1.06744 g/ml) into the new
conversion formula yields an average value of 15.71% BF. The same Db
entered in the Siri (24) and Schutte et al.
(22) conversion formulas yields %BF values of 13.73 and
16.97%, respectively. These between-formula differences in %BF are
reduced at lower Db values but increased at higher Db values. Thus, for
obese subjects, all the Db conversion formulas will yield similar
results, but, for very lean subjects, the differences in %BF between
equations are proportionately much larger. This relationship is
illustrated in Fig. 6.
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There are several plausible explanations for the differences in conversion formulas and FFBd observed in the present study compared with that reported by Schutte et al. (22). First, the black men of the present study varied widely in age (19-45 yr) and BF (3.52-36.60% BF4-C), as well as physical activity level and socioeconomic status. In contrast, Schutte et al. (22) used a relatively homogeneous sample of college students. That sample was both younger (20.3 ± 1.70 yr) and leaner (12.1 ± 5.81% BFTBW) than the subjects in the present study. No reference was made to the physical activity status of the other study's subjects, but a young, lean sample may also have been very athletic, with increased BMC and BMD values. This could partially account for the greater FFBd reported by Schutte et al. (22).
Also, Schutte et al. (22) used the hydrometry formula of Pace and Rathbun (16) to convert TBW to %BF for a reference measure. A multicomponent model, such as the one used in the present study, is less likely to be affected by large variations in hydration. Data from the present study indicate that the TBW method might slightly overestimate %BF in black men. If this were the case in the Schutte et al. study, the difference they obtained between %BF estimated from densitometry and hydrometry would have been less, thereby reducing their estimation of FFBd.
It is logical that the actual FFBd of black men is closer to the 1.10570 g/ml obtained from the present data rather than the 1.113 g/ml reported by Schutte et al. (22). Schutte and co-workers noted that a FFBd of 1.113 g/ml would require a BMC that is 36% greater than that assumed for white men and acknowledged that this is unlikely, given that past cadaver analysis showed only a 10-20% increase in BMC for black men. Indeed, in a study of 24 black and 24 white men matched for age, height, and weight, Gerace et al. (6) reported that the BMC measured by dual photon absorptiometry of black men was only 8.7% greater than that of white men. Furthermore, the sample size of the black men in the present study was double that of the sample used by Schutte et al. Due to the larger sample size, greater heterogeneity of our sample, older average age, and higher average %BF, the present study may be more representative of the black male population; thus the results may have a greater generalizability.
TBW, estimated from D2O dilution and mass spectrometry, was converted to %BF using the Pace and Rathbun (16) formula. The values for absolute TBW and TBW relative to the FFB from this study were similar to those found in other studies (4, 5, 22, 23, 27). The average TBW for the black men in the present study (50.35 ± 6.77 l) was greater than that reported by Schutte et al. (46.1 ± 4.63 l), but average BM was also greater for the subjects in the present study (84.15 ± 14.98 kg vs. 72.0 ± 8.99 kg).
Overall, this method and formula produced %BF results very similar to what was obtained with the 4-C model. However, although the difference was not large, there was a consistent overestimation of %BF using the Pace and Rathbun (16) conversion formula. This overestimation was the result of a difference between the assumed and actual proportions of water in the FFB. Because the hydrometry method is based solely on the assumption of a constant value for the hydration fraction of the FFB, any deviation from this value will result in an over- or underestimation of %BF. The Pace and Rathbun formula assumes the hydration fraction of the FFB to be 73.2%, but, on average, the actual percentage of water in the FFB from this study was only 71.73%. Additionally, the hydration fraction of 87% of the subjects in this study was below 73.2% accounting for the consistent overestimation of %BF by the Pace and Rathbun formula.
The mean hydration fraction of the FFB of the subjects in the present study was very similar to the 71.94% proposed by Siri (24). However, Siri also estimated a biological variability of 2% in the water content of the FFB and noted that values from 67 to 74% are common. The hydration fractions of the FFB in the present study ranged from 69.7 to 75.6% with a mean of 71.73 ± 1.32%. Other studies that have used a multicomponent model to obtain reference FFB for men have reported mean hydration fractions of 73.32 ± 2.19 (5) and 72.6 ± 1.3% (4), with ranges of 69.4-78.4% and 71.1-74.2%, respectively. As long as the variance in the hydration fraction of the FFB remains small and the TBW-to-fat-free mass ratio is close to the assumed value of 73.2%, the hydrometry method with the Pace and Rathbun (16) formula will accurately estimate a sample within the ±3.5% BF standard. However, with large interindividual variations in the proportion of water in the FFB, there is the potential for substantial individual errors in the estimation of %BF.
Mean %BF was estimated better by DXA than any of the other conversion
formulas or reference methods. On average, DXA overestimated %BF by
only 0.28%. A similar level of accuracy was also observed in other
studies that compared 2-C reference methods to a 4-C model (4, 5,
17). These research teams reported similarly small mean
differences in the %BF estimated from DXA and 4-C models ranging from
0.4 to 1.3%. Furthermore, DXA was the only reference measure that
did not consistently over- or underestimate %BF in this sample of
black men (Fig. 4). The Siri (24) and Brozek et al.
(3) formulas consistently underestimated %BF, whereas the
formulas of Schutte et al. (22) and Pace and Rathbun
(16) consistently overestimated %BF. Thus the present
study is in agreement with the findings of Friedl et al.
(4), Fuller et al. (5), and Prior et al.
(17), who concluded that DXA is a better predictor of %BF
than HW or TBW.
It is not surprising that DXA produced the best estimation of %BF compared with the other reference methods in this sample of black men. Based on a review of the literature (26), a primary difference in body composition between black and white men is the greater BMC and BMD found in black men. Whereas the densitometry and hydrometry methods rely on assumptions about BMC and BMD, DXA directly measures these variables. Thus DXA will account for any race-specific variation in BMC and BMD that results in a FFBd different from the assumed value.
In conclusion, we have shown that the hydrodensitometry conversion
formulas developed from the cadaver analyses of white men consistently
underestimate the %BF of black men but that the race-specific conversion formula of Schutte et al. (22) consistently
overestimates the %BF of black men. By using a multicomponent body
composition model on a heterogeneous group of black men, we calculated
the FFBd of black men as 1.10570 g/ml. Subsequently, we developed a 2-C
model formula to convert Db to %BF for black men {%BF = [(4.858/Db) 4.394] × 100}. We recommend using this formula
for estimating the %BF of black men aged 19-45 yr from
hydrodensitometry; however, we suggest that it be cross-validated on
other independent samples of black men. Additionally, although the SEE
for DXA is greater than the 2-C HW formulas, DXA appears to be a
suitable alternative to HW for the estimation of %BF of black men.
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ACKNOWLEDGEMENTS |
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We thank Dr. David James for conducting prescreening physicals and admitting subjects into the General Clinical Research Center. Special thanks to Ann Gibson and Donna Lockner, the General Clinical Research Center, and the Clinical Nutrition Laboratory personnel for assistance with data collection.
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FOOTNOTES |
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Research was supported by the General Clinical Research Center at the University of New Mexico (National Center for Research Resources Grant 5M01-RR-00997), the Office of Graduate Studies (Research Project and Travel Grant), and the Graduate and Professional Students Association (Student Research Allocation Committee Grant) of the University of New Mexico.
Address for reprint requests and other correspondence: D. R. Wagner, Exercise and Sports Science Dept., Vanguard Univ. of Southern California, 55 Fair Dr., Costa Mesa, CA 92626 (E-mail: dwagner{at}vanguard.edu).
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Received 17 November 1999; accepted in final form 28 August 2000.
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REFERENCES |
|---|
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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1.
Bland, JM,
and
Altman DG.
Statistical methods for assessing agreement between two methods of clinical measurement.
Lancet
1:
307-310,
1986[ISI][Medline].
2.
Bonge, D,
and
Donnelly JE.
Trials to criteria for hydrostatic weighing at residual volume.
Res Q Exerc Sport
60:
176-179,
1989[ISI][Medline].
3.
Brozek, J,
Grande F,
Anderson JT,
and
Keys A.
Densitometric analysis of body composition: revision of some quantitative assumptions.
Ann NY Acad Sci
110:
113-140,
1963.
4.
Friedl, KE,
DeLuca JP,
Marchitelli LJ,
and
Vogel JA.
Reliability of body-fat estimations from a four-component model by using density, body water, and bone mineral measurements.
Am J Clin Nutr
55:
764-770,
1992
5.
Fuller, NJ,
Jebb SA,
Laskey MA,
Coward WA,
and
Elia M.
Four-component model for the assessment of body composition in humans: comparison with alternative methods and evaluation of the density and hydration of fat-free mass.
Clin Sci (Colch)
82:
687-693,
1992[Medline].
6.
Gerace, L,
Aliprantis A,
Russell M,
Allison DB,
Buhl KM,
Wang J,
Wang ZM,
Pierson RN,
and
Heymsfield SB.
Skeletal differences between black and white men and their relevance to body composition estimates.
Am J Hum Biol
6:
255-262,
1994.
7.
Heyward, VH,
and
Stolarczyk LM.
Applied Body Composition Assessment. Champaign, IL: Human Kinetics, 1996, p. 12.
8.
Johnson, J,
and
Dawson-Hughes B.
Precision and stability of dual-energy X-ray absorptiometry measurements.
Calcif Tissue Int
49:
174-178,
1991[ISI][Medline].
9.
Khaled, MA,
Lukaski HC,
and
Watkins CL.
Determination of total body water by deuterium NMR.
Am J Clin Nutr
45:
1-6,
1987
10.
Kumanyika, SK.
Special issues regarding obesity in minority populations.
Ann Intern Med
119:
650-654,
1993
11.
Lohman, TG.
Advances in Body Composition Assessment. Current Issues in Exercise Science Series. Champaign, IL: Human Kinetics, 1992, p. 44.
12.
Malina, RM.
Regional body composition: age, sex, and ethnic variation.
In: Human Body Composition, edited by Roche AF,
Heymsfield SB,
and Lohman TG.. Champaign, IL: Human Kinetics, 1996, p. 217-255.
13.
Mazess, RB,
Barden HS,
Bisek JP,
and
Hanson J.
Dual-energy X-ray absorptiometry for total-body and regional bone-mineral and soft-tissue composition.
Am J Clin Nutr
51:
1106-1112,
1990
14.
Motley, HL.
Comparison of a simple helium closed method with oxygen circuit method for measuring residual air.
Am Rev Tuber Pulm Dis
76:
601-615,
1957.
15.
National Center for Health Statistics.
Health, United States, 1998. Hyattsville, MD: Public Health Service, 1999, p. 281.
16.
Pace, N,
and
Rathbun EN.
Studies on body composition. III. The body water and chemically combined nitrogen content in relation to fat content.
J Biol Chem
158:
685-691,
1945
17.
Prior, BM,
Cureton KJ,
Modlesky CM,
Evans EM,
Sloniger MA,
Saunders M,
and
Lewis RD.
In vivo validation of whole body composition estimates from dual-energy X-ray absorptiometry.
J Appl Physiol
83:
623-630,
1997
18.
Ross, RM,
and
Jackson AS.
Exercise Concepts, Calculations, and Computer Applications. Carmel, IN: Benchmark, 1990, p. 109.
19.
Schoeller, DA.
Hydrometry.
In: Human Body Composition, edited by Roche AF,
Heymsfield SB,
and Lohman TG.. Champaign, IL: Human Kinetics, 1996, p. 25-43.
20.
Schoeller, DA,
Kushner RF,
Taylor P,
Dietz WH,
and
Bandini L.
Measurement of total body water: isotope dilution techniques.
In: 6th Ross Conference on Medical Research. Columbus, OH: Ross Laboratories, 1985, p. 24-29.
21.
Schoeller, DA,
van Santen E,
Peterson DW,
Dietz W,
Jaspan J,
and
Klein PD.
Total body water measurement in humans with 18O- and 2H-labeled water.
Am J Clin Nutr
33:
2686-2693,
1980
22.
Schutte, JE,
Townsend EJ,
Hugg J,
Shoup RF,
Malina RM,
and
Blomqvist CG.
Density of lean body mass is greater in Blacks than in Whites.
J Appl Physiol
56:
1647-1649,
1984
23.
Sheng, HP,
and
Huggins RA.
A review of body composition studies with emphasis on total body water and fat.
Am J Clin Nutr
32:
630-647,
1979
24.
Siri, WE.
Body composition from fluid spaces and density: Analysis of methods.
In: Techniques for Measuring Body Composition, edited by Brozek J,
and Henschel A.. Washington, DC: National Academy of Sciences, 1961, p. 223-244.
25.
Tabachnick, BG,
and
Fidell LS.
Using Multivariate Statistics. New York: HarperCollins, 1996, p. 66-70.
26.
Wagner, DR,
and
Heyward VH.
Measures of body composition in blacks and whites: a comparative review.
Am J Clin Nutr
71:
1392-1402,
2000
27.
Zillikens, MC,
and
Conway JM.
Estimation of total body water by bioelectrical impedance analysis in blacks.
Am J Hum Biol
3:
25-32,
1991.
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