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1 Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, Tennessee 38105; 2 Department of Physiology, University of Arizona, Tucson, Arizona 85721; 3 PPD Development, Inc., Austin, Texas 78704; 4 Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, Wisconsin 53706; 5 Synarc, Inc. and 7 Department of Epidemiology and Biostatistics, University of California-San Francisco, San Francisco, California 94105; 6 University of Pittsburgh, Pittsburgh, Pennsylvania 15261; 8 Institute for Research in Extramural Medicine, VU University Medical Center, 1081 BT Amsterdam, The Netherlands; and 9 National Institute on Aging, National Institutes of Health, Bethesda, Maryland 20892
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ABSTRACT |
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 TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES
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This study evaluated the accuracy with which the dual-energy X-ray absorptiometer (Hologic QDR 4500A) measured fat-free mass (FFM), fat mass (FM), and hydration of FFM. In a study of 58 men and women (ages 70-79 yr), the QDR 4500A was found to provide a systematically higher estimate of FFM and lower estimate of FM than a four-component model of body composition. A correction factor from this study was developed and applied to two other samples (n = 13 and 37). We found mean corrected levels of FFM and FM to be equivalent to that obtained by the four-component model or total body water. In addition, the hydration of the corrected FFM was closer to the established hydration level in adult samples and that obtained from the four-component model. These findings suggest that the current calibration of the fan-beam system of the Hologic QDR 4500A provides an overestimate of FFM and underestimate of FM compared with reference methods.
body composition; hydration of fat-free mass; four-component model of body composition; total body water; dual-energy X-ray absorptiometer
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INTRODUCTION |
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TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES
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RECENT DEVELOPMENTS IN dual-energy X-ray absorptiometry (DXA) hardware with fan-beam technology have led to new software development for body composition assessment predictive of body composition. The short assessment time of fan-beam technology for body composition analysis allows large samples to be included in clinical, epidemiological, and survey designs. In addition, this technology allows separation of the body mass into bone mass, fat mass (FM), and fat-free mass (FFM) and estimation of regional body composition. However, one of the limitations of fan-beam technology is the magnification of scanned structures as the distance from the X-ray source varies. Recent validation studies have tested the DXA fan-beam (DXAfan) approach with the four-component (4-C) model of body composition analysis (12, 14).
Further investigation of the DXA soft tissue calibration by our group has revealed a systematic bias between the DXA body composition results and several criterion methods, including the 4-C model and total body water (TBW) by deuterium dilution. Work by our group and others suggests that the calibration of the QDR 4500A produces higher total and regional FFM estimates compared with previous generations of Hologic whole body scanners (3) and compared with estimates based on alternative body composition methods (12, 14, 15). These three independent studies confirmed the overestimation of FFM and underestimation of FM and percent fat. Overestimation of FFM varied between 3 and 10%, depending on the validation cohort and criterion method.
Because of the systematic differences between fan-beam and pencil-beam body composition analysis, additional studies are warranted to assess the fan-beam approach. Our study used the 4-C model and DXAfan data to create a correction factor for the DXAfan. We then applied this to two other adult samples of different ages using DXAfan and pencil-beam (DXApencil) technology with a 4-C model and TBW as criterion methods. The results of the correction for FM (FMDXAfan) and FFM from DXAfan (FFMDXAfan) were evaluated against the criterion methods.
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MATERIALS AND METHODS |
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TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES
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Subjects
There were three samples included in these analyses. Sample 1 consisted of 30 men and 28 women, aged 70-79 yr, selected so that 25% had a body mass index (BMI) <25 kg/m2, 50% had a BMI of 25-30 kg/m2, and 25% had a BMI >30 kg/m2 (range 17.5-39.8 kg/m2), from the study by Visser et al. (15). There were 52 Caucasians and 6 African-Americans. All measurements on a subject were conducted on the same day after an overnight fast. (Two subjects were excluded from the original sample due to technical errors in underwater weighing.)Sample 2 is a subset of 13 from sample 1 that had an additional measurement of a DXApencil (Hologic QDR 2000) whole body scan. This group consisted of 5 men and 8 women with an age range of 70-75 yr and BMI range of 23.3-35.9 kg/m2. There were 11 Caucasians and 2 African-Americans.
In sample 3, 37 adults participating in various weight-loss regimens were recruited (14). The 2 men and 35 women (33 Caucasians and 4 African-Americans) ranged in age from 19 to 71 yr (mean ± SD = 43.2 ± 10.8 yr), with BMI ranging from 23.8 to 38.2 kg/m2.
Body Composition
FFM, FM, lean soft tissue mass (LSTM), and bone mineral content (BMC) were assessed by using the 4-C model and TBW. The 4-C model was used as the criterion with which to compare FFM obtained from DXA (FFMDXA) in samples 1 and 2. TBW was the criterion with which to compare FFMDXA in sample 3. Percent hydration of FFM was calculated as (FFM/TBW) × 100.Whole Body DXA
A Hologic model QDR 4500A fan-beam densitometer (DXAfan) and a QDR 2000 densitometer using the pencil-beam mode (DXApencil) were used to measure bone and body composition. LSTM, FM, BMC, and bone mineral density were assessed by using software version 8.21 for the fan beam and enhanced whole body software version 5.71 for the pencil beam. Scan positioning, acquisition, and analysis were standardized. All subjects had fan-beam scans. Pencil-beam scans were done on a subset of sample 2 (n = 13) and all of sample 3 (n = 37).4-C Model
The 4-C model by Lohman and Going (8) was used as the criterion method. This model requires measurements of body density, TBW, total body bone mineral mass, and body weight, and it takes into account interindividual variations in the water content and mineral content of the FFM. Body density was measured by using underwater weighing. Subjects wore a bathing suit. Water temperature was set at 32-35°C. When possible, 10 submersions with maximal exhalation were performed. The average of the five most consistent trials (difference, 0.02 kg) was used. Before submersion, residual lung volume was measured by using a Collins Respirometer (model SVR/PLUS, Braintree, MA). With the mouthpiece in place, subjects were asked to breathe normally until the spirometer equilibrated for collection of data on functional residual capacity. After equilibration, subjects performed a forced inhalation followed by a forced exhalation for collection of inspiratory and expiratory reserve capacity data, respectively. Residual volume was calculated as functional residual capacity minus expiratory capacity. Three separate tests were performed, and the average was used to adjust body volume.Body composition from the 4-C model was calculated by using the
following formula: body fat (%) = (2.747/D 
0.714 * W + 1.146 * M 2.0503) * 100, where D is body density
from underwater weighing, W is the water fraction of the body (TBW/body
weight), and M is the mineral fraction of the body [total body mineral
mass (TMM)/body weight]. TMM was calculated from measured total body
BMC in the skeleton by the DXAfan technology. To account
for the mineral in nonossesous tissue, total mineral from DXA was
multiplied by 1.23. The value was based on data coming from reference
man and original work by Brozek et al. (2). FFM was
calculated as body weight minus body fat. LSTM was calculated by
subtracting BMC from FFM.
TBW
TBW was assessed by deuterium dilution measured with mass spectroscopy (13). An oral dose of deuterium oxide (~50 g, 8.3 atom percent D2O) was measured to the nearest 0.01 g and administered to each participant after a 6- to 12-h fast. Plasma samples using a dry EDTA tube were collected before and 4 h after the isotope administration. Samples were stored frozen at20°C and analyzed in batches for deuterium. The deuterium
dilution space was calculated from the enrichment of deuterium in
plasma water in the 4-h sample compared with the predose sample.
Subjects were allowed a small amount of fluid at 1 h after the
dose, and corrections were made in those in whom intake exceeded 200 ml. TBW was calculated as deuterium dilution space (liters) divided by
1.042, yielding kilograms of TBW. (13) FFM obtained from
TBW (FFMTBW) was calculated as TBW/0.73 (kg), and FM
was calculated as scale weight minus FFMTBW (kg).
Statistical Analysis
Means and standard deviations were calculated for all measures of body composition, as well as for physical characteristics of the participants. Paired t-tests were used to determine absolute differences between two methods, with a P value of < 0.05 considered statistically significant. Linear regression analysis was used to compare the FFM obtained from the 4-C model (FFM4-C) or FFMTBW to FFMDXA by pencil beam (FFMDXApencil) and FFMDXAfan. The standard error of the estimate reported is the root mean square error. The method of Bland and Altman (1) was used to compare DXA with the criterion methods.| |
RESULTS |
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TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES
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Characteristics of the Study Population
The characteristics of three samples assessed for body composition are shown in Table 1. In sample 1, 58 persons provided information from the 4-C model and fan-beam system to evaluate the relationship between FFM4-C and FFMDXAfan. This sample reflects individuals between the ages of 70 and 80 yr and with a BMI ranging between normal weight to obese. Sample 2 was a subset of sample 1 and provided information from 13 individuals to compare FFM obtained from pencil-beam and fan-beam systems. Sample 3 provided information for 37 participants for both the fan and pencil-beam system and TBW. At baseline, the individuals represent a large age range, and their BMI classification included those with normal weight up through obese.
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Comparison of FFM4-C with FFMDXAfan
Sample 1.
The mean FFM4-C was 50.7 kg (Table 1), and
FFMDXAfan was 53.5 kg. The
FFMDXAfan was 5.5% higher than
FFM4-C (P < 0.0001). The results of
the FFMDXAfan regressed on
FFM4-C are presented in Fig.
1A (n = 58).
The intercept was not significantly different from zero, so the slope
was determined with a zero intercept. The slope of the regression
suggests that the DXAfan consistently overestimated FFM by
3.6% and indicates that the absolute error in FFMDXA
compared with FFM4-C increased progressively as FFM increased. When the differences between the uncorrected
FFMDXAfan (FFMDXAfan uncorrected) and
FFM4-C were plotted against the mean of the two
measurements, there was no association with an increase in FFM
(r = 0.16; P = 0.21) (Fig.
1B). The slope of the regression line between
FFMDXAfan and FFM4-C was
then applied as a correction factor to
FFMDXAfan to yield a corrected
FFMDXAfan (FFMDXAfan corrected). When the
differences between FFMDXAfan corrected and FFM4-C were plotted against the mean of the two
measurements, there was no association with increase in FFM
(r = 0.16; P = 0.22) (Fig.
1C). To evaluate if this correction factor was appropriate for FFMDXAfan, we examined the relationship
between FFMDXAfan corrected and
FFM4-C in sample 2 and
FFMDXAfan corrected and
FFMTBW in sample 3. These same analyses were
performed on the corrected FMDXAfan. To obtain
the corrected FMDXAfan, the total weight from DXA was subtracted from the corrected FFM. BMC was held constant in the
correction process.
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Body Composition and Hydration Status of FFM: Corrected and Uncorrected
Sample 2.
Total weight, FFM, LSTM, FM, TMM, percent TMM of FFM, and percent
hydration of FFM for those in sample 2 (n = 13) are presented in Table
2. Values for the components of body
composition are presented as obtained from the 4-C model, the
pencil-beam system, and the fan-beam system before (uncorrected) and
after correction (corrected) using the correction factor derived from
the 4-C model. There were no differences in total weight between
that obtained from the scale and from the fan and pencil-beam systems.
FFM4-C was higher than
FFMDXApencil, lower than
FFMDXAfan uncorrected, and not different
than FFMDXAfan corrected. There were no
differences in TMM obtained with the fan or pencil beam. The percent
hydration of FFMDXApencil was higher than
expected, and the FFMDXAfan uncorrected
was lower than the percent hydration obtained by the
FFM4-C. The hydration of
FFMDXAfan corrected (71.5 ± 2.1%)
was the same as FFM4-C (P > 0.05). On the contrary, compared with the 4-C model, FM was
estimated to be higher by the pencil beam, lower by the uncorrected fan
beam, and no different for the corrected fan beam. TMM was 6.4% higher
as assessed by the pencil-beam compared with the fan-beam system
(P < 0.0002). Compared with the percentage of TMM to
FFM4-C, the pencil beam yielded higher values and the
uncorrected fan-beam values were the same. Compared with the percent
hydration for FFM4-C, the FFMDXApencil was higher and the
FFMDXAfan uncorrected was lower than would
be expected. There were no differences in the percent hydration of
FFM4-C compared with that obtained from the FFMDXAfan corrected.
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Sample 3.
Total weight, FFM, LSTM, FM, TMM, percent TMM of FFM, and percent
hydration of FFM for those in sample 3 are presented in Table 3. Values are presented for body
composition obtained by using TBW, the pencil-beam system, and
the fan-beam system before (uncorrected) and after the correction
(corrected). Data are provided for the sample at baseline and after
3.4 ± 2.3 mo of follow-up. Subjects lost an average of 5.7 ± 4.5 kg over the 3-mo period. There were no differences in total
weight between that obtained from the scale and from the fan and
pencil-beam systems. At baseline, FFMTBW as the
criterion method was higher than
FFMDXApencil and lower than
FFMDXAfan uncorrected. In contrast,
compared with the FMTBW, FM was estimated to be
higher by the pencil beam and lower by the uncorrected fan beam. TMM
was higher when assessed by the pencil than by the fan beam. The
percentage of TMM to FFM was lower for uncorrected fan beam, and the
pencil beam was lower than that for FFM4-C. The percent
hydration of FFMDXApencil was higher than
that for the FFMDXAfan uncorrected. When
the uncorrected DXAfan measurements were corrected to the
4-C model, no difference was found between the criterion
FFMTBW and
FFMDXAfan corrected (Fig.
2). When the correlation analysis was
repeated, excluding the one outlier, the results were r = 0.04, P = 0.8. Similar findings for FFM,
FM, TMM, percent TMM of FFM, and percent hydration were obtained at the
follow-up visit (Table 3).
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DISCUSSION |
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TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES
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The present study found higher FFM (5.5%) as estimated from DXA fan beam than that estimated from the 4-C model (n = 58) in a sample of men and women between 70 and 80 yr of age. The proposed equation, FFM (kg) = 0.964 FFMDXAfan (kg), corrects DXAfan measurement to the 4-C model. By using a proportional correction, i.e., 2.5 kg for 70-kg FFM vs. 1.1 kg for 30-kg FFM, the equation corrects for the observed correlation between the difference between methods and the mean FFM (r = 0.16, P < 0.22). Applying this correction to two other samples, we found the mean levels of FFM to be equivalent to that obtained by the 4-C model or TBW. In addition, the hydration of corrected FFM is the same as obtained from the 4-C model. These findings suggest that the current calibration of the fan-beam system of the QDR 4500A provides an overestimate of FFM and underestimate of FM and our correction factor eliminates these biases.
Calibration of DXA units can be modified by the manufacturer to provide differing amounts of lean and fat tissue. New generations of DXA scanners (software and hardware changes) are often compared with results from the previous generation to judge the ability to transition from older to newer technology. Our results from two independent samples confirm that the calibration of the QDR 4500A produces higher total FFM and lower FM estimates compared with the Hologic whole body pencil-beam scanners. Although our correction factor decreases the estimates of FFM and, consequently, increases the FM to match the 4-C model, the corrected FM is still substantially less than estimated by the QDR 2000.
The TMM of the fat free body using the QDR 2000 is higher than that using DXA4500A in both samples 2 and 3. The mineral expressed as a percentage of the corrected FFM in sample 3 before and after weight loss (6.1 and 6.2%, respectively) is comparable to that found in a young adult population by Evans et al. (4) at 6.1% using DXApencil (Hologic QDR 1000W) and somewhat lower than that found in reference human (6.8%) (2). The differences in mineral calibration between the two scanners used in this study reflect differences between specific scanners rather than calibration differences between models.
Among the differences between the DXAfan and DXApencil, the magnification effect has been shown to affect the measurements of bone area, hip geometry (11), and FFM and FM (3) for the Hologic technology. Mazess and Barden (9) also compared fan beam (Expert and Prodigy from GE/Lunar) with pencil beam (DPX from GE/Lunar) for lean tissue mass and percent fat, finding less systematic variation between modes but large prediction errors for the Expert but not for the Prodigy. Our studies performed on the QDR 4500A used software version 8.21. This version corrects for differential magnification at each pixel. If beam magnification were an underlying factor contributing to differences in the assessment of FFM from the fan beam, then the Bland-Altman plots should show an increasing difference between the two methods as FFM increases. In sample 1, the error in measurement between the fan beam and the 4-C model appears to increase with increasing levels of FFM, but this increase was not significant; thus fan beam appears to be an unbiased estimator of FFM with increasing levels of FFM (Fig. 1B). However, previous work by Salamone et al. (12) shows an increased error in assessment of FM >30 kg of total body fat compared with the 4-C model. Whether this increased error is due to magnification or the difficulty in assessing body composition, which overlies the skeleton, remains to be determined.
Theoretically, estimation of soft tissue by DXA can be affected by small differences in hydration (10). Experimental data support that DXA readily measures increases in fluid retention from dialysis or the loss of fluids with dehydration (5, 6) through estimates of FFM. Thus different levels of fluid retention can affect the percent hydration of FFM, depending on when the measurements of TBW and FFM were obtained. In all of our samples, FFMTBW and FFMDXA were measured at the same visit after an overnight fast; thus the disparity in the percent hydration of FFM between the fan and pencil beam evidenced in this study cannot be attributed to differences in tissue hydration. Differences in X-ray attenuation of soft tissue determine whether tissue is considered to be FFM and FM by DXA. The mineral content of the TBW is largely responsible for these differences in X-ray absorption. Thus, whereas DXA cannot be used to measure true hydration of FFM, any difference between the apparent hydration from DXA and that of the 4-C analysis suggests a calibration offset. When FFM from the fan beam is corrected for the systematic differences with the 4-C model, the hydration of FFM moves closer to the established physiological value of 72-73% (16) and to that found in several studies with body water and DXA (7).
Limitations of estimating body composition are inherent in the methods available for use by researchers. Whereas the definitive method to assess body composition is carcass analysis, this option is limited for most validation studies. Technical measurement error, day-to-day variation in BMC, and the concentration of water can contribute to variability in the estimation of FM and FFM by scale weight, hydrodensitometry, TBW, and DXA (7). By incorporating each of these methods, the 4-C model takes advantage of minimizing the error associated with estimating body fat, water, mineral, and protein from one- or two-component models (7).
In summary, we found systematic differences in the assessment of FFM and FM between the fan system and pencil-beam systems from Hologic. In addition, we found that the systematic differences in body composition estimates between the fan-beam system and 4-C model or TBW could be alleviated by applying a correction factor of 0.964. After the correction was applied in two samples, the average FFM and FM were the same as those obtained from the 4-C model and TBW, and the hydration of FFM was closer to the established hydration level in adult samples. Consistent results in populations that included men, women, African-Americans, as well as Caucasians, over a large age and weight range suggest that a correction made to FFM and FM obtained by the QDR 4500A should be considered when evaluating body composition studies. Further validation studies are needed that include children through young adults with a broad range of BMI before this correction factor can be applied to these populations.
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ACKNOWLEDGEMENTS |
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The research of M. Visser has been made possible by a fellowship of the Royal Netherlands Academy of Arts and Sciences. This study was supported by National Institute on Aging contract nos. N01-AG-6-2106, N01-AG-6-2102, and N01-AG-6-2103. Support was obtained from Hologic, Inc.
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FOOTNOTES |
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Address for reprint requests and other correspondence: F. A. Tylavsky, Dept. of Preventive Medicine, 66 N. Pauline St., Suite 633, Memphis, TN 38105 (E-mail: ftylavsky{at}utmem.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.
First published November 1, 2002;10.1152/japplphysiol.00732.2002
Received 7 August 2002; accepted in final form 27 October 2002.
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TOP
ABSTRACT
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MATERIALS AND METHODS
RESULTS
DISCUSSION
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N. Cameron, P. L Griffiths, M. M Wright, C. Blencowe, N. C Davis, J. M Pettifor, and S. A Norris Regression equations to estimate percentage body fat in African prepubertal children aged 9 y Am. J. Clinical Nutrition, July 1, 2004; 80(1): 70 - 75. [Abstract] [Full Text] [PDF]
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S. Blanc, D. A Schoeller, D. Bauer, M. E Danielson, F. Tylavsky, E. M Simonsick, T. B Harris, S. B Kritchevsky, and J. E Everhart Energy requirements in the eighth decade of life Am. J. Clinical Nutrition, February 1, 2004; 79(2): 303 - 310. [Abstract] [Full Text] [PDF]
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