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Institute of Physiology, Faculty of Medicine, University of Lausanne and Departments of Surgical Intensive Care, Internal Medicine, and Radiology, University Hospital, CH-1011 Lausanne, Switzerland
ABSTRACT
INTRODUCTION
METHOD
RESULTS
DISCUSSION
ACKNOWLEDGEMENTS
FOOTNOTES
REFERENCES
ABSTRACT 
Bracco, David, Daniel Thiébaud, René L. Chioléro, Michel Landry, Peter Burckhardt, and Yves Schutz.
Segmental body composition assessed by bioelectrical impedance
analysis and DEXA in humans. J. Appl.
Physiol. 81(6): 2580-2587, 1996.
The present study assessed the relative contribution of each body segment to whole
body fat-free mass (FFM) and impedance and explored the use of
segmental bioelectrical impedance analysis to estimate segmental tissue
composition. Multiple frequencies of whole body and segmental
impedances were measured in 51 normal and overweight women. Segmental tissue composition was independently
assessed by dual-energy X-ray absorptiometry. The sum of
the segmental impedance values corresponded to the whole body value
(100.5 ± 1.9% at 50 kHz). The arms and legs contributed to 47.6 and 43.0%, respectively, of whole body impedance at 50 kHz, whereas they represented only 10.6 and 34.8% of total FFM, as
determined by dual-energy X-ray absorptiometry. The trunk averaged
10.0% of total impedance but represented 48.2% of FFM. For each
segment, there was an excellent correlation between the specific
impedance index
(length2/impedance) and FFM
(r = 0.55, 0.62, and 0.64 for arm,
trunk, and leg, respectively). The specific resistivity was in a
similar range for the limbs (159 ± 23 cm for the arm and 193 ± 39 cm for the leg at 50 kHz) but was higher for the trunk (457 ± 71 cm). This study shows the potential interest of segmental body
composition by bioelectrical impedance analysis and provides specific
segmental body composition equations for use in normal and overweight
women.
dual-energy X-ray absorptiometry; body segments; body fat; fat-free
mass
INTRODUCTION ASSESSMENT OF BODY COMPOSITION plays an important role
in nutritional evaluation, and bioelectrical impedance analysis (BIA), which has been known for more than 50 years, has become widely used in
clinical settings during the last 10 years (10, 13, 14).
Numerous investigations have demonstrated the usefulness of BIA in
assessing body composition, body composition changes, and body fluid
distribution in a wide range of physiological and clinical conditions
(6, 11, 19). The resistance of tissues to electrical current is
directly related to their fluid content: the highly hydrated fat-free
mass (FFM) is a good electrical conducting medium, whereas the poorly
hydrated adipose tissue is a good electrical insulator. In normal and
ill subjects, BIA is correlated with total body water, and the
variations of both are also correlated (11). Measurements of the
conducting volume of the body is based on Ohm's law, which states that
a volume of constant section is proportional to the length squared
(L2) divided by
its resistance. However, recently, growing interest has focused on
certain limitations of this method, such as the geometry of the
measured conductor: there is a linear relationship between
bioelectrical impedance index
(height2/resistance) and FFM,
provided the conductor measured is apparented to a cylinder or has a
constant section. This is obviously not the case when assessing the
whole body BIA, as the conductor usually measured (wrist to ankle)
consists of two long thin conductors (limbs) separated by a shorter and
thicker one (trunk). Despite this limitation, most investigators have
demonstrated a good relationship between the square of index
height-to-whole body resistance and FFM (11), since the relative
contribution of each segment increases in concert with body size.
The aims of the present study were to
1) describe segmental body
composition by segmental BIA and dual-energy X-ray absorptiometry (DEXA), 2) analyze the relationship in healthy subjects
between segmental FFM by BIA and DEXA, and 3) determine
the relationships between the L2/impedance
index and the segmental FFM for each segment at three different
frequencies.
METHOD
, the measurement
was repeated. Whole body and segmental resistance and reactance
were measured, and impedance and phase angle were calculated from the
vectorial resultant of these two components.
DEXA. DEXA (model QDR 2000, Hologic) was used to assess body composition independently. Subjects were measured while wearing only a standard light cotton shirt to minimize clothing absorption. Measurements were performed by a trained radiology technician with dual-energy X-ray beams at 70 and 140 KeV. Single rectilinear scanning mode was used on a 148 × 330 pixel matrix in a 196 × 80 cm window. Although DEXA was the first method developed to measure bone mineral density (15), the application to whole body soft tissue composition has become current practice (20). The DEXA device measures the attenuation of the two energy X-ray beams crossing the tissue. This allows partitioning between bone vs. soft tissue and fat vs. lean tissue in pixels of the body where there is no overlying calcified tissue. The DEXA device provides for each area the mass of bone, soft tissue FFM, and fat. For further computations and comparison with BIA, FFM including bone mineral content (also taken into account by the BIA method) was taken. The duration of total body scanning time was 15 min, and total X-ray irradiation absorbed by the organism was <5 mrems, which corresponds to 10% of a standard chest film. Total body scanning area was divided into precise anatomic segments: the arms were separated from the trunk by a line passing through the humeral head and the apex of the axilla. The trunk was separated from the legs by a line passing from the iliac crest to the perineum. The head was excluded from the trunk by a horizontal line passing just below the mandible. The use of precise identical anatomic landmarks in both BIA and DEXA allowed the comparison of these two methods. Computations. Computation methods underlying the BIA technique are reviewed elsewere (11) and demonstrate that there is a linear relationship between FFM and the L2/impedance index
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(1) |
50 kHz), the conducting volume
is assumed to represent the highly hydrated lean tissue (i.e., FFM) of
the analyzed segment, whereas low-frequency currents flow mainly
through the extracellular volume (27).
By using this approach, specific resistivity can be estimated from
1) FFM independently derived from
DEXA, 2) length measured by
anthropometry, and 3) impedance
measured by BIA
|
(2) |
RESULTS
Anthropometry. As shown in Table 1, the sample studied purposely covered a broad range of body weight, ranging from lean to morbidly obese. However, as in current population studies, the sample showed a slight kurtosis toward high body weight, since markedly overweight subjects were also included. This is illustrated by the fact that median body weight (71.5 kg), body mass index (BMI; 23.9 kg/m2), and percentage or ideal body weight (109%) were lower than their respective mean values. Prediction and validation groups were comparable in terms of weight, height, age, BMI, and body composition.
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DEXA. Body composition assessment by
DEXA demonstrated an excellent agreement between measured body weight
and reconstituted weight from the sum of all DEXA pixels. The bias was
<1 kg for both groups (mean absolute weight difference of 0.74 ± 0.67 kg). There was also a good correlation between left and right limb FFM, the mean absolute difference in segmental FFM being only 180 ± 270 g (not significant) for the arms and 180 ± 160 g (not significant) for the legs, confirming the precision of segments delineation by the radiology technicians. The limbs showed a tendency to a higher percentage of fat (42.7 ± 14.9% for arms and
41.0 ± 12.1% for legs) compared with the trunk (31.4 ± 16.9%). From the leanest to the most overweight women, relative
body fat increased more in the trunk (1.5-62.1%) than in the arm
(9.9-68.5%) or the legs (14.3-63.5%). The contribution of
each segment to increasing body weight is illustrated in Fig.
2, which shows the segmental composition of
the 51 women ranked by increasing weight (from 48.6 to 131.2 kg). Whole
body FFM increased twofold from 38.8 to 55.2 kg, whereas fat mass
increased a 20-fold range, i.e., from 3.8 to 73.6 kg. The major part of
this fat accumulation occurred in the trunk, where fat mass increased
by a factor of one hundred (from 0.4 to 37.2 kg). From the regression
coefficient between fat mass and weight
(r2 = 0.97, P < 0.0001), it could be calculated
that for each kilogram of change in weight the relative contribution of
fat to the additional weight was as high as 86%. The FFM rose only
slightly with increasing obesity, and the major part of adipose tissue
deposition occurred in the trunk. The change in the composition of the
limbs was less marked. From the slopes of the regression lines, we can
establish that 1 kg of additional weight contains 127 ± 22 g FFM
(r = 0.64, P < 0.0001), 466 ± 14 g fat
deposited in the trunk (r = 0.98, P < 0.0001), 288 ± 12 g fat in
the legs (r = 0.96, P < 0.0001), and 102 ± 10 g fat
in the arms (r = 0.85, P < 0.0001).
Segmental body composition by
impedancemetry. BIA (Table
2) confirmed that the major part of body
impedance at the three measured frequencies (0.5, 50, and 100 kHz) was
confined to the limbs, with the trunk constituting only a small part of
the total whole body bioelectrical impedance. There was an excellent
recovery between the measured whole body resistance and reactance
(wrist to ankle) and the sum of the segmental BIA measurements.
However, this was not the case for 0.5-kHz reactance, secondary to the fact that the measured values were close to zero (95% of values <10
for whole body). Given the precision of our instrument (±1 )
and the possible dielectric capacitive effect at the level of the skin
surface with such low frequencies, recoveries of >100% may not be
surprising.
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Derived equations for segmental body composition by
BIA. On a physiological-mathematical basis, the
L2/impedance
index is directly proportional to the conducting volume and thus to the
measured FFM. This investigation confirmed that at all frequencies and
in all segments, there was a good correlation between the segmental FFM
and the
L2/impedance
index (Fig. 3). Linear regression analysis
in the prediction group is summarized in Table
3. On this basis, predicted FFM was
calculated for each subject of the validation group at the three
frequencies, and the residuals are plotted in Fig.
4. At 50 kHz, the mean difference (average
of absolute values of the differences) between predicted and measured
FFM was 2.26 ± 1.42 kg for the whole body, 0.30 ± 0.27 kg for
the arm, 2.12 ± 1.89 kg for the trunk, and 0.61 ± 0.55 kg for
the leg. Linear regression between segmental FFM and the
L2/impedance
index of the entire sample is also summarized in Table 3. It is
noteworthy that, when performing linear regression analysis of these
two parameters, a positive intercept of the regression line remains,
indicating that part of the FFM measured by DEXA is not crossed by
electrical current.
) and for each segment [arm
(
), trunk (
), and leg (x)] at 0.5 (A), 50 (B), and 100 (C) kHz.
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), and 100 () kHz.
In a stepwise multiple regression model, we used independent variables such as weight, height, age, waist-to-hip ratio, percent ideal weight, and resistance index. We found that the latter had the best correlation to FFM (r2 = 0.62), and the remaining variables improved r2 by 7% (r2 = 0.69). On the other hand, a model based on anthropometric variables only (weight, height, waist-to-hip ratio, and BMI) had an r2 of 0.60.
The specific resistivity index was calculated by dividing the segmental FFM by the L2/impedance index and 1.1 g/cm3. This parameter expresses the resistance that could be measured between two 1 × 1 cm electrodes placed on the opposite side of a 1-g average FFM of the measured segment. When this parameter is low, it means that the FFM of that segment is a good conductor, whereas high values indicate FFM with higher insulating properties (Table 4). It must be stressed that this parameter gives a crude estimation of specific resistivity, since it assumed that the measured segment was a homogeneous conductor.
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DISCUSSION
This investigation, performed in lean and obese volunteers, demonstrated that segmental body composition could be determined by segmental BIA, compared with DEXA as a reference method. There was a significant correlation between segmental FFM obtained from BIA and FFM measured by DEXA. By using an appropriate anatomic location of electrodes, the recovery between the sum of the three segments and whole body BIA had an error of <1%.
Segmental body composition estimated by BIA. Several studies investigating segmental bioelectrical impedance have previously been published (1, 4, 5, 8, 9, 16-18, 21-23, 29). Unlike whole body BIA, which is well standardized (11), there are some differences between the various methods used and between the anatomic location of measured segments (18). All BIA devices did not measure the same value: some devices measure the impedance (Holtain device), whereas others measure resistance only (Valhalla device) and others measure both resistance and reactance, allowing calculation of impedance and phase shift (RJL, Xitron device). At low frequencies, phase shift is very low, so that the difference between the magnitude of resistance and impedance is of little practical importance, whereas at higher frequencies this difference cannot be neglected. When comparing resistance or impedance together, there is little difference between various BIA devices (8).
While performing segmental BIA, there are some methodological inconsistencies between the various investigators in the anatomic disposition of the current injecting and sensing electrodes (18). First, some investigators moved the current-injecting electrodes when measuring segmental impedance. Second, for measuring the leg impedance, some investigators (1, 4, 5) placed their sensing electrode at the anterior midline of the thigh, in the same plane as the gluteal crease, whereas others (8) placed the pelvic electrode at the same location as in the present study. Third, for measurement of the trunk, the upper sensing electrode was located at the sternal notch by some (8) and on the anterior part of the shoulder by others (1, 4, 5). Sensing-electrode location for the arm did not differ from one study to another. The anatomic location of the current-injecting electrode is of crucial importance because it determines the electrical current pathway across various segments of the body (18). In the majority of the previously published studies (1, 4, 5, 8), the current-injecting electrodes were moved and located just a few centimeters beneath the voltage-sensing electrodes. This changes the current pathways across the measured segment and thus the effective conducting volume measured. As shown in Table 5, in all studies where the current-injecting electrodes were moved (4, 5, 8, 28), the sum of segmental impedance (or resistance) was greater than the whole body impedance (resistance), whereas in the study of Organ et al. (18), where the electrodes were kept in place, the sum of segmental impedance perfectly corresponded to whole body assessements. In the present study, the degree of agreement between the sum of segmental impedance and whole body corresponded to the results of Organ et al. and was excellent. One critical issue is the relative contribution of the trunk and legs to whole body impedance observed in different studies. In the former studies (4, 5, 8, 28), it ranged from 15 to 17% compared with ~10% in the study of Organ et al. and in the present investigation. The leg contributed to 50-53% of whole body resistance in studies where current-injecting electrodes were displaced compared with 43.0% in the present investigation. However, as shown by a positive intercept in the FFM vs. L2/impedance regression line, the volume assessed by segmental BIA was lower than the FFM measured by DEXA. In the trunk, for example, the electrical current flows from one shoulder to the ipsilateral tight, and there is a limited amount of electrical current across the opposite shoulder and hip, although these tissues are included in DEXA-measured FFM.
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Segmental equations for body composition by BIA derived from our sample are shown in Table 3. In each segment, there was a good agreement between FFM measured by DEXA and the index L2/impedance at all frequencies. However, at high frequencies (50 and 100 kHz in the present investigation), BIA assessment was more appropriate for FFM determination than at low-frequency BIA, since in the latter the electrically measured volume is primarily confined to the extracellular space. Despite the fact that this concept is not applicable for the whole body, Fig. 3 shows that there was a reasonable agreement between the height2/impedance index and FFM due to the fact that with increasing body size, the relative contribution of each segment to length and FFM rises in concert (Fig. 2). It must be stressed that the height/impedance index is the best single predictor of FFM, as measured by DEXA. The addition of other anthropometric variables commonly used only slightly improved the prediction power.
Body composition assessed by DEXA. Since the advent of DEXA, the use of this device in body composition research has generated a great enthusiasm. The method is safe, requires little cooperation from the subject, and is totally independent, i.e., it does not have to be calibrated against a reference method. Moreover, DEXA devices are widely available for bone mineral content assessment in humans. Body composition investigation requires only software implementation. However, as any in vivo body composition assessment, it has nevertheless some limitations (24). For each pixel measured, two parameters are obtained (attenuation at low and high energy) and three variables need to be calculated (bone, lean, and fat). Mathematically, it is not possible to resolve a system composed of two equations with three unknown variables. Therefore, some assumptions have to be made. If the X-ray beam attenuation is high, the tissue crossed is assumed to contain bone; for this particular pixel, the system resolves the equations for bone and nonbone by assuming that the relative composition of nonbone is comparable to the surrounding bone-free (low-attenuation) pixels. This assumption implies that the composition of soft tissue overlying bone must have the same composition as the surrounding tissues. In addition, pixels including a small amount of calcium may be below the threshold value and may not be counted as bone but assimilated to very lean tissue. An additional interfering factor is the water content of FFM. Current DEXA software assumes that FFM contains 73.2% water. All of the subjects of our investigation were adults in good health (except obesity in some) with no concurrent medical conditions, and none were taking drugs. Whether the FFM of our sample did contain a fixed proportion of water (12) remains to be seen. DEXA remains a reliable technique for measuring body composition, but analysis of head and, to some extent, thorax soft tissue composition may be difficult because of superimposed bone. For the present investigation, there was a need for an independent technique capable of measuring segmental soft tissue composition. Some studies investigated limbs segmental body composition by anthropometry against BIA (4, 5, 8), but, to the best of our knowledge, only one investigation in humans has described segmental body composition assessed by DEXA vs. BIA (28).
When considering the values obtained by DEXA for body composition of the legs, trunks, and arms in this group of adults, there was a wide variation in segmental values. Therefore, it seems that the trunk acts as a reservoir for fat accumulation in overweight individuals. With increasing weight, the contribution of fat to excess body weight is as high as 86%, and about one-half of this adipose tissue is accumulated in the trunk.
In the present study, the relative error of FFM determination by BIA by using DEXA as the reference method was 6.7-7.6% for whole body, 15.9-16.9% for the arm, 11.7-12.9% for the trunk, and 11.9-12.7% for the leg. This indicates the uncertainty of accurately assessing the absolute FFM in wide and short segments such as the trunk.
In conclusion, segmental body composition assessment by using segmental bioelectrical impedance constitutes a simple, inexpensive, and relatively accurate method to assess body composition in healthy and obese subjects. This study demonstrated that there is an excellent recovery between segmental and whole body BIA, with this highly standardized technique. Regression equations are provided that allow us to calculate segmental FFM by using segmental impedance and length. However, this requires prior standardization, particularly when different approaches and different BIA devices are employed.
ACKNOWLEDGEMENTS
The authors thank all of the subjects who participated in this investigation. We are indebted to K. Watrin and the radiology technicians who performed the DEXA scans and to Dr. M. Berger for reviewing the manuscript.
FOOTNOTES
Address for reprint requests: Y. Schutz, Institute of Physiology, Faculty of Medicine, Rue du Bugnon 7, CH-1011 Lausanne, Switzerland.
Received 21 July 1995; accepted in final form 25 June 1996.
REFERENCES
| 1. | Baumgartner, R. N., W. C. Chumlea, and A. F. Roche. Bioelectric impedance phase angle and body composition. Am. J. Clin. Nutr. 48: 16-23, 1988. [Abstract] |
| 2. | Bland, J., and D. Altman. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1: 307-310, 1986. [Medline] |
| 3. | Burgess, N. S. Wrestlers' minimal weight: anthropometry, bioimpedance, and hydrostatic weighing compared. Med. Sci. Sports Exercise 23: 247-253, 1991. [Medline] |
| 4. | Chumlea, W. C., R. N. Baumgartner, and C. O. Mitchell. The use of segmental bioelectric impedance in estimating body composition. In: Advances in In Vivo Body Composition Studies, edited by S. Yasumura. New York: Plenum, 1990, p. 375-385. |
| 5. | Chumlea, W. C., R. N. Baumgartner, and A. F. Roche. Specific resistivity used to estimate fat-free mass from segmental body measures of bioelectric impedance. Am. J. Clin. Nutr. 48: 7-15, 1988. [Abstract] |
| 6. | Deurenberg, P., K. Van der Kooy, and J. G. Hautvast. Applications of bioelectrical impedance analysis: a critical review. Basic Life Sci. 55: 391-393, 1990. [Medline] |
| 7. | Durnin, J. V. G. A., and M. Ramahan. The assessment of the amount of fat in the human body from measurements of skinfold thickness. Br. J. Nutr. 21: 681-689, 1967. [Medline] |
| 8. | Fuller, N. J., and M. Elia. Potential use of bioelectrical impedance of the "whole body" and of body segments for the assessment of body composition: comparison with densitometry and anthropometry. Eur. J. Clin. Nutr. 43: 779-791, 1989. [Medline] [Medline] |
| 9. | Ishikawa, M., and N. Shinagawa. Nutritional assessment by bioelectrical impedance analysis. Jpn. J. Clin. Med. 49 Suppl.: 87-90, 1991. |
| 10. | Jebb, S. A., and M. Elia. Techniques for the measurement of body composition: a practical guide. Int. J. Obes. 17: 611-621, 1993. |
| 11. | Kushner, R. F. Bioelectrical impedance analysis: a review of principles and applications. J. Am. Coll. Nutr. 11: 199-209, 1992. [Medline] [Medline] |
| 12. | Lohman, T. Applicability of body composition techniques and constants for children and youth. Exercise Sport Sci. Rev. 14: 325-357, 1986. [Medline] |
| 13. | Lukaski, H., W. Bolonchuk, C. Hall, and W. Siders. Validation of tetrapolar bioelectrical impedance method to assess human body composition. J. Appl. Physiol. 60: 1327-1332, 1986. [Medline] |
| 14. | Lukaski, H., P. Johnson, W. Bolonchuk, and G. Lykken. Assessement of fat-free mass using bioelectrical impedance measurements of the human body. Am. J. Clin. Nutr. 41: 810-817, 1985. [Abstract] |
| 15. | Mazess, R., H. Barden, J. Bisek, and J. Hanson. Dual-energy X-ray absorptiometry for total-body and regional bone mineral and soft tissue composition. Am. J. Clin. Nutr. 51: 1106-1112, 1990. [Abstract] |
| 16. | Mazess, R. B. Alterations in body fluid content can be detected by bioelectrical impedance analysis. J. Surg. Res. 50: 461-468, 1991. [Medline] |
| 17. | Nyboer, J. Workable volume and flow concepts of bio-segments by electrical impedance plethysmography. Nutrition 7: 396-408, 1991. [Medline] |
| 18. | Organ, L. W., G. B. Bradham, D. T. Gore, and S. L. Lozier. Segmental bioelectrical impedance analysis: theory and application of a new technique. J. Appl. Physiol. 77: 98-112, 1994. [Medline] |
| 19. | Paijmans, I. J., K. M. Wilmore, and J. H. Wilmore. Bioelectrical impedance analysis: a review of principles and applications. J. Am. Coll. Nutr. 11: 199-209, 1992. |
| 20. | Pritchard, J. E., C. A. Nowson, B. J. Strauss, J. S. Carlson, B. Kaymakci, and J. D. Wark. Evaluation of dual-energy X-ray absorptiometry as a method of measurement of body fat. Eur. J. Clin. Nutr. 47: 216-228, 1993. [Medline] |
| 21. | Rallison, L. R., R. F. Kushner, D. Penn, and D. A. Schoeller. Errors in estimating peritoneal fluid by bioelectrical impedance analysis and total body electrical conductivity. J. Am. Coll. Nutr. 12: 66-72, 1993. [Medline] |
| 22. | Ross, R., L. Leger, P. Martin, and R. Roy. Potential use of bioelectrical impedance of the "whole body" and of body segments for the assessment of body composition: comparison with densitometry and anthropometry. Eur. J. Clin. Nutr. 43: 779-791, 1989. |
| 23. | Roubenoff, R., R. A. Roubenoff, L. M. Ward, S. M. Holland, and D. B. Hellmann. Identifying body fluid distribution by measuring electrical impedance. J. Trauma 33: 665-670, 1992. [Medline] |
| 24. | Roubenoff, R. A., J. J. Kehayias, B. Dawson-Hughes, and S. B. Heymsfield. Use of dual-energy X-ray absorptiometry in body composition studies: not yet a "gold standard." Am. J. Clin. Nutr. 58: 589-591, 1993. [Medline] |
| 25. | SAS Institute JMP Statistical Package for Macintosh (3rd ed.). Cary, NC: SAS, 1994. |
| 26. | Schutz, Y., and D. Bracco. Impedance bioélectrique: utilité pour l'évaluation de la composition corporelle. Méd. Hyg. 51: 770-777, 1993. |
| 27. | Segal, K., S. Burastero, A. Chun, P. Coronel, and R. Pierson. Estimation of extra-cellullar and total body water by multiple-frequency bioelectrical-impedance measurement. Am. J. Clin. Nutr. 54: 26-29, 1991. [Abstract] |
| 28. | Stewart, S. P., P. N. Bramley, R. Heighton, J. H. Green, A. Horsman, M. S. Losowsky, and M. A. Smith. Estimation of body composition from bioelectrical impedance of body segments: comparison with dual-energy X-ray absorptiometry. Br. J. Nutr. 69: 645-655, 1993. [Medline] |
| 29. | Zillikens, M. C., J. W. O. van den Berg, J. H. F. Wilson, and G. R. Swart. Whole-body and segmental bioelectrical-impedance analysis in patients with cirrhosis of the liver: changes after treatment of ascites. Am. J. Clin. Nutr. 55: 621-625, 1992. [Abstract] |
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F. Zhu, D. Schneditz, E. Wang, and N. W. Levin Dynamics of segmental extracellular volumes during changes in body position by bioimpedance analysis J Appl Physiol, August 1, 1998; 85(2): 497 - 504. [Abstract] [Full Text] [PDF]
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R. B. Mazess Letters to the Editor J Appl Physiol, January 1, 1998; 84(1): 396 - 396. [Full Text] [PDF]
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