| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
Original Research Communication |
1 From the Obesity Research Center, St Luke’s-Roosevelt Hospital, Columbia University College of Physicians and Surgeons, New York.
2 Supported by National Institutes of Health grant PO1-DK42618. 3 Reprints not available. Address correspondence to ZM Wang, Weight Control Unit, 1090 Amsterdam Avenue, 14th Floor, New York, NY 10025. E-mail: zw28{at}columbia.edu.
 |
ABSTRACT |
|---|
 TOP ABSTRACT INTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Objective: We explored 2 SM prediction approaches, one based on the assumption that the ratio of TBK to SM is stable in healthy adults and the other on a multiple regression TBK-SM prediction equation.
Design: Healthy subjects aged 
20 y were recruited for body-composition evaluation. TBK and SM were measured by whole-body 40K counting and multislice magnetic resonance imaging, respectively. A conceptual model with empirically derived data was developed to link TBK and adipose tissue–free SM as the ratio of TBK to SM.
Results: A total of 300 subjects (139 men and 161 women) of various ethnicities with a mean (± SD) body mass index (in kg/m2) of 25.1 ± 5.4 met the study entry criteria. The mean conceptual model–derived TBK-SM ratio was 122 mmol/kg, which was comparable to the measurement-derived TBK-SM ratios in men and women (119.9 ± 6.7 and 118.7 ± 8.4 mmol/kg, respectively), although the ratio tended to be lower in subjects aged 70 y. A strong linear correlation was observed between TBK and SM (r = 0.98, P < 0.001), with sex, race, and age as small but significant prediction model covariates.
Conclusions: Two different types of prediction models were developed that provide validated approaches for estimating SM mass from 40K measurements by whole-body counting. These methods afford an opportunity to predict SM mass from TBK data collected in healthy adults.
Key Words: Body composition • nutritional assessment • whole-body counting • total body potassium • skeletal muscle • prediction models • ratio of total body potassium to skeletal muscle
|
INTRODUCTION |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
At present, the most accurate in vivo methods of measuring whole-body SM are multislice magnetic resonance imaging (MRI) and computed axial tomography (CT) (2). Although MRI and CT are often used as criterion methods for estimating SM, their application is limited because of expense, lack of instrument access, and unavailability of resources for image analysis. The CT method also exposes subjects to radiation, and CT for research purposes is not often approved by institutional review boards, especially in evaluating healthy children and premenopausal women.
Two available field methods for estimating SM are the use of anthropometric measurements and bioelectrical impedance analysis (2–5). Although noninvasive and inexpensive, these methods are not sufficiently accurate to evaluate individuals or to monitor small changes in muscle mass (4, 5). Two urine collection–based laboratory methods, one relying on urinary creatinine excretion and the other on urinary 3-methylhistidine excretion, ideally include a 1-wk meat-free diet protocol and 3 consecutive 24-h urine collections (1, 6–8). The between-day CV for the urinary marker methods approaches 5%, even with the rigorous conditions available in a metabolic ward (6).
The limitations of these SM estimation methods led us in the present study to seek an in vivo method for measuring total-body SM mass. Potassium is a measurable element in vivo, and the use of total body potassium (TBK) as an index of body composition has a long history in nutritional research. Body potassium is distributed entirely in the fat-free mass (FFM) compartment, and a large proportion exists in SM. For example, 60% of TBK in reference man is found in SM (9). The ratio of TBK to FFM is 54–59 mmol/kg for healthy females and 59–62 mmol/kg for healthy males (1, 10), and this relation provides a means of estimating FFM from measured TBK (1, 11). Similarly, SM is distributed in FFM, and the mean (± SD) ratio of SM to FFM is 0.473 ± 0.037 for healthy females and 0.528 ± 0.036 for healthy males (12–14). These 2 observations led us to hypothesize that the ratio of TBK to SM may be relatively stable in healthy adults, thus providing the basis for an SM prediction method.
A similar concept was advanced by Forbes (1), who first measured TBK by whole-body counting and then calculated FFM according to the assumed constant ratio of TBK to FFM (ie, 87 mmol/kg). Total-body SM was next calculated on the basis of the assumption that SM makes up, on average, 49% of FFM in adult humans (15). However, Forbes was unable to assess the accuracy of TBK-predicted SM estimates because a reference SM measurement method, such as MRI or CT, was unavailable 3 decades ago.
Whole-body 40K counting is available at over 30 body-composition centers throughout the world that have large cross-sectional and longitudinal TBK databases. This led us in the present study to develop and validate models associating TBK and SM mass, with the specific aim of providing an approach to the measurement of total-body SM mass.
|
SUBJECTS AND METHODS |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
 | (1) |
A second modeling strategy was also applied because we assumed at the outset that the TBK-SM ratio might have influencing factors of unknown magnitude such as age, sex, and race. Accordingly, we developed an SM prediction multiple regression function (F) in which total-body SM was set as the dependent variable and TBK as the main predictor variable,
 | (2) |
TBK/SM model
Because almost all body potassium exists within intracellular fluid (ICF) and extracellular fluid (ECF), TBK is equal to the sum of the potassium masses within ICF (KICF) and ECF (KECF),
 | (3) |
The cellular body-composition level is composed of 3 compartments: cells, ECF, and extracellular solids (16). The cellular compartment can be further divided into fat and body cell mass (BCM), which is defined as a "component of body composition containing the oxygen-exchanging, potassium-rich, glucose-oxidizing, work-performing tissue" (17).
In body-composition studies, 2 SM terms are usually used: adipose tissue (AT)–free SM and anatomical SM. AT-free SM is composed of 2 main compartments: SM cells and SM ECF. SM cell mass is the largest contributor to BCM and can be expressed as SM cells = m x BCM = m x ICW/a, where m is the fraction of BCM that consists of SM cells and a is the fraction of BCM that consists of ICW. Similarly, SM ECF is a portion of whole-body ECF and can be expressed as SM ECF = n x ECF = n x ECW/b, where n is the fraction of whole-body ECF that consists of SM ECF and b is the fraction of ECF that consists of ECW. A TBK/AT-free SM model is thus derived as
 | (4) |
 |
Because total body water is made up of ICW and ECW, ECW can be expressed as a function of ICW: ECW = E/I x ICW, where E/I is the ratio of ECW to ICW. Equation 4
can be converted and simplified as
 | (5) |
 |
 |
When MRI is applied, the observed SM image area in each slice contains a small amount of interstitial AT that cannot be entirely separated out by analysis software. The MRI-measured SM, or anatomical SM, contains AT-free SM and this small amount of interstitial AT within muscle. Equation 5 is thus modified for MRI-measured SM as
 | (6) |
, the TBK-SM ratio observed by MRI is determined by 8 factors. The mean magnitudes for the 8 determinants are described below.
Determinants [K]ICW, [K]ECW, a, b, and E/I
In our previous studies, we discussed the physiologic aspects of these 5 determinants (11, 18). The same magnitude and variation range for each determinant was applied in the present study.
The cellular and extracellular potassium concentrations are physiologically stable in mammals. Previous studies reported similar [K]ICW and [K]ECW in mammals: 150–160, 150 ± 7.2 (SD), and 159 mmol/kg H2O for [K]ICW and 4–6 mmol/kg H2O for [K]ECW (11). In healthy subjects the mean [K]ICW and [K]ECW are thus assumed to be 155 and 5 mmol/kg H2O, respectively.
Determinant a is cellular hydration (ie, ICW/BCM), and determinant b is ECF hydration (ie, ECW/ECF). Cellular hydration is tightly regulated and thus should be minimally variable in healthy adults. We discussed the physiologic basis for the means of these 2 determinants (ie, a = 0.70 with a variation range of 0.69–0.71 and b = 0.98 with a variation range of 0.97–0.99) in an earlier report (11).
E/I is the ratio of ECW to ICW. We measured E/I by combining 3H2O and sodium bromide dilution and observed means (± SDs) of 0.79 ± 0.13 and 1.03 ± 0.19 for men and women, respectively (18).
Determinants m and n
Determinant m is the fraction of BCM that consists of SM cells, and determinant n is the fraction of whole-body ECF that consists of SM ECF. Information is limited regarding m and n because of the difficulty in quantifying cell mass and ECF within individual tissues in vivo. Therefore, we based the estimates of m and n on data available for reference man (9). In reference man, the amount of TBK is 3580 mmol (140 g) and the amount of potassium in SM is 2148 mmol (84 g). On the basis of the assumption that all potassium exists within cells, whole-body BCM is 29.8 kg (ie, 0.00833 kg/mmol x 3580 mmol) and SM cell mass is 17.9 kg (ie, 0.00833 kg/mmol x 2148 mmol) (17). The determinant m is thus 17.9/29.8 = 0.60 for reference man.
The total-body SM mass in reference man is 28.0 kg, and the SM ECF mass is equal to the difference between the SM mass and the SM cell mass (ie, 28.0 kg - 17.9 kg = 10.1 kg). In reference man, the total-body ECW mass is 18.0 kg, which is equivalent to 18.4 kg of ECF (ie, 18.0 kg/0.98). The determinant n is thus 10.1/18.4 = 0.55 for reference man.
The mean m and n values in women should be slightly smaller than those in men. This is because women have a smaller ratio of SM to AT–free mass (ie, 0.47–0.49 for women compared with 0.53–0.57 for men) (12, 14). In the present study, we assumed mean values of 0.55 and 0.50 for m and n, respectively, in women.
Determinant f
Determinant f is the fraction of MRI-measured SM that consists of interstitial AT. The f value is assumed to be < 0.03 in healthy, nonobese subjects. In reference man, for example, the f value is 0.022 (9). For obese subjects, the f value may reach 
0.05. Although we usually try to remove interstitial AT pixels from the muscle cross-sectional area when analyzing MRI images, some AT pixels are below the visible detection threshold. However, the remaining interstitial AT pixels must be much smaller relative to the whole muscle area.
Magnitude of TBK-SM ratio
The mean values of each of the determinants described above are as follows: [K]ICW = 155 mmol/kg, [K]ECW = 5 mmol/kg, a = 0.70, b = 0.98, E/I = 0.79 for men and 1.03 for women, m = 0.60 for men and 0.55 for women, and n = 0.55 for men and 0.50 for women. According to Equation 6, the mean magnitude of the TBK-SM ratio can be calculated as
 | (7) |
 |
 | (8) |
 |
Equations 7 and 8 indicate that the mean magnitude of the TBK-SM ratio should be identical in men and women if there is no large difference in the f value. On the basis of Equations 7 and 8, f values and the corresponding TBK-SM ratios are shown in Table 1
. As the f value increases from 0 to 0.05, the MRI-measured TBK-SM ratio gradually decreases from 122 to 116 mmol/kg. For AT-free SM (ie, f = 0), a single SM prediction model from TBK can be developed for healthy adults,
 | (9) |
|
20 y were recruited into this study. To be included in the study, subjects had to be ambulatory and have no orthopedic problems or physical handicaps. Each subject completed a medical history, physical examination, and routine blood studies to exclude the presence of underlying diseases. The Institutional Review Board of St Luke’s-Roosevelt Hospital Center approved the study protocol, and all subjects gave informed written consent before participation. About 60% of the subject data came from our earlier body-composition studies (5). The subjects’ body mass was measured to the nearest 0.1 kg while they were fasting and wearing minimal clothing. Height was measured with a stadiometer to the nearest 0.1 cm. Total body fat and FFM were estimated with the use of dual-energy X-ray absorptiometry (DXA; Lunar DPX, software version 3.6; Lunar Corp, Madison, WI). The between-measurement technical error at our center for FFM measured by DXA is 1.2%.
Whole-body counting
The St Luke’s 4
whole-body counter was used to detect the natural 1.46 MeV 
-ray of 40K. The 40K raw counts collected over 9 min were adjusted for body size on the basis of an experimental 42K calibration equation (19). The correction equations for men and women are corrected body K (from 42K) = 0.85 x body K (from 40K) + 7.6 x body mass + 250 (R2 = 0.90; SD = 183 mmol) and corrected body K (from 42K) = 0.88 x body K (from 40K) + 6.4 x body mass + 64.2 (R2 = 0.88; SD = 143 mmol), respectively, where K is in mmol and body mass is in kg. TBK was calculated as 40K/0.000118 (1). The current technical error in our laboratory for repeated phantom 40K counting is ± 2.4% (20).
Magnetic resonance imaging
Total-body SM was measured by using multislice MRI (21). Subjects were placed on the MRI scanner (1.5 T 6X Horizon; General Electric, Milwaukee) platform with their arms extended above their heads. One-centimeter-thick images were taken from the gap between lumbar vertebrae 4 and 5 to the tip of the toes and fingers with a 4.0-cm gap between scans. The protocol involved the acquisition of 35–45 axial images, depending on height, over the whole body.
All MRI scans were analyzed with the use of VECT image analysis software (Tomovision, Montreal) by a group of highly trained observers. The mean (± SD) technical error for between-day measurements of the same scan by the same observer of MRI-derived SM volume is 0.34 ± 1.1% (22). Total-body SM mass was calculated as
 | (10) |
Statistical analysis
Data are expressed as means (± SDs). Statistical comparisons of physical characteristics and body composition between men and women were made by Student’s t test. Age-related differences in TBK, MRI-measured SM, and the TBK-SM ratio were examined across age and sex groups by one-way analysis of variance. Simple linear regression analysis was used to investigate the associations between TBK and MRI-measured SM.
All subjects were randomly separated into 2 groups, a model-development group and a cross-validation group. Empirical models for predicting MRI-measured SM were developed in the model-development group by using multiple-regression analysis. TBK served as the major predictor variable, whereas age, sex, race, and the interactions of these variables with TBK were evaluated as covariates in the model. Dummy variables were used for the 4 ethnic groups. A forward-backward stepwise selection procedure was applied to determine significant variables and derive prediction equation models. The prediction equation obtained from the model-development group was then validated in the cross-validation group by using the approach suggested by Bland and Altman (23). Two-tailed tests of significance (P < 0.05) were used. All analyses were carried out by using SPSS (version 10.0; SPSS Inc, Chicago).
|
RESULTS |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
. The men were significantly younger (P < 0.01), heavier (P < 0.001), and taller (P < 0.001) than the women. There was no significant difference in body mass index between the sexes, although the men had a significantly lower percentage of fat than did the women (P < 0.001). There were also no significant differences in baseline characteristics between the model-development and cross-validation groups.
|
). The TBK-SM ratio was inversely correlated (r = -0.22, P < 0.001; SEE = 7.5 mmol/kg) with age (n = 300),
 | (11) |
). Both TBK and SM were negatively associated with age in the men and the women (P for trend < 0.05–0.001). In the men there was no significant difference in TBK-SM ratios across the age groups. In the women, one-way analysis of variance showed significant differences in TBK-SM ratios across the age groups (P for trend < 0.01).
|
). A simple prediction equation was thus derived from the 300 subjects.
 | (12) |
|
 | (13) |
was applied in the cross-validation group (n = 150), a significant correlation was observed between the measured and predicted SM (r2 = 0.96, P < 0.001; SEE = 1.52 kg). The predicted SM for the cross-validation group was 27.0 ± 7.8 kg (95% CI: 11.4, 42.6 kg), which was very similar to the MRI-measured SM value of 26.8 ± 7.9 kg (95% CI: 11.1, 42.5 kg). Bland-Altman analysis (23) failed to disclose a significant bias in prediction for the cross-validation group (r2 = 0.003, P = 0.52) (Figure 2).
|
|
DISCUSSION |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Ratio model
This approach for predicting SM mass is based on the concept that TBK is measurable as 40K and the assumption of a stable and known TBK-SM ratio in healthy adults. When combined with empirically derived data, our conceptual model suggests a sex-independent TBK-SM ratio of 122 mmol/kg. AT-free SM can thus be estimated as 0.0082 x TBK. This modeling approach is similar to the use of 2 classic ratios in predicting FFM: total body water/FFM and TBK/FFM (11, 13). Our derived TBK-SM ratio of 122 mmol/kg differs by < 3% from the observed mean values of 120.1 and 119.4 mmol/kg for men and women, respectively, aged < 70 y. If we assume for discussion purposes that the fraction of SM that consists of interstitial AT is 0.03, the model-derived TBK-SM ratio would be equal to 119.6 mmol/kg, almost identical to the observed values. The small difference in the measured TBK-SM ratio between men and women (ie, 0.5%) is probably due to sex differences in the content of interstitial AT within MRI-measured SM (Table 1). These observations suggest the appropriateness of 2 SM prediction models in subjects aged < 70 y: AT-free SM = 0.0082 x TBK, and MRI-observed SM = 0.0083 x TBK.
Our observed results indicating a relatively stable TBK-SM ratio for women aged < 70 y (119.4 ± 8.3 mmol/kg) were accompanied by a significantly lower ratio in women aged 70 y (112.6 ± 6.1 mmol/kg; P < 0.01). There are at least 2 biological observations that might explain a lower TBK-SM ratio in elderly subjects. First, the amount of interstitial AT is well known to increase with age (24, 25). Second, skeletal muscle per se atrophies with age, leading to a loss of potassium-rich myofiber mass and a relative expansion of connective tissue and ECF (26). Both a relative increase in intramuscular AT and a lowering of SM cell mass would reduce the overall TBK-SM ratio. Additional studies are needed to test this hypothesis. Whatever the mechanism, the simple SM prediction model based on the TBK-SM ratio would need modification for subjects aged 70 y. Appropriate TBK/SM coefficients are presented in Table 3 by age group. Several investigators (27, 28) made a similar observation of an age-related lowering of the TBK-FFM ratio.
There are 2 error sources to consider with the ratio model approach. These are measurement error and model error.
Measurement error
TBK assessment is the only source of measurement error in the ratio model method. The error caused by TBK assessment can be evaluated in the subjects in the present study by assuming a mean body composition as shown in Table 2 and a TBK measurement precision of ± 2.4% as described in Subjects and Methods,
 | (14) |
 | (15) |
The SM estimation error in this approach is thus 0.5–1.0 kg in healthy adults.
Model error
The suggested constancy of the TBK-SM ratio is based on 3 assumptions. First, we assume that the ratio of SM to other potassium-rich tissues and organs is stable. For instance, a large portion of body potassium exists within SM (ie, 60% for reference man), and the remaining 40% of potassium is present in non-SM components including organs, skin, AT, and skeleton (9). Second, we assume that the ratio of SM cells to SM ECF is stable. Third, we assume that the potassium concentration (ie, 155 mmol/kg H2O) is stable in SM cells and in other tissue and organ cells. Any variation in the 3 assumed stable ratios between subjects will cause a corresponding change in the TBK-SM ratio. Our observations across age groups indicate that the TBK-SM ratio is relatively stable up to an age of 70 y. Although our sample aged 70 y was small, the lower observed TBK-SM ratio suggests that 1 of the 3 assumptions may be invalid in the elderly.
Empirical model
The second approach was to link SM with TBK via a multiple regression prediction model and then cross-validate the model in another group. Our in vivo measurements showed that TBK is the strongest predictor and that alone it explains 95.9% of the observed between-individual variation of MRI-measured SM mass (ie, Equation 12). Of the easily acquired biological factors, age, sex, and race also had a small influence on SM prediction, after TBK was controlled for first. Accordingly, a multiple regression equation (Equation 13) was derived for predicting SM mass on the basis of TBK and these other easily acquired prediction variables. Adding age, sex, and race to TBK, Equation 13 explained 97% of the observed between-individual variation in MRI-measured SM mass. The SEE for the TBK-SM multiple regression prediction method (ie, 1.45 kg) was lower than that for Equation 12 (ie, 1.60 kg), which predicts SM by TBK alone.
As with the ratio model, the simple linear regression formula (Equation 12) should perform well in subjects aged < 70 y, although the complete validated model (Equation 13) with a lower SEE is preferred. The multiple regression model is also preferred when evaluating SM in subjects aged 70 y, but further studies with larger numbers of elderly subjects are needed for cross-validation purposes.
Comparison between SM prediction methods
MRI and CT are now applied as the criterion methods for measuring total-body SM mass. Other alternative methods include neutron activation analysis, anthropometric methods, bioelectrical impedance analysis, 24-h urinary creatinine and 3-methylhistidine excretion, and DXA-measured appendicular lean soft tissue mass (Table 4). On the basis of potassium-to-nitrogen ratios of SM and non-SM lean tissue, Burkinshaw et al (30) suggested a model for estimating total-body SM mass. However, this method underestimates SM by an average of 6.9 kg or 20.1% (P = 0.0001) in healthy men (31). The remaining 7 alternative methods can be empirically organized into 3 groups.
|
The methods in group II, which are urinary marker methods, are based on 24-h urinary creatinine and 3-methylhistidine excretion (7, 8). These 2 methods have intermediate SEEs (1.9 kg). However, both methods are impractical because they require a meat-free diet for 7 d and complete 24-h urine collections during the final 3 d of the diet. These 2 methods are therefore not suitable for routine measurement and field studies.
Group III, which consists of nonurinary laboratory methods, include a DXA method (29) and the currently suggested TBK method. Both the DXA and TBK methods have similar low SEEs (1.5–1.6 kg) and high r2 values (0.96). No radiation is administered with the whole-body counting TBK method, whereas DXA involves a small radiation dose, 1–10% of that of a chest X-ray. Both methods are thus convenient and safe for most subjects and are routinely approved by institutional review boards for both women and children. An additional advantage of the DXA method is that it may provide regional SM estimates (32).
About 30 whole-body counters are now available worldwide, and 11 of them are in the United States. The measurement of TBK by whole-body counting is rapid, convenient, and simple to carry out. This method can be applied in subjects of any age because no radiation is involved and no active subject participation is necessary. In addition to predicting whole-body SM, TBK measurements can also be applied to predict BCM, an important body component at the cellular level (17). Although the 4 whole-body counting facilities are very heavy and cannot be easily moved, the so-called "shadow shield" counter is much lighter than completely shielded facilities and can be applied in field studies (1).
Conclusion
The present research was initially prompted by the need for improved SM estimation methods that are safe and practical. The long-considered potential of whole-body 40K counting in evaluating total-body SM mass was critically examined, and a theoretical model was fitted with existing data, suggesting a sex-independent TBK-SM ratio of 122 mmol/kg. This ratio and its variability were explored as a prelude to developing a TBK-SM prediction formula that includes easily acquired variables such as age, sex, and race. The present study did not include children or patients with underlying diseases, and thus future validation studies are needed to evaluate the relation between TBK and SM in populations other than healthy adults.
|
REFERENCES |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
This article has been cited by other articles:
|
|
 |
|
  Z. Wang, S. Heshka, A. Pietrobelli, Z. Chen, A. M. Silva, L. B. Sardinha, J. Wang, D. Gallager, and S. B. Heymsfield A New Total Body Potassium Method to Estimate Total Body Skeletal Muscle Mass in Children J. Nutr., August 1, 2007; 137(8): 1988 - 1991. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 N. Morita, N. Takamura, T. Murakami, O. Jo, K. Aoyagi, S. Yamashita, and Y. Okumura Evaluation of fat-free mass by whole-body counter in Japanese healthy young adults Radiat Prot Dosimetry, January 1, 2007; 123(1): 128 - 130. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 L. Wielopolski, L. M. Ramirez, D. Gallagher, S. B. Heymsfield, and Z. M. Wang Measuring partial body potassium in the arm versus total body potassium J Appl Physiol, September 1, 2006; 101(3): 945 - 949. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. Zhu, M. K. Kuhlmann, G. A. Kaysen, S. Sarkar, C. Kaitwatcharachai, R. Khilnani, L. Stevens, E. F. Leonard, J. Wang, S. Heymsfield, et al. Segment-specific resistivity improves body fluid volume estimates from bioimpedance spectroscopy in hemodialysis patients J Appl Physiol, February 1, 2006; 100(2): 717 - 724. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 B. A. Pederson, J. M. Schroeder, G. E. Parker, M. W. Smith, A. A. DePaoli-Roach, and P. J. Roach Glucose Metabolism in Mice Lacking Muscle Glycogen Synthase Diabetes, December 1, 2005; 54(12): 3466 - 3473. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 G. A Kaysen, F. Zhu, S. Sarkar, S. B Heymsfield, J. Wong, C. Kaitwatcharachai, M. K Kuhlmann, and N. W Levin Estimation of total-body and limb muscle mass in hemodialysis patients by using multifrequency bioimpedance spectroscopy Am. J. Clinical Nutrition, November 1, 2005; 82(5): 988 - 995. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M.-P. St-Onge, Z. Wang, M. Horlick, J. Wang, and S. B. Heymsfield Dual-energy X-ray absorptiometry lean soft tissue hydration: independent contributions of intra- and extracellular water Am J Physiol Endocrinol Metab, November 1, 2004; 287(5): E842 - E847. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. C. Wells, A. J Murphy, H. M Buntain, R. M Greer, G. J Cleghorn, and P. S. Davies Adjusting body cell mass for size in women of differing nutritional status Am. J. Clinical Nutrition, August 1, 2004; 80(2): 333 - 336. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. Kim, S. Heshka, D. Gallagher, D. P. Kotler, L. Mayer, J. Albu, W. Shen, P. U. Freda, and S. B. Heymsfield Intermuscular adipose tissue-free skeletal muscle mass: estimation by dual-energy X-ray absorptiometry in adults J Appl Physiol, August 1, 2004; 97(2): 655 - 660. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 I. Janssen, R. N. Baumgartner, R. Ross, I. H. Rosenberg, and R. Roubenoff Skeletal Muscle Cutpoints Associated with Elevated Physical Disability Risk in Older Men and Women Am. J. Epidemiol., February 15, 2004; 159(4): 413 - 421. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
Q. He, M. Heo, S. Heshka, J. Wang, R. N Pierson Jr, J. Albu, Z. Wang, S. B Heymsfield, and D. Gallagher Total body potassium differs by sex and race across the adult age span Am. J. Clinical Nutrition, July 1, 2003; 78(1): 72 - 77. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
