whole-body skeletal muscle mass

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76 Am J Clin Nutr2003;77:7682. Printed in USA. 2003 American Society for Clinical Nutrition

Whole-body skeletal muscle mass: development and validation oftotal-body potassium prediction models1-3

ZiMian Wang, Shankuan Zhu, Jack Wang, Richard N Pierson Jr, and Steven B Heymsfield

ABSTRACT

Background:A substantial proportion of total body potassium

(TBK) in humans is found in skeletal muscle (SM), thus

afford ing a means of predicting total-body SM from whole-body

countermeasured 40K. There are now > 30 whole-body counters

worldwide that have large cross-sectional and longitudinal TBK

databases.

Objective: We explored 2 SM prediction approaches, one based

on the assumption that the ratio of TBK to SM is stable in healthyadults 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 tissuefree SM as the

ratio of TBK to SM.

Results: A total of 300 subjects (139 men and 161 women) of var-

ious ethnicities with a mean ( SD) body mass index (in kg/m2)

of 25.1 5.4 met the study entry criteria. The mean conceptual

modelderived TBK-SM ratio was 122 mmol/kg, which was com-

parable 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 signifi-

cant 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. Am J Clin Nutr2003;77:7682.

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

Skeletal muscle (SM), the largest component of the tissue-

organ body-composition level in adult humans, plays an impor-

tant role in physiologic processes and energy metabolism. Whole-

body SM mass is influenced by several modifying biological

factors such as age, sex, race, physical activity, and disease (1).

Although of growing research and clinical interest (2), SM mass

remains a difficult or impractical body component to accurately

quantify in living humans.

1 From the Obesity Research Center, St Lukes-Roosevelt Hospital, Colum-

bia 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 Con-

trol Unit, 1090 Amsterdam Avenue, 14th Floor, New York, NY 10025. E-mail:

[email protected].

Received November 9, 2001.

Accepted for publication April 9, 2002.

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 appli-

cation 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 analy-

sis (25). 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 collectionbased

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, 68). 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 dis-

tributed entirely in the fat-free mass (FFM) compartment, and a

large proportion exists in SM. For example, 60% of TBK in ref-

erence man is found in SM (9). The ratio of TBK to FFM is

5459 mmol/kg for healthy females and 5962 mmol/kg for

healthy males (1, 10), and this relation provides a means of esti-

mating FFM from measured TBK (1, 11). Similarly, SM is dis-

tributed 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 (1214). 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.


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MUSCLE MEASUREMENT 77

A similar concept was advanced by Forbes (1), who first meas-

ured 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 measure-

ment method, such as MRI or CT, was unavailable 3 decades ago.

Whole-body

40

K counting is available at over 30 body-compositioncenters 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

Protocol

Our strategy was to provide 2 alternative means to predict total-

body SM mass from TBK. A conceptual cellular-level TBK/SM

model was first developed and then used, with available experi-

mental data, to explore the magnitude of the TBK-SM ratio. We

then specifically tested the model predictions by evaluating TBK

and SM in a large sample of healthy adults. Under ideal circum-

stances a stable TBK-SM ratio (k) could be used to predict total-

body SM as

SM = 1/k TBK (1)

A second modeling strategy was also applied because we

assumed at the outset that the TBK-SM ratio might have influ-

encing 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,

SM = F(TBK, age, sex, race) (2)

where age, sex, and race were entered as potential independent

predictor variables after controlling for TBK.

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),

TBK = KICF + KECF (3)

KICF can be expressed as the product of intracellular water (ICW)

and ICW potassium concentration ([K]ICW; KICF = ICW [K]ICW).

Similarly, KECF is the product of extracellular water (ECW) and

ECW potassium concentration ([K]ECW; KECF = ECW [K]ECW).

The cellular body-composition level is composed of 3 com-partments: 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: adi-

pose tissue (AT)free SM and anatomical SM. AT-free SM is com-

posed 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 BCM = m 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 ECF = n 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

TBK/AT-free SM = (KICF + KECF)/

(SM cells + SM ECF) = ([K]ICW ICW

+ [K]ECW ECW)/(m ICW/a + n ECW/b) (4)

Because total body water is made up of ICW and ECW, ECW

can be expressed as a function of ICW: ECW =E/I ICW, whereE/Iis the ratio of ECW to ICW. Equation 4 can be converted and

simplified as

TBK/AT-free SM = ([K]ICW ICW + [K]ECW ICW E/I)/[m ICW/a + n ICW (E/I)/b] = ([K]ICW + [K]ECW E/I)/(m/a + n/b E/I) (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 forMRI-measured SM as

TBK/MRI-measured SM = (1 f)

[([K]ICW + [K]ECW E/I)/(m/a + n/b E/I)] (6)

wherefis the fraction of MRI-measured SM that consists of inter-

stitial AT. As shown in Equation 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 varia-

tion range for each determinant was applied in the present study.

The cellular and extracellular potassium concentrations arephysiologically stable in mammals. Previous studies reported sim-

ilar [K]ICW and [K]ECW in mammals: 150160, 150 7.2 (SD), and

159 mmol/kg H2O for [K]ICW and 46 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 deter-

minant 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 0.690.71

and b = 0.98 with a variation range of 0.970.99) in an earlier

report (11).

E/Iis the ratio of ECW to ICW. We measured E/Iby combin-

ing 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 andn because of the difficulty

in quantifying cell mass and ECF within individual tissues in vivo.

Therefore, we based the estimates ofm and n on data available for ref-

erence man (9). In reference man, the amount of TBK is 3580 mmol


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TABLE 2

Baseline characteristics of the subjects (n = 300)1

Men (n = 139) Women (n = 161)

Age (y) 39.0 14.6 45.2 16.42

Body mass (kg) 80.4 13.4 66.5 14.63

Height (cm) 176.5 11.2 162.1 7.53

BMI (kg/m2) 25.6 3.9 25.3 5.1

Fat (%) 20.2 8.0 33.2 10.23

1x SD.2,3Significantly different from men (Students ttest): 2P < 0.01, 3 P < 0.001.

TABLE 3

Total body potassium (TBK), total-body skeletal muscle (SM), and ratio of TBK to SM by sex and age1

Men Women

Age (y) TBK2 SM3 TBK/SM TBK4 SM3 TBK/SM3

mmol kg mmol/kg mmol kg mmol/kg

2029 (n = 46 M, 30 F) 4110 567 34.3 5.8 120.6 7.1 2405 324 19.9 3.3 121.3 7.0

3039 (n = 38 M, 41 F) 4141 527 34.9 5.0 119.1 5.3 2504 360 21.2 3.6 119.1 9.0

4049 (n = 25 M, 32 F) 3877 641 32.4 6.6 120.6 6.9 2599 348 21.7 3.5 120.4 8.8

5059 (n = 17 M, 28 F) 3782 542 31.5 5.0 120.4 7.9 2442 295 20.9 3.2 117.4 8.2

6069 (n = 5 M, 14 F) 3490 457 29.3 4.0 119.3 3.6 2187 267 18.7 2.3 117.5 7.9

70 (n = 8 M, 16 F) 3343 388 28.9 4.4 116.6 8.2 2130 306 19.0 2.8 112.6 6.1

Total (n = 139 M, 161 F) 3970 592 33.3 5.7 119.9 6.7 2429 354 20.6 3.4 118.7 8.4

P for trend


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80 WANG ET AL

FIGURE 1. Total-body skeletal muscle (SM) measured by magnetic

resonance imaging plotted against total body potassium (TBK) measured

by whole-body 40K counting. SM (kg) = 0.0085 TBK (mmol) (r= 0.98,

P < 0.001; SEE = 1.60 kg; n = 300).

FIGURE 2. Bland-Altman (23) analysis of the cross-validation group. The

difference between skeletal muscle (SM) measured by magnetic resonance

imaging (MRI) and SM predicted by Equation 13 plotted against the MRI-

measured and predicted SM mean. The line describing the data is expressed

by the following equation:y = 0.0102x 0.54 (r= 0.052, P = 0.52; n = 150).

The 95% CI is indicated by the upper and lower lines.

SM (kg) = 0.0093 TBK (mmol) 1.31 sex + 0.59 black+ 0.024 age 3.21 (13)

where sex is 0 for women and 1 for men, and black is 1 for African

Americans and 0 for the other 3 ethnic groups. When Equation 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

In the present study we examined 2 different strategies for pre-dicting total-body SM mass from measured 40K, one based on a

TBK-SM ratio model and the other based on an empirical multi-

ple regression model. Both approaches appear to provide a good

means of estimating total-body SM in healthy adults.

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 TBK. This modeling approach is simi-lar to the use of 2 classic rat ios 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 interstitialAT 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 predic ti on mode ls in subject s aged < 70 y: AT-freeSM = 0.0082 TBK, and MRI-observed SM = 0.0083 TBK.

Our observed results indicating a relatively stable TBK-SM ratio

for women aged


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TABLE 4

Comparison of different methods of predicting whole-body skeletal muscle mass1

Method Main predictor SEE r2 Criterion Reference

kg

Anthropometric method (n = 244) Body mass and height 2.8 0.86 MRI 5

BIA (n = 388) Height2/R 2.7 0.86 MRI 4

Anthropometic method (n = 244) Skinfold thicknesses and circumferences 2.2 0.91 MRI 5

3-MH (n = 10) 24-h Urinary 3-methylhistidine 2.3 0.77 CT 8

Creatinine (n = 12) 24-h Urinary creatinine 1.9 0.85 CT 7DXA (n = 414) Appendicular lean soft tissue 1.6 0.96 MRI 29

Whole-body 40K counting (n = 300) TBK 1.5 0.96 MRI Present study

1 3-MH, 3-methylhistidine; BIA, bioelectrical impedance analysis; CT, computed axial tomography; DXA, dual-energy X-ray absorptiometry; MRI,

magnetic resonance imaging;R, resistance; TBK, total body potassium.

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 obser-vations across age groups indicate that the TBK-SM ratio is rela-

tively stable up to an age of70 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, Equa-

tion 12). Of theeasilyacquired biological factors, age, sex, and race

also had a small influence on SM prediction, after TBK was con-

trolled for first. Accordingly, a multiple regression equation (Equa-tion 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-SMmultiple 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, bio-

electrical 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) sug-

gested 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.

Group I, which consists of potential field methods, includes

bioelectrical impedance analysis (4) and 2 anthropometric meth-

ods (5), one based on body mass and height and the other on limb

skinfold thicknesses and circumferences. Each of these 3 meth-

ods is simple and can be readily applied in field settings. How-ever, the SEEs of these methods are large (2.22.8 kg), indicating

low estimation accuracy for individual subjects.

The methods in group II, which are urinary marker methods,

are based on 24-h urinary creatinine and 3-methylhistidine excre-

tion (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

(1.51.6 kg) and high r2 values (0.96). No radiation is adminis-

tered with the whole-body counting TBK method, whereas DXAinvolves a small radiation dose, 110% 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 meas-

urements 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, theso-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 evaluat-

ing 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


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82 WANG ET AL

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 under-

lying diseases, and thus future validation studies are needed to

evaluate the relation between TBK and SM in populations other

than healthy adults.

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