Whole-body skeletal muscle mass: development and validation of total-body potassium prediction models

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  
Background: A substantial proportion of total body potassium (TBK) in humans is found in skeletal muscle (SM), thus affording a means of predicting total-body SM from whole-body counter–measured 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 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  
Skeletal muscle (SM), the largest component of the tissue-organ body-composition level in adult humans, plays an important 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.

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  
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 experimental 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 circumstances a stable TBK-SM ratio (k) could be used to predict total-body SM as

RESULTS  
Baseline characteristics
A total of 300 healthy adult subjects, of whom 139 were men (35 African Americans, 17 Asians, 63 whites, and 24 Hispanics) and 161 were women (56 African Americans, 18 Asians, 68 whites, and 19 Hispanics), met the study entry criteria. The baseline characteristics of the subjects are presented in Table 2. 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.

View this table:
TABLE 2 . Baseline characteristics of the subjects (n = 300)¹  
TBK-SM ratio
The men had significantly more TBK and MRI-measured SM than did the women (P < 0.001 for both). However, there was no significant difference (P = 0.17) in the TBK-SM ratio between the men and the women (119.9 ± 6.7 compared with 118.7 ± 8.4 mmol/kg, respectively), and both ratios were minimally (< 3%) smaller than the model-derived value of 122 mmol/kg for AT-free SM (Table 3). The TBK-SM ratio was inversely correlated (r = -0.22, P < 0.001; SEE = 7.5 mmol/kg) with age (n = 300),

DISCUSSION  
In the present study we examined 2 different strategies for predicting total-body SM mass from measured ⁴⁰K, one based on a TBK-SM ratio model and the other based on an empirical multiple 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 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,

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