Literature DB >> 12499326

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

ZiMian Wang1, Shankuan Zhu, Jack Wang, Richard N Pierson, Steven B Heymsfield.   

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 (40)K. 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 >or= 20 y were recruited for body-composition evaluation. TBK and SM were measured by whole-body (40)K 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/m(2)) 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 >or= 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 (40)K measurements by whole-body counting. These methods afford an opportunity to predict SM mass from TBK data collected in healthy adults.

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Year:  2003        PMID: 12499326     DOI: 10.1093/ajcn/77.1.76

Source DB:  PubMed          Journal:  Am J Clin Nutr        ISSN: 0002-9165            Impact factor:   7.045


  16 in total

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