Development and validation of a simple anthropometric equation to predict appendicular skeletal muscle mass

Ryoko Kawakami*, Motohiko Miyachi, Kumpei Tanisawa, Tomoko Ito, Chiyoko Usui, Taishi Midorikawa, Suguru Torii, Kaori Ishii, Katsuhiko Suzuki, Shizuo Sakamoto, Mitsuru Higuchi, Isao Muraoka, Koichiro Oka

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Background & aims: A limited number of studies have developed simple anthropometric equations that can be implemented for predicting muscle mass in the local community. Several studies have suggested calf circumference as a simple and accurate surrogate maker for muscle mass. We aimed to develop and cross-validate a simple anthropometric equation, which incorporates calf circumference, to predict appendicular skeletal muscle mass (ASM) using dual-energy X-ray absorptiometry (DXA). Furthermore, we conducted a comparative validity assessment of our equation with bioelectrical impedance analysis (BIA) and two previously reported equations using similar variables. Methods: ASM measurements were recorded for 1262 participants (837 men, 425 women) aged 40 years or older. Participants were randomly divided into the development or validation group. Stepwise multiple linear regression was applied to develop the DXA-measured ASM prediction equation. Parameters including age, sex, height, weight, waist circumference, and calf circumference were incorporated as predictor variables. Total error was calculated as the square root of the sum of the square of the difference between DXA-measured and predicted ASMs divided by the total number of individuals. Results: The most optimal ASM prediction equation developed was: ASM (kg) = 2.955 × sex (men = 1, women = 0) + 0.255 × weight (kg) − 0.130 × waist circumference (cm) + 0.308 × calf circumference (cm) + 0.081 × height (cm) − 11.897 (adjusted R2 = 0.94, standard error of the estimate = 1.2 kg). Our equation had smaller total error and higher intraclass correlation coefficient (ICC) values than those for BIA and two previously reported equations, for both men and women (men, total error = 1.2 kg, ICC = 0.91; women, total error = 1.1 kg, ICC = 0.80). The correlation between DXA-measured ASM and predicted ASM by the present equation was not significantly different from the correlation between DXA-measured ASM and BIA-measured ASM. Conclusions: The equation developed in this study can predict ASM more accurately as compared to equations where calf circumference is used as the sole variable and previously reported equations; it holds potential as a reliable and an effective substitute for estimating ASM.

Original languageEnglish
Pages (from-to)5523-5530
Number of pages8
JournalClinical Nutrition
Volume40
Issue number11
DOIs
Publication statusPublished - 2021 Nov

Keywords

  • Anthropometry
  • Body composition
  • Body size
  • Dual-energy X-ray absorptiometry scan
  • Prediction equation
  • Sarcopenia

ASJC Scopus subject areas

  • Nutrition and Dietetics
  • Critical Care and Intensive Care Medicine

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