S Toselli1, F Campa2, C N Matias3, Bruna Spolador de Alencar Silva4, Vanessa Ribeiro Dos Santos4, P Maietta Latessa5, L A Gobbo4. 1. Department of Biomedical and Neuromotor Science, University of Bologna, Italy. 2. Department for Life Quality Studies, University of Bologna, 47921 Rimini, Italy. Electronic address: Francesco.campa3@unibo.it. 3. CIDEFES -Universidade Lusófona, 1749-024 Lisboa, Portugal; Bioperformance & Nutrition Research Unit, Ingrediente Métrico S.A., 2740-262 Lisbon, Portugal. 4. Department of Physical Education, São Paulo State University, Presidente Prudente, Brazil. 5. Department for Life Quality Studies, University of Bologna, 47921 Rimini, Italy.
Abstract
BACKGROUND: Low muscle mass is associated with sarcopenia and increased mortality. Muscle mass, especially that of the limbs, is commonly estimated by dual-energy X-ray absorptiometry (DXA) or bioimpedance analysis (BIA). However, BIA-based predictive equations for estimating lean appendicular soft tissue mass (ALST) do not take into account body fat distribution, an important factor influencing DXA and BIA measurements. OBJECTIVES: To develop and cross-validate a BIA-based equation for estimating ALST with DXA as criterion, and to compare our new formula to three previously published models. METHODS: One-hundred eighty-four older adults (140 women and 44 men) (age 71.5 ± 7.3 years, body mass index 27.9 ± 5.3 kg/m2) were recruited. Participants were randomly split into validation (n = 118) and cross-validation groups (n = 66). Bioelectrical resistance was obtained with a phase-sensitive 50 kHz BIA device. RESULTS: A BIA-based model was developed for appendicular lean soft tissue mass [ALST (kg) = 5.982 + (0.188 × S2 / resistance) + (0.014 × waist circumference) + (0.046 × Wt) + (3.881 × sex) - (0.053 × age), where sex is 0 if female or 1 if male, Wt is weight (kg), and S is stature (cm) (R2 = 0.86, SEE = 1.35 kg)]. Cross validation revealed r2 of 0.91 and no mean bias. Two of three previously published models showed a trend to significantly overestimate ALST in our sample (p < 0.01). CONCLUSIONS: The new equation can be considered valid, with no observed bias and trend, thus affording practical means to quantify ALST mass in older adults.
BACKGROUND: Low muscle mass is associated with sarcopenia and increased mortality. Muscle mass, especially that of the limbs, is commonly estimated by dual-energy X-ray absorptiometry (DXA) or bioimpedance analysis (BIA). However, BIA-based predictive equations for estimating lean appendicular soft tissue mass (ALST) do not take into account body fat distribution, an important factor influencing DXA and BIA measurements. OBJECTIVES: To develop and cross-validate a BIA-based equation for estimating ALST with DXA as criterion, and to compare our new formula to three previously published models. METHODS: One-hundred eighty-four older adults (140 women and 44 men) (age 71.5 ± 7.3 years, body mass index 27.9 ± 5.3 kg/m2) were recruited. Participants were randomly split into validation (n = 118) and cross-validation groups (n = 66). Bioelectrical resistance was obtained with a phase-sensitive 50 kHz BIA device. RESULTS: A BIA-based model was developed for appendicular lean soft tissue mass [ALST (kg) = 5.982 + (0.188 × S2 / resistance) + (0.014 × waist circumference) + (0.046 × Wt) + (3.881 × sex) - (0.053 × age), where sex is 0 if female or 1 if male, Wt is weight (kg), and S is stature (cm) (R2 = 0.86, SEE = 1.35 kg)]. Cross validation revealed r2 of 0.91 and no mean bias. Two of three previously published models showed a trend to significantly overestimate ALST in our sample (p < 0.01). CONCLUSIONS: The new equation can be considered valid, with no observed bias and trend, thus affording practical means to quantify ALST mass in older adults.
Authors: Luís B Sardinha; Gil B Rosa; Megan Hetherington-Rauth; Inês R Correia; João P Magalhães; Analiza M Silva; Henry Lukaski Journal: Eur J Clin Nutr Date: 2022-10-17 Impact factor: 4.884