Predictive equation for assessing appendicular lean soft tissue mass using bioelectric impedance analysis in older adults: Effect of body fat distribution
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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.
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BIA, Body composition, Elderly, Sarcopenia, Skeletal muscle index
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Inglês
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Experimental Gerontology, v. 150.
