Cross-validation of 20 anthropometric prediction equations for appendicular muscle mass in older Brazilian women: a cross-sectional study

Objective: To test the cross-validation of anthropometric prediction equations for appendicular muscle mass (AMM) in older Brazilian women. Methods: Sixty-seven older women (69.84 ± 5.95 years old) underwent anthropometric measurements. AMM (kg) reference values obtained by dual-energy X-ray absorpt...

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Veröffentlicht in:Geriatrics, Gerontology and Aging (Online) Gerontology and Aging (Online), 2023-01, Vol.16, p.1-5
Hauptverfasser: Abdalla, Pedro Pugliesi, Bohn, Lucimere, Santos, André Pereira dos, Silva, Leonardo Santos Lopes da, Tasinafo, Márcio Fernando, Venturini, Ana Claudia Rossini, Ramos, Nilo César, Pardo, Pablo Jorge Marcos, Mota, Jorge, Machado, Dalmo Roberto Lopes
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Sprache:eng
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Zusammenfassung:Objective: To test the cross-validation of anthropometric prediction equations for appendicular muscle mass (AMM) in older Brazilian women. Methods: Sixty-seven older women (69.84 ± 5.95 years old) underwent anthropometric measurements. AMM (kg) reference values obtained by dual-energy X-ray absorptiometry (AMMDXA) were compared to 20 anthropometric equations for estimating AMM in older adults. A paired t-test (p > 0.05), standard error of estimate (SEE < 3.50 kg), and r2 > 0.70 confirmed the validity of the equations. The agreement between predictions and the reference was also verified (Bland-Altman). Results: Four American equations and one Mexican equation were not statistically different from AMMDXA (p > 0.05) but did not present suitable r2 values for validation. The American equation from the National Health and Nutrition Examination Survey (NHANES), AMM (kg) = (-0.04 × age [years]) + (0.46 × calf circumference [cm]) + (0.32 × arm circumference [cm]) + (0.11 × thigh circumference [cm]) – (0.27 × body mass index [BMI, kg/m2]) + (0.07 × waist circumference [cm]) – 13 119) showed the best performance (r2 = 0.64; SEE = 3.24 kg), with minimal mean difference (0.26 kg), no heteroscedasticity for extreme values, and with high agreement with the Brazilian sample (-3.90 to 3.40 kg). Conclusion: When specific equations for a given population are not available, the use of generic equations of greater sample representativeness with scientifically and reliably analyzed data is allowed.
ISSN:2447-2123
2447-2123
DOI:10.53886/gga.e0220034