巴西老年妇女阑尾肌质量的20个人体测量预测方程的交叉验证:一项横断面研究

P. Abdalla, L. Bohn, A. P. Santos, Leonardo Santos Lopes da Silva, M. Tasinafo, A. C. R. Venturini, N. Ramos, P. M. Pardo, J. Mota, D. Machado
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引用次数: 1

摘要

目的:检验巴西老年妇女阑尾肌质量(AMM)人体测量预测方程的交叉验证。方法:对67例老年妇女(69.84±5.95岁)进行人体测量。将双能x射线吸收仪(AMMDXA)获得的AMM (kg)参考值与用于估计老年人AMM的20个人体测量方程进行比较。配对t检验(p < 0.05)、估计的标准误差(SEE < 3.50 kg)和r2 < 0.70证实了方程的有效性。预测和参考之间的一致性也得到了验证(Bland-Altman)。结果:4个美国方程和1个墨西哥方程与AMMDXA无统计学差异(p < 0.05),但没有合适的r2值进行验证。美国国家健康与营养调查(NHANES)公式AMM (kg) = (-0.04 ×年龄[年]+ (0.46 ×小腿围[cm]) + (0.32 ×臂围[cm]) + (0.11 ×大腿围[cm]) - (0.27 ×体重指数[BMI, kg/m2]) + (0.07 ×腰围[cm]) - 13 119)表现最佳(r2 = 0.64;SEE = 3.24 kg),平均差异最小(0.26 kg),极端值无异方差,与巴西样本高度一致(-3.90至3.40 kg)。结论:当无法获得给定人群的特定方程时,允许使用具有更大样本代表性和科学可靠分析数据的通用方程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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 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.
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