Ramirez-Zea Manuel, Torun Benjamin, Martorell Reynaldo, Stein Aryeh D
Institute of Nutrition of Central America and Panama, PO Box 1188, Calzada Roosevelt, Zona 11, Guatemala City, Guatemala 01011.
Am J Clin Nutr. 2006 Apr;83(4):795-802. doi: 10.1093/ajcn/83.4.795.
Most predictive equations currently used to assess percentage body fat (%BF) were derived from persons in industrialized Western societies.
We developed equations to predict %BF from anthropometric measurements in rural and urban Guatemalan adults.
Body density was measured in 123 women and 114 men by using hydrostatic weighing and simultaneous measurement of residual lung volume. Anthropometric measures included weight (in kg), height (in cm), 4 skinfold thicknesses [(STs) in mm], and 6 circumferences (in cm). Sex-specific multiple linear regression models were developed with %BF as the dependent variable and age, residence (rural or urban), and all anthropometric measures as independent variables (the "full" model). A "simplified" model was developed by using age, residence, weight, height, and arm, abdominal, and calf circumferences as independent variables.
The preferred full models were %BF = -80.261 - (weight x 0.623) + (height x 0.214) + (tricipital ST x 0.379) + (abdominal ST x 0.202) + (abdominal circumference x 0.940) + (thigh circumference x 0.316); root mean square error (RMSE) = 3.0; and pure error (PE) = 3.4 for men and %BF = -15.471 + (tricipital ST x 0.332) + (subscapular ST x 0.154) + (abdominal ST x 0.119) + (hip circumference x 0.356); RMSE = 2.4; and PE = 2.9 for women. The preferred simplified models were %BF = -48.472 - (weight x 0.257) + (abdominal circumference x 0.989); RMSE = 3.8; and PE = 3.7 for men and %BF = 19.420 + (weight x 0.385) - (height x 0.215) + (abdominal circumference x 0.265); RMSE = 3.5; and PE = 3.5 for women.
These equations performed better in this developing-country population than did previously published equations.
目前用于评估体脂百分比（%BF）的大多数预测方程是根据西方工业化社会的人群推导出来的。
我们开发了根据危地马拉城乡成年人的人体测量数据预测%BF的方程。
采用水下称重法并同时测量残气量，对123名女性和114名男性进行身体密度测量。人体测量指标包括体重（千克）、身高（厘米）、4处皮褶厚度（毫米）和6处周长（厘米）。以%BF为因变量，年龄、居住地（农村或城市）以及所有人体测量指标为自变量，建立了性别特异性多元线性回归模型（“完整”模型）。通过使用年龄、居住地、体重、身高以及手臂、腹部和小腿周长作为自变量，建立了一个“简化”模型。
首选的完整模型男性为%BF = –80.261 –（体重×0.623）+（身高×0.214）+（三头肌皮褶厚度×0.379）+（腹部皮褶厚度×0.202）+（腹围×0.940）+（大腿围×0.316）；均方根误差（RMSE）= 3.0；纯误差（PE）= 3.4，女性为%BF = –15.471 +（三头肌皮褶厚度×0.332）+（肩胛下皮褶厚度×0.154）+（腹部皮褶厚度×0.119）+（臀围×0.356）；RMSE = 2.4；PE = 2.9。首选的简化模型男性为%BF = –48.472 –（体重×0.257）+（腹围×0.989）；RMSE = 3.8；PE = 3.7，女性为%BF = 19.420 +（体重×0.385）–（身高×0.215）+（腹围×0.265）；RMSE = 3.5；PE = 3.5。
在这个发展中国家人群中，这些方程比之前发表的方程表现更好。
