Anthropometric predictors of body fat as measured by hydrostatic weighing in Guatemalan adults

BACKGROUND: Most predictive equations currently used to assess percentage body fat (%BF) were derived from persons in industrialized Western societies. OBJECTIVE: We developed equations to predict %BF from anthropometric measurements in rural and urban Guatemalan adults. DESIGN: 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. RESULTS: 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. CONCLUSION: These equations performed better in this developing-country population than did previously published equations.