Body mass prediction from femoral volume and sixteen other femoral variables in the elderly: BMI and adipose tissue effects.

Abstract

The frequently used prediction equations of body mass do not seem appropriate for elderly individuals. Here, we establish the relationship between femoral dimensions and known body mass in elderly individuals in order to develop prediction formulas and identify the factors affecting their accuracy. The body mass linear least-squares regression is based on 17 femoral dimensions, including femoral volume, and 66 individuals. Body proportion and composition effects on accuracy are analyzed by means of the body mass index (BMI) and on a subset sample (n = 25), by means of the masses of adipose, bone and muscle tissues. Most variables significantly reflect body mass. Among them, six dimensions (e.g., biepicondylar breadth, femoral volume, and head femoral diameter) present percent standard errors of estimate ranging from 9.5 to 11% (r = 0.72-0.81) in normal BMI samples. Correlations are clearly lower in samples with normal and abnormal BMI [r = 0.38-0.58; % of standard error of estimate (SEE) = 17.3-19.6%] and not significantly correlated in females (femoral volume) who present high proportions of abnormal BMI and adipose tissue. In the subset, femoral volume is well correlated with bone mass (r = 0.88; %SEE = 7.9%) and lean body mass (r = 0.67; %SEE = 17.2%). Our body mass estimation equations for elderly individuals are relevant since relatively low correlations are recurrent in studies using younger individuals of known body mass. However, age, sex, lifestyle, and skeleton considerations of studied populations can provide information about the relevance of the body mass estimation, which is dependent on the BMI classification and the proportion of adipose tissue. Our general considerations can be used for studies of younger individuals.