T L Dupler1, H Tolson. 1. University of Houston-Clear Lake, Texas 77058, USA. dupler@cl.uh.edu
Abstract
BACKGROUND: The purpose of this study was to develop and validate anthropometric body composition prediction equations for elderly (i.e., > or =65 years old) men. This was necessary because of a lack of accurate and reliable predictive equations specifically developed for this population. METHODS:Seventy-five elderly men were randomly assigned to either an equation development sample (on = 50) or an equation validation sample (n = 25). Subject anthropometric measures were analyzed in a regression procedure with hydrodensitometry-determined body density, percentage of fat, fat-free mass, and fat weight to develop prediction equations for each body composition variable. The equation estimates were then validated against the hydrostatically determined measures. RESULTS: Four equations were developed and validated for the estimation of elderly male body composition variables [one each for body density (R2 = .66, SEE = +/- .01, where SEE is the standard error of estimate), percentage of fat (R2 = .66, SEE = +/- 4.43), fat-free mass (R2 = .88, SEE = +/- 3.94, and fat weight (R2 = .90, SEE = +/- 4.11)]. The equations provided estimates of body density, percentage of fat, fat-free mass, and fat weight, which were not statistically different from the hydrostatically determined criterion variables. CONCLUSIONS: The results of this study indicate that accurate and reliable anthropometric predictive equations can be developed for an active and healthy elderly male population. These equations may be used for accurate epidemiological testing of this group's body composition variables.
RCT Entities:
BACKGROUND: The purpose of this study was to develop and validate anthropometric body composition prediction equations for elderly (i.e., > or =65 years old) men. This was necessary because of a lack of accurate and reliable predictive equations specifically developed for this population. METHODS: Seventy-five elderly men were randomly assigned to either an equation development sample (on = 50) or an equation validation sample (n = 25). Subject anthropometric measures were analyzed in a regression procedure with hydrodensitometry-determined body density, percentage of fat, fat-free mass, and fat weight to develop prediction equations for each body composition variable. The equation estimates were then validated against the hydrostatically determined measures. RESULTS: Four equations were developed and validated for the estimation of elderly male body composition variables [one each for body density (R2 = .66, SEE = +/- .01, where SEE is the standard error of estimate), percentage of fat (R2 = .66, SEE = +/- 4.43), fat-free mass (R2 = .88, SEE = +/- 3.94, and fat weight (R2 = .90, SEE = +/- 4.11)]. The equations provided estimates of body density, percentage of fat, fat-free mass, and fat weight, which were not statistically different from the hydrostatically determined criterion variables. CONCLUSIONS: The results of this study indicate that accurate and reliable anthropometric predictive equations can be developed for an active and healthy elderly male population. These equations may be used for accurate epidemiological testing of this group's body composition variables.
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