Related Experiment Video
Updated: May 10, 2026

Clinical Anthropometrics and Body Composition from 3-Dimensional Optical Imaging
Published on: June 7, 2024
Predicting body composition in college students using the womersley and durnin body mass index equation
Jeremy P Loenneke1, Kathryn M Hirt, Jacob M Wilson
1Department of Health and Exercise Science. The University of Oklahoma, Norman, Oklahoma, USA.
Purpose:
When assessing fitness levels, body composition is usually measured. The purpose of this study was to determine the overall efficacy of a body mass index (BMI) equation for predicting body composition with respect to college aged participants.
Methods:
Body composition was measured using dual-energy x-ray absorptiometry (DXA) and was estimated using the Womersley and Durnin BMI prediction equation.
Results:
There was no significant (P=0.8) percent body fat (%BF) difference between the BMI prediction equation and DXA (BMI Predicted=25 (10) [min=6; max=52] %BF vs DXA=25 (6) [min=10; max=45] %BF). In addition, a significant correlation was found between the two approaches (r=0.791, P=0.001). However, both the standard error of estimate (6.32 %BF) and total error (6.63 %BF) were outside acceptable ranges for prediction equations.
Conclusion:
The Womersley and Durnin equation for estimating %BF was not found to be a good estimate. Therefore, although the BMI predicted %BF has been previously found to predict skinfold estimated %BF, it does not appear valid in estimating %BF from DXA.
More Related Videos
07:44Evaluation of Changes in Hydration and Body Cell Mass with Bioelectrical Impedance Analysis after Exercise Program for Rheumatoid Arthritis Patients
Published on: July 14, 2023
08:22Using Deuterium Oxide as a Non-Invasive, Non-Lethal Tool for Assessing Body Composition and Water Consumption in Mammals
Published on: February 20, 2020
Related Concept Videos
Body Water Content and Fluid Compartments
Obesity
Composition of Body Fluids
Drug Dosing: Obese Patients
Mechanistic Models: Compartment Models in Individual and Population Analysis
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...