Predicting Regional Circumferences from Regional Body Composition Data

Authors

Toria McMullin, Brigham Young University
Dr. Robert T. Davidson, Brigham Young University

Keywords

regional circumferences, regional body composition data, health

College

Life Sciences

Department

Nutrition, Dietetics, and Food Science

Abstract

Due to the current trend obesity rates and the increased public awareness of the connection between body composition and health, individuals are becoming more and more interested in assessing and changing their own body composition. The current methods used to assess body composition include the following: dual-energy x-ray absorptiometry (DEXA), computerized tomography (CT) scans, magnetic resonance imaging (MRI), bioelectric impedance analysis (BIA), Near-Infrared Interactance (NIR), BodPod measurements, skinfold and circumference anthropometric measurements, and hydrodensitometry. Multicomponent models most accurately predict body composition. However, such models—including hydrodensitometry and DEXA—are either too difficult or too costly for practical, widespread consideration. Other methods are also impractical due to their cost, large measurement error, or reliance upon skilled technicians. Consequently, more research needs to be done in order to accurately and inexpensively help individuals predict body composition and body composition changes associated with changes in weight.

Recommended Citation

McMullin, Toria and Davidson, Dr. Robert T. (2013) "Predicting Regional Circumferences from Regional Body Composition Data," Journal of Undergraduate Research: Vol. 2013: Iss. 1, Article 1361.
Available at: https://scholarsarchive.byu.edu/jur/vol2013/iss1/1361