1. Reliability of Head, Neck, and Trunk Anthropometric Measurements Used for Predicting Segment Tissue Masses in Living Humans
- Author
-
David M. Andrews, Charles Kahelin, Nicole C. George, and Timothy A. Burkhart
- Subjects
Adult ,Male ,Adolescent ,Intraclass correlation ,0206 medical engineering ,Biophysics ,02 engineering and technology ,03 medical and health sciences ,0302 clinical medicine ,Predictive Value of Tests ,medicine ,Humans ,Orthopedics and Sports Medicine ,Reliability (statistics) ,Mathematics ,Anthropometry ,Rehabilitation ,Head neck ,Reproducibility of Results ,Torso ,030229 sport sciences ,Anatomy ,020601 biomedical engineering ,Trunk ,Biomechanical Phenomena ,medicine.anatomical_structure ,Body Composition ,Female ,Head ,Neck - Abstract
Soft and rigid tissue mass prediction equations have been previously developed and validated for the segments of the upper and lower extremities in living humans using simple anthropometric measurements. The reliability of these measurements has been found to be good to excellent for all measurement types (segment lengths, circumferences, breadths, skinfolds). However, the reliability of the measurements needed to develop corresponding equations for the head, neck, and trunk has yet to be determined. The purpose of this study was to quantify the inter- and intrameasurer reliability of 34 surface anthropometric measurements of the head, neck, and trunk segments. Measurements (11 lengths, 7 circumferences, 11 breadths, 5 skinfolds) were taken twice separately on 50 healthy, university-age individuals using standard anthropometric tools. The mean inter- and intrameasurer measurement differences were fairly small overall, with 64.7% and 67.6% of the relative differences less than 5%, respectively. All measurements, except for the right lateral trunk, had intraclass correlation coefficients (ICCs) greater than 0.75, and coefficients of variation (CVs) less than 10%, indicating good reliability overall. These results are consistent with previous work for the extremities and provide support for the use of the defined surface measurements for future tissue mass prediction equation development.
- Published
- 2017