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Nicole C. George, Charles Kahelin, Timothy A. Burkhart, and David M. Andrews

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.

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Danielle L. Gyemi, Charles Kahelin, Nicole C. George, and David M. Andrews

Accurate prediction of wobbling mass (WM), fat mass (FM), lean mass (LM), and bone mineral content (BMC) of living people using regression equations developed from anthropometric measures (lengths, circumferences, breadths, skinfolds) has previously been reported, but only for the extremities. Multiple linear stepwise regression was used to generate comparable equations for the head, neck, trunk, and pelvis of young adults (38 males, 38 females). Equations were validated using actual tissue masses from an independent sample of 13 males and 13 females by manually segmenting full-body dual-energy x-ray absorptiometry scans. Prediction equations exhibited adjusted R2 values ranging from .249 to .940, with more explained variance for LM and WM than BMC and FM, especially for the head and neck. Mean relative errors between predicted and actual tissue masses ranged from −11.07% (trunk FM) to 7.61% (neck FM). Actual and predicted tissue masses from all equations were significantly correlated (R2 = .329 to .937), except head BMC (R2 = .046). These results show promise for obtaining in-vivo head, neck, trunk, and pelvis tissue mass estimates in young adults. Further research is needed to improve head and neck FM and BMC predictions and develop tissue mass prediction equations for older populations.