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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 R 2 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 (R 2  = .329 to .937), except head BMC (R 2  = .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.

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.

This study aimed to examine the effects of sex and sport on the tissue composition of the distal lower extremity of varsity athletes, in sports that involve repetitive-impact loading patterns. Fat mass, lean mass, bone mineral content and wobbling mass were predicted for the leg and leg + foot segments of varsity basketball, cross-country, soccer and volleyball athletes. The absolute masses were normalised to body mass, and also expressed relative to each other as ratios. Females and males differed on most normalised tissue masses and ratios by 11-101%. Characteristic differences were found in the normalised tissue masses across sports, with the lowest and highest values displayed by cross-country and volleyball (female)/basketball (male) athletes, respectively. Conversely, cross-country athletes had the highest wobbling mass:bone mineral content and lean mass:bone mineral content ratios for females by 10% and 16%, respectively. The differences between sports may be explained in part by different impact loading patterns characteristic of each sport. Tissue mass ratio differences between sports may suggest that the ratios of soft to rigid tissues are optimised by the body in response to typical loading patterns, and may therefore be useful in investigations of distal lower extremity injury mechanisms in athletes.

The purpose of this preliminary investigation was to determine the relative role of the distal lower extremity tissue masses of varsity athletes in predicting distal lower extremity injury sustained during a competitive season. One hundred male and female varsity athletes (basketball, volleyball, soccer, cross country) completed a questionnaire on general health, physiological, and psychosocial variables, during each sport's respective training camp. A series of anthropometric measurements were used as inputs to distal lower extremity tissue mass prediction equations to calculate lean mass, fat mass, bone mineral content and wobbling mass (lean mass + fat mass) and tissue mass ratios. Athletes were monitored throughout their respective seasons and were instructed to report any distal lower extremity injuries to a certified athletic therapist who was responsible for assessing and confirming the reports. Logistic regression analyses were performed to determine which variables significantly predicted distal lower extremity injury. Mean leg fat mass:bone mass (OR = 1.6, CI = 1.0 - 2.5), and competition surface (rubber OR = 8.5, CI = 1.5 - 47.7; artificial turf OR = 4.0, CI = 0.77 - 22.9) were identified as significant predictors of injury. Overall, tibia bone injuries were significantly associated with the ratio of fat mass:bone mineral content and the surface on which the athletes compete.

The purpose of this study was to derive and validate regression equations for the prediction of fat mass (FM), lean mass (LM), wobbling mass (WM), and bone mineral content (BMC) of the thigh, leg, and leg + foot segments of living people from easily measured segmental anthropometric measures. The segment masses of 68 university-age participants (26 M, 42 F) were obtained from full-body dual photon x-ray absorptiometry (DXA) scans, and were used as the criterion values against which predicted masses were compared. Comprehensive anthropometric measures (6 lengths, 6 circumferences, 8 breadths, 4 skinfolds) were taken bilaterally for the thigh and leg for each person. Stepwise multiple linear regression was used to derive a prediction equation for each mass type and segment. Prediction equations exhibited high adjusted R2 values in general (0.673 to 0.925), with higher correlations evident for the LM and WM equations than for FM and BMC. Predicted (equations) and measured (DXA) segment LM and WM were also found to be highly correlated (R2 = 0.85 to 0.96), and FM and BMC to a lesser extent (R2 = 0.49 to 0.78). Relative errors between predicted and measured masses ranged between 0.7% and -11.3% for all those in the validation sample (n = 16). These results on university-age men and women are encouraging and suggest that in vivo estimates of the soft tissue masses of the lower extremity can be made fairly accurately from simple segmental anthropometric measures.

Accurate body segment parameter (BSP) information is required for dynamic analyses of motion and the current methods available for obtaining these BSPs have been criticized. The purpose of this study was to determine whether dual energy X-ray absorptiometry (DXA) could accurately measure the BSPs of scanned objects and thus be used as a tool for measuring the BSPs of human subjects. Whole body mass (WBM) of 11 males was measured from a DXA scan and the values were compared to criterion scale-measured values by calculating the mean percent error. Two objects (plastic cylinder, human cadaver leg) were also scanned and DXA measurements of mass, length, centre of mass location (CM) and moment of inertia about the centre of mass (I(CM)) were made using custom software. Criterion BSP measurements were then made and compared to DXA BSP values by calculating the percent error. Criterion I(CM) measurements of the two objects were made using a pendulum technique and a second criterion I(CM) calculation was made for the cylinder using a geometric formula. A mean percent error of -1.05% +/-1.32% was found for WBM measurements of the human subjects. Errors for the cylinder and cadaver leg were under 3.2% for all BSPs except for I(CM) when DXA was compared to the pendulum method (14.3% and 8.2% for cylinder and leg, respectively). The errors between DXA and the pendulum method were attributed to uncertainty in the pendulum technique (J. Biomech. 2002, in Review). I(CM) error of the cylinder when DXA was compared to the geometric calculation was 2.63%. This error, combined with the low errors for all other BSPs, indicated that DXA can be used as a simple and accurate means of obtaining direct BSP information on living humans.