TY - JOUR
T1 - A model of prediction and cross-validation of fat-free mass in men with motor complete spinal cord injury
AU - Gorgey, Ashraf S.
AU - Dolbow, David R.
AU - Gater, David R.
PY - 2012/7
Y1 - 2012/7
N2 - Objectives: To establish and validate prediction equations by using body weight to predict legs, trunk, and whole-body fat-free mass (FFM) in men with chronic complete spinal cord injury (SCI). Design: Cross-sectional design. Setting: Research setting in a large medical center. Participants: Individuals with SCI (N=63) divided into prediction (n=42) and cross-validation (n=21) groups. Intervention: Not applicable. Main Outcome Measure: Whole-body FFM and regional FFM were determined by using dual-energy x-ray absorptiometry. Body weight was measured by using a wheelchair weighing scale after subtracting the weight of the chair. Results: Body weight predicted legs FFM (legs FFM=.09×body weight+6.1; R 2=.25, standard error of the estimate [SEE]=3.1kg, P<.01), trunk FFM (trunk FFM=.21×body weight+8.6; R 2=.56, SEE=3.6kg, P<.0001), and whole-body FFM (whole-body FFM=.288×body weight+26.3; R 2=.53, SEE=5.3kg, P<.0001). The whole-body FFM predicted (FFM predicted from the derived equations) shared 86% of the variance in whole-body FFM measured (FFM measured using dual-energy x-ray absorptiometry scan) (R 2=.86, SEE=1.8kg, P<.0001), 69% of trunk FFM measured, and 66% of legs FFM measured. The trunk FFM predicted shared 69% of the variance in trunk FFM measured (R 2=.69, SEE=2.7kg, P<.0001), and legs FFM predicted shared 67% of the variance in legs FFM measured (R 2=.67, SEE=2.8kg, P<.0001). Values of FFM did not differ between the prediction and validation groups. Conclusions: Body weight can be used to predict whole-body FFM and regional FFM. The predicted whole-body FFM improved the prediction of trunk FFM and legs FFM.
AB - Objectives: To establish and validate prediction equations by using body weight to predict legs, trunk, and whole-body fat-free mass (FFM) in men with chronic complete spinal cord injury (SCI). Design: Cross-sectional design. Setting: Research setting in a large medical center. Participants: Individuals with SCI (N=63) divided into prediction (n=42) and cross-validation (n=21) groups. Intervention: Not applicable. Main Outcome Measure: Whole-body FFM and regional FFM were determined by using dual-energy x-ray absorptiometry. Body weight was measured by using a wheelchair weighing scale after subtracting the weight of the chair. Results: Body weight predicted legs FFM (legs FFM=.09×body weight+6.1; R 2=.25, standard error of the estimate [SEE]=3.1kg, P<.01), trunk FFM (trunk FFM=.21×body weight+8.6; R 2=.56, SEE=3.6kg, P<.0001), and whole-body FFM (whole-body FFM=.288×body weight+26.3; R 2=.53, SEE=5.3kg, P<.0001). The whole-body FFM predicted (FFM predicted from the derived equations) shared 86% of the variance in whole-body FFM measured (FFM measured using dual-energy x-ray absorptiometry scan) (R 2=.86, SEE=1.8kg, P<.0001), 69% of trunk FFM measured, and 66% of legs FFM measured. The trunk FFM predicted shared 69% of the variance in trunk FFM measured (R 2=.69, SEE=2.7kg, P<.0001), and legs FFM predicted shared 67% of the variance in legs FFM measured (R 2=.67, SEE=2.8kg, P<.0001). Values of FFM did not differ between the prediction and validation groups. Conclusions: Body weight can be used to predict whole-body FFM and regional FFM. The predicted whole-body FFM improved the prediction of trunk FFM and legs FFM.
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U2 - 10.1016/j.apmr.2012.02.027
DO - 10.1016/j.apmr.2012.02.027
M3 - Article
C2 - 22426241
AN - SCOPUS:84863315072
SN - 0003-9993
VL - 93
SP - 1240
EP - 1245
JO - Archives of Physical Medicine and Rehabilitation
JF - Archives of Physical Medicine and Rehabilitation
IS - 7
ER -