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Fat-free mass
Table 3 : Evaluation of Fat-Free Mass predictive equations in 103 Dutch obese adolescents, based on bias, RMSE, and percentage accurate prediction, sorted by % accurate prediction
FFM predictive equation
Kg/d % % % % % % kg
FFM-DXA 56.1 9.8
Deurenberg’90(21) 57.1 9.2 68.0 4.9 27.2 2.2 -14.0 12.6 2.8
Gray (22) 55.7 8.3 63.1 18.4 18.4 -0.1 -16.4 12.0 3.2
Kyle (23) 56.4 8.4 61.2 15.5 23.3 1.2 -10.3 17.2 3.1
Lukaski (34) 53.7 8.5 54.4 39.8 5.8 -3.8 -17.3 11.0 3.9
Sun (35) 57.1 9.6 49.5 16.5 34.0 2.2 -11.2 18.8 3.8
Houtkooper(19) 58.9 9.4 44.7 2.9 52.4 5.4 -12.8 19.2 4.0
Deurenberg’91(18) 58.8 9.3 40.8 2.9 56.3 5.3 -10.7 17.8 3.9
Haroun(10) 59.5 10.9 35.9 7.8 56.3 6.2 -13.0 29.7 5.7
Lazzer(9) 51.2 8.5 28.2 69.9 1.9 -8.3 -23.2 9.0 6.4
Horie (36) 62.5 9.5 17.5 1.0 81.6 12.0 -5.4 29.7 7.4
Wabitsch(8) 49.8 7.6 7.8 92.2 0.0 -10.7 -25.1 3.0 7.1
Schaefer (20) 45.9 6.8 1.9 98.1 0.0 -17.6 -29.3 -0.7 11.0
Suprasongsin (33) 68.0 11.0 1.0 0.0 99.0 21.6 0.1 36.2 12.4
1As measured; 2The percentage of subjects predicted by this predictive equation within 5% of the measured value; 3The percentage of subjects predicted by this predictive equation <5% of the measured value; 4The percentage of subjects predicted by this predictive equation >5% of the measured value; 5Mean percentage error between predictive equation and the measured value; 6The largest underprediction that was found with this predictive equation as a percentage of the measured value; 7The largest over prediction that was found with this predictive equation as a percentage of the measured value; 8Root mean squared prediction error.
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FFM1
SD
Accurate predictions2
Under predictions3
Over predictions4
Bias5
Maximum negative error6
Maximum positive error7
RMSE8