Table 3.

Evaluation of prediction equation accuracy in comparison with RMR measured by indirect calorimetry^†

(Mean values and standard deviations; limits of agreement (LOA); percentages)

	REE (kcal/d)		Bias (P-M)								Slope (kcal/d per 100 kcal/d)		Intercept (kcal/d)
	Mean	sd	Mean	sd	95 % LOA (± 2 sd)	RMSE	Accurate predictions within ± 5 %‡ (%)	Accurate predictions within  ± 10 %§ (%)	Underpredictionsǁ (%)	Overpredictions¶ (%)	Mean	sd	Mean	sd
RMR measured	1424	247
Harris–Benedict	1502	162	78*	157	−229, 384	174	33⋅6	60⋅8	7⋅2	32⋅0	−4⋅6*	0⋅1	757*	88
Henry	1432	202	8	163	−311, 327	153	41⋅6	65⋅6	14⋅4	20⋅0	−0⋅2*	0⋅1	335*	96
Mifflin St–Jeor	1424	180	0	153	−300, 300	162	43⋅2	71⋅2	12⋅0	16⋅8	−3⋅5*	0⋅1	503*	86
Owen	1303	131	−121*	165	−443, 202	204	24⋅8	59⋅2	36⋅8	4⋅0	−6⋅8*	0⋅1	803*	76
Schofield	1466	211	42*	173	−297, 381	177	29⋅6	63⋅2	13⋅6	23⋅2	−1⋅8*	0⋅5	313*	83

REE, resting energy expenditure; P-M, predicted RMR minus measured RMR; RMSE, root-mean-square error calculated as √(Σ(actual RMR – predicted RMR)²)/n.

^*Mean value was significantly different from zero (P < 0⋅05).

^†To convert kcal to kJ, multiply by 4·184.

^‡Percentage of participants with predicted RMR within 5 % of measured RMR.

^§Percentage of participants with predicted RMR within 10 % of measured RMR.

^ǁPercentage of participants with predicted RMR being more than 10 % below measured RMR.

^¶Percentage of participants with predicted RMR being more than 10 % above measured RMR.