Validity of predictive equations to estimate RMR in females with varying BMI

Abstract

Estimation of RMR using prediction equations is the basis for calculating energy requirements. In the present study, RMR was predicted by Harris–Benedict, Schofield, Henry, Mifflin–St Jeor and Owen equations and measured by indirect calorimetry in 125 healthy adult women of varying BMI (17–44 kg/m2). Agreement between methods was assessed by Bland–Altman analyses and each equation was assessed for accuracy by calculating the percentage of individuals predicted within ± 10 % of measured RMR. Slopes and intercepts of bias as a function of average RMR (mean of predicted and measured RMR) were calculated by regression analyses. Predictors of equation bias were investigated using univariate and multivariate linear regression. At group level, bias (the difference between predicted and measured RMR) was not different from zero only for Mifflin–St Jeor (0 (sd 153) kcal/d (0 (sd 640) kJ/d)) and Henry (8 (sd 163) kcal/d (33 (sd 682) kJ/d)) equations. Mifflin–St Jeor and Henry equations were most accurate at the individual level and predicted RMR within 10 % of measured RMR in 71 and 66 % of participants, respectively. For all equations, limits of agreement were wide, slopes of bias were negative, and intercepts of bias were positive and significantly (P < 0⋅05) different from zero. Increasing age, height and BMI were associated with underestimation of RMR, but collectively these variables explained only 15 % of the variance in estimation bias. Overall accuracy of equations for prediction of RMR is low at the individual level, particularly in women with low and high RMR. The Mifflin–St Jeor equation was the most accurate for this dataset, but prediction errors were still observed in about one-third of participants.

Predictive Equations Overestimate Resting Metabolic Rate in Young Chilean Women with Excess Body Fat

“…The Mifflin–St Jeor equation showed the lowest overestimation of RMR in both women with overweight and obesity, so it is recommended as the most reliable, especially in subjects with obesity. This is consistent with what has been reported in other studies [ 37 , 43 , 44 ]. The equation was derived from measurements of RMR by indirect calorimetry that involved 251 men and 247 women, with 47% of the participants exhibiting overnutrition and BMI between 30 and 42 kg/m 2 ; unfortunately, the ethnic composition of the subjects was not reported [ 12 ].…”

“…However, it is not without some inaccuracies because it overestimated RMR IC in 69.5% and 44.4% of women with overweight and obesity, respectively. These values are much higher than those reported in other studies, in which the percentage of subjects with RMR IC overestimated reached 20% [ 28 , 37 , 44 ]. As for the FAO/WHO/UNU (1985) and FAO/WHO/UNU (2004) equations, the first equation showed a relatively better adequacy in our study.…”

Comparison of Various Predictive Energy Equations for Female University Students With Measured Basal Metabolic Rate

“…Similarly, Weijs and Vansant39 conducted a study in Belgian women and found that Harris-Benedict and Mifflin-St Jeor formulas were reported to be reliable in women with a BMI of 18.5 to 50.0 kg/m 2 . Thom et al13 also found that, in women with a normal-range BMI, Schofield, Owen, Mifflin-St Jeor, and Henry formulas provided similar accuracy rates. Our findings were consistent with these results, suggesting that the Mifflin-St Jeor formula may be used in healthy women subjects with a normal BMI.…”

The importance of education about women nutrition for Kader Kesehatan in the effort of stunting reduction in Indonesia

“…Pregnant women with MUAC <23.5 cm is more likely to have stunted child 22 . In order to deliver education and distribute sufficient intervention to women with higher risk of having stunted children, it is necessary to identify undernourished women using correct anthropometric measurement and indicators 15 24,25 . Aside of REE, total energy expenditure (TEE) calculation also needs the physical activity and thermic effect of food factor 26 .…”