Aims: The aims of this study were: to develop new equations for predicting resting energy expenditure (REE) in obese Italian subjects according to body composition parameters; to compare them with predicted values estimated by other REE prediction equations; and to cross-validate our equations using a validation set cohort. Methods: Four hundred patients were enrolled and divided into three groups. Besides anthropometry and REE (indirect calorimetry), total body fat and lean were evaluated by dual X-ray absorptiometry, and fat mass and fat-free mass by bioelectrical impedance analysis. Results: The subjects eligible to participate were 330. Group 1 (n = 174) was used to develop (R2 = 0.79) and (R2 = 0.77). Group 2 (n = 115) was used to generate (R2 = 0.85) and (R2 = 0.81). Group 3 (n = 41) was used to cross-validate the equations. Conclusion: Equations 1 and 3 are reliable to measure REE from calorimetry and better than other equations that use anthropometric variables as predictors of REE. Further analysis in different populations is required before it can be applied in clinical practice.
De Lorenzo, A., Di Renzo, L., Morini, P., de Miranda, R.c., Romano, L., Colica, C. (2018). New equations to estimate resting energy expenditure in obese adults from body composition. ACTA DIABETOLOGICA, 55(1), 59-66 [10.1007/s00592-017-1061-3].
New equations to estimate resting energy expenditure in obese adults from body composition
De Lorenzo, Antonino;Di Renzo, Laura;de Miranda, Renata Costa;
2018-01-01
Abstract
Aims: The aims of this study were: to develop new equations for predicting resting energy expenditure (REE) in obese Italian subjects according to body composition parameters; to compare them with predicted values estimated by other REE prediction equations; and to cross-validate our equations using a validation set cohort. Methods: Four hundred patients were enrolled and divided into three groups. Besides anthropometry and REE (indirect calorimetry), total body fat and lean were evaluated by dual X-ray absorptiometry, and fat mass and fat-free mass by bioelectrical impedance analysis. Results: The subjects eligible to participate were 330. Group 1 (n = 174) was used to develop (R2 = 0.79) and (R2 = 0.77). Group 2 (n = 115) was used to generate (R2 = 0.85) and (R2 = 0.81). Group 3 (n = 41) was used to cross-validate the equations. Conclusion: Equations 1 and 3 are reliable to measure REE from calorimetry and better than other equations that use anthropometric variables as predictors of REE. Further analysis in different populations is required before it can be applied in clinical practice.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
