New Predictive Equations for Resting Energy Expenditure in Normal to Overweight and Obese Population (P16-048-19) - Almajwal, Ali (Curr Dev Nutr, 2019)
OBJECTIVES: The unique demographic and dietary characteristics of our population require the development of a new equation to estimate the resting energy expenditure (REE). This study presented new equations characteristic to our population. METHODS: A set of predictive equations for REE was derived for 427 healthy male and female subjects (aged 18–57 ± 14 years). Measurement of REE (REEm) was done by the indirect calorimetry (IC) and its prediction (REEp) by using nine equations. REEp was compared with REEm to determine the predictive accuracy of these equations. Using IC and anthropometrics for stepwise linear regression analysis, a new equation to predict REE of Saudi men and women was developed. RESULTS: Using a number of parameters (bias, underprediction, overprediction, % accurate prediction), our results suggested that almost all (9/9 in men and 7/9 in women) equations either underpredicted or overpredicted (2/9) REE. None of the already existing equations showed an acceptable REEp/REEm difference as low as 5%, and an accurate prediction (∼55%) at the individual level. Based on these findings, a new prediction equation (hereafter referred to as Almajwal–Abulmeaty [AA] equation) was developed using this study's data, after a rigorous stepwise regression analysis using the following formula: REE = 3832.955 + BW [Kg] × 48.037 − Ht [Cm] × 30.642 + gender × 141.268 − age [years] × 4.525. The regression model accounted for about 70% of the variance in REEm (R(2) = 0.702). CONCLUSIONS: Previous equations likely over- or underpredicted REE. Therefore, the new predictive “AA equation” developed in this study is recommended for the estimation of REE in young to middle-aged Saudi men and women with different body mass index. Future research is also required for further clinical and cross-validation of this new equation. FUNDING SOURCES: This study was supported by the King Abdulaziz City for Science and Technology (grant number 11 – MED 1966 – 02). SUPPORTING TABLES, IMAGES AND/OR GRAPHS: