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Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes: what can we use?

ABSTRACT: Background:Evaluation of the resting energy expenditure (REE) is essential to ensure an appropriate dietary prescription for patients with type 2 diabetes. The aim of this record was to evaluate the accuracy of predictive equations for REE estimation in patients with type 2 diabetes, considering indirect calorimetry (IC) as the reference method. Methods:A cross-sectional study was performed in outpatients with type 2 diabetes. Clinical, body composition by electrical bioimpedance and laboratory variables were evaluated. The REE was measured by IC (QUARK RMR, Cosmed, Rome, Italy) and estimated by eleven predictive equations. Data were analyzed using Bland-Altman plots, paired t-tests, and Pearson's correlation coefficients. Results:Sixty-two patients were evaluated [50% female; mean age 63.1?±?5.2?years; diabetes duration of 11 (1-36) years, and mean A1C of 7.6?±?1.2%]. There was a wide variation in the accuracy of REE values predicted by equations when compared to IC REE measurement. In all patients, Ikeda and Mifflin St-Jeor equations were that most underestimated REE. And, the equations that overestimated the REE were proposed by Dietary Reference Intakes and Huang. The most accurate equations were FAO/WHO/UNO in women (-?1.8% difference) and Oxford in men (-?1.3% difference). Conclusion:In patients with type 2 diabetes, in the absence of IC, FAO/WHO/UNO and Oxford equations provide the best REE prediction in comparison to measured REE for women and men, respectively.

SUBMITTER: Grassi T

PROVIDER: S-EPMC7525981 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes: what can we use?

Grassi Thaiciane T Boeno Francesco Pinto FP de Freitas Mauren Minuzzo MM de Paula Tatiana Pedroso TP Viana Luciana Vercoza LV de Oliveira Alvaro Reischak AR Steemburgo Thais T

BMC nutrition 20200930

<h4>Background</h4>Evaluation of the resting energy expenditure (REE) is essential to ensure an appropriate dietary prescription for patients with type 2 diabetes. The aim of this record was to evaluate the accuracy of predictive equations for REE estimation in patients with type 2 diabetes, considering indirect calorimetry (IC) as the reference method.<h4>Methods</h4>A cross-sectional study was performed in outpatients with type 2 diabetes. Clinical, body composition by electrical bioimpedance ...[more]

PMID: 33005431

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Project description:Background and Aims:The unique demographic and dietary characteristics of modern Arabic population require development of a new predictive equation for the estimation of resting energy expenditure (REE). This study presented new equations characteristic to Saudi population. Methods:A set of predictive equations for REE was derived for 427 healthy male and female subjects (aged 18-57?±?14 years). REE was measured (REEm) by indirect calorimetry (IC) and predicted (REEp) 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 set of equations to predict REE of men and women was developed. Accuracy of the new main equations was further tested in an external sample of 48 subjects (men?=?50%). Results:Using a number of parameters (bias, underprediction, overprediction, and % 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 the Almajwal-Abulmeaty (AA) equation) was developed using this study's data, after a rigorous stepwise regression analysis using the following formula: REE?=?3832.955?+?AdjWt (kg)?×?48.037?-?Ht (cm)?×?30.642?+?gender?×?141.268?-?age (years)?×?4.525 [AdjWt is Adjusted body weight?=?(Wt?-?IBW)/4?+?IBW. IBW is Ideal body weight; for men IBW?=?(Ht(cm)?-?152.4)?×?1.0714)?+?45.36 and for women IBW?=?(Ht(cm)-152.4)?×?0.8928)?+?45.36]. The regression model accounted for approximately 70% of the variance in REEm (R 2?=?0.702). Conclusion:Previous equations likely over- or underpredicted REE. Therefore, the new predictive AA equations developed in this study are recommended for the estimation of REE in young to middle-aged Saudi men and women with different body mass indexes. Future research is also required for further clinical and cross-validation of these new equations.

Dataset Information

Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes: what can we use?

Publications

Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes: what can we use?

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