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.

Energy expenditure due to gluconeogenesis in pathological conditions of insulin resistance

“…Few studies have directly measured the EE attributable to GNG in humans (4), although the energy cost of GNG has been estimated based on knowledge of rates of GNG, moles of oxygen consumption by GNG, and average oxygen consumption (1). Furthermore, equations used to predict EE may over or underestimate EE in patients with diabetes (5,6). Therefore, we estimated the EE attributable to GNG in three pathological conditions of insulin resistance in humans [insulin receptor pathogenic variants (INSR), lipodystrophy, and type 2 diabetes (T2DM)] and obesity without diabetes and compared this with predicted GNG EE using previously published rates of GNG in healthy individuals and the Mifflin St. Jeor equation (7).…”