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

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RESEARCH ARTICLE

Open Access

Predictive equations for evaluation for resting energy expenditure in Brazilian patients with type 2 diabetes: what can we use? Thaiciane Grassi1, Francesco Pinto Boeno2, Mauren Minuzzo de Freitas2, Tatiana Pedroso de Paula3, Luciana Vercoza Viana3, Alvaro Reischak de Oliveira2 and Thais Steemburgo1*

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. Keywords: Indirect calorimetry, Type 2 diabetes, Resting energy expenditure, Energy metabolism

* Correspondence: [email protected] 1 Postgraduate Program in Food, Nutrition, and Health, Universidade Federal do Rio Grande do Sul (UFRGS), Ramiro Barcelos Street 2400, 2nd Floor, Porto Alegre, RS 90035-003, Brazil Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creat