Literature DB >> 23267745

A new equation to estimate basal energy expenditure of patients with diabetes.

Kaori Ikeda1, Shimpei Fujimoto, Masashi Goto, Chizumi Yamada, Akihiro Hamasaki, Megumi Ida, Kazuaki Nagashima, Kenichiro Shide, Takashi Kawamura, Nobuya Inagaki.   

Abstract

BACKGROUND & AIMS: Predictive equations for basal energy expenditure (BEE) derived from Caucasians tend to overestimate BEE in non-Caucasians. The aim of this study was to develop a more suitable method to estimate BEE in Japanese patients with diabetes using indices readily measured in clinical practice.
METHODS: BEE was measured by indirect calorimetry under a strict basal condition in 68 Japanese patients with type 1 or type 2 diabetes. The best fitting equation was investigated by multiple regression analysis using of age, sex, and anthropometric indices. The resultant new equation was tested in a separate group of 60 Japanese patients with type 1 or type 2 diabetes, and the accuracy compared with existing equations.
RESULTS: The best-fit equation was BEE [kcal/day] = 10 × (body weight)[kg] - 3 × (age)[y] + 125 (if male) + 750. Adjusted coefficient of determination was 81.0%. Root mean squared errors and accurate prediction in the validation set were 103 kcal/day and 78% for the new equation; 184 and 50 for Harris-Benedict; 209 and 38 for Oxford; 205 and 42 for Liu; and 140 and 63 for Ganpule.
CONCLUSIONS: This new equation is simpler and estimates BEE more accurately in Japanese patients with diabetes than the presently used equations do.
Copyright © 2012 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Entities:  

Keywords:  Basal metabolic rate; Diabetes; Indirect calorimetry; Medical nutrition therapy; Prediction equation; Resting metabolic rate

Mesh:

Year:  2012        PMID: 23267745     DOI: 10.1016/j.clnu.2012.11.017

Source DB:  PubMed          Journal:  Clin Nutr        ISSN: 0261-5614            Impact factor:   7.324


  6 in total

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

Authors:  Thaiciane Grassi; Francesco Pinto Boeno; Mauren Minuzzo de Freitas; Tatiana Pedroso de Paula; Luciana Vercoza Viana; Alvaro Reischak de Oliveira; Thais Steemburgo
Journal:  BMC Nutr       Date:  2020-09-30

2.  Low resting energy expenditure in postmenopausal Japanese women with type 2 diabetes mellitus.

Authors:  Risa Ide; Makiko Ogata; Naoko Iwasaki; Tetsuya Babazono
Journal:  Diabetol Int       Date:  2019-02-28

Review 3.  Energy Expenditure in People with Diabetes Mellitus: A Review.

Authors:  Nathan Caron; Nicolas Peyrot; Teddy Caderby; Chantal Verkindt; Georges Dalleau
Journal:  Front Nutr       Date:  2016-12-22

4.  Resting Energy Expenditure in the Elderly: Systematic Review and Comparison of Equations in an Experimental Population.

Authors:  Honoria Ocagli; Corrado Lanera; Danila Azzolina; Gianluca Piras; Rozita Soltanmohammadi; Silvia Gallipoli; Claudia Elena Gafare; Monica Cavion; Daniele Roccon; Luca Vedovelli; Giulia Lorenzoni; Dario Gregori
Journal:  Nutrients       Date:  2021-01-29       Impact factor: 5.717

5.  Comparison of the Harris-Benedict Equation, Bioelectrical Impedance Analysis, and Indirect Calorimetry for Measurement of Basal Metabolic Rate among Adult Obese Filipino Patients with Prediabetes or Type 2 Diabetes Mellitus.

Authors:  Sybil Claudine Luy; Oliver Allan Dampil
Journal:  J ASEAN Fed Endocr Soc       Date:  2018-09-10

6.  Total energy expenditure measured using doubly labeled water compared with estimated energy requirements in older adults (≥65 y): analysis of primary data.

Authors:  Judi Porter; Kay Nguo; Jorja Collins; Nicole Kellow; Catherine E Huggins; Simone Gibson; Zoe Davidson; Dale Schoeller; Ross Prentice; Marian L Neuhouser; Linda Snetselaar; Helen Truby
Journal:  Am J Clin Nutr       Date:  2019-12-01       Impact factor: 7.045

  6 in total

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