Journal of Food and Nutrition Research
ISSN (Print): 2333-1119 ISSN (Online): 2333-1240 Website: http://www.sciepub.com/journal/jfnr Editor-in-chief: Prabhat Kumar Mandal
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Journal of Food and Nutrition Research. 2019, 7(1), 19-32
DOI: 10.12691/jfnr-7-1-4
Open AccessArticle

How Well Are We Predicting the Resting Energy Expenditure in Underweight to Obese Brazilian Adults?

Natália Tomborelli Bellafronte1, , Daiane Leite da Roza2 and Paula Garcia Chiarello1

1Department of Internal Medicine, Medicine School, University of São Paulo, Ribeirão Preto, São Paulo, 14049-190, Brazil

2Department of Social Medicine, Medicine School, University of São Paulo, Ribeirão Preto, São Paulo, 14049-190, Brazil

Pub. Date: January 16, 2019

Cite this paper:
Natália Tomborelli Bellafronte, Daiane Leite da Roza and Paula Garcia Chiarello. How Well Are We Predicting the Resting Energy Expenditure in Underweight to Obese Brazilian Adults?. Journal of Food and Nutrition Research. 2019; 7(1):19-32. doi: 10.12691/jfnr-7-1-4

Abstract

Resting energy expenditure (REE) measurement is costly and rarely feasibly. Alternatively, is easily predicted by predictive equations but accuracy varies across ethnicity, body size and body composition. The purpose was to evaluate the validity of REE predictive equations between adult from Brazil and across body mass index (BMI). We also developed a new equation. It was a cross-sectional observational study in which predicted REE was tested for agreement with indirect calorimetry. Brazilian men and women (n=367) age from 20 to 40 years were analyzed from October 2016 to October 2017. Participants were from underweight to obese (BMI from 17 to 40kg/m2). REE was measured (mREE) with indirect calorimetry and predicted (pREE) by REE predictive equations. Each equation was compared for accuracy (pREE= ±10%mREE). Bias between mREE and pREE with 95% confidence intervals, Bland-Altman and scatter plots graphs were also analyzed. The root mean squared error measured the performance of the equations. Stepwise multiple-regression analyses were applied for developing a new equation. As a result, the new equation (r2= 0.46; SEE= 226.92kcal/day) presented a good performance among normal, overweight and obese subjects (51, 51 and 45% of accuracy, respectively). The best performance of REE equations evaluated were from Anjos (39% of accuracy) among underweight subjects; Anjos and Sabounchi among normal weight (38% of accuracy for both) and overweight (53 and 48% of accuracy, respectively) individuals; Anjos and Owens (48 and 44% of accuracy, respectively) among obese subjects. No equation was able to accurately predict REE in 60% of the time and all tended to overestimate. In conclusion, Anjos, Sabounchi and Owens equations showed the best performances. Therefore, all predictive equation presented large individual errors. The new equation had a good performance from normal to obese individuals. However, indirect calorimetry is still necessary for the most accurate information about energy needs.

Keywords:
resting energy expenditure indirect calorimetry predictive equations weight management body mass index

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