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Comparative Study
. 2017 May-Jun;61(3):257-262.
doi: 10.1590/2359-3997000000228. Epub 2016 Nov 24.

Applicability of predictive equations for resting energy expenditure in obese patients with obstructive sleep apnea

Mariana Pantaleão Del Re  1 , Camila Maria de Melo  1 , Marcus Vinicius Dos Santos  2 , Sergio Tufik  1 , Marco Túlio de Mello  3
Affiliations
Comparative Study

Applicability of predictive equations for resting energy expenditure in obese patients with obstructive sleep apnea

Mariana Pantaleão Del Re et al. Arch Endocrinol Metab. 2017 May-Jun.

Abstract

Objective: To investigate the applicability of predictive equations for resting energy expenditure (REE) in obese individuals with obstructive sleep apnea (OSA) and the effects of OSA severity on REE.

Materials and methods: Twenty-nine obese men, 41.5 ± 7 years old, with moderate and severe OSA were recruited. All subjects were submitted to a clinical polysomnography, body composition, and indirect calorimetry measurements. REE was also predicted by three different equations: Harris and Benedict (1919), Cunningham (1990), and DRI (2002).

Results: No effects of OSA severity on REE were found. The measured REE (2416.0 ± 447.1 kcal/day) and the REE predicted by equations were different from each other (F = 2713.88; p < 0.05): Harris and Benedict (2128.0 ± 245.8 kcal/day), Cunningham (1789.1 ± 167.8 kcal/day) and DRI (2011.1 ± 181.4 kcal/day). Pearson correlations showed a moderate positive correlation between the REE measured and predicted by all equations.

Conclusion: Our findings suggest that predictive equations for REE underestimate the energy expenditure in obese patients with sleep apnea. Also, no effects of OSA severity on REE were found.

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Conflict of interest statement

Disclosure: no potential conflict of interest relevant to this article was reported.

Figures

Figure 1
Figure 1. Resting energy expenditure measured by indirect calorimetry and estimated by different equations. São Paulo, 2015.
IC: indirect calorimetry; HB: Harris & Benedict equation; DRI: DRI’s equation. Measured repeated ANOVA, F = 49.992 p ≤ 0,05. Values presented in Mean ± Standard Deviation; * p < 0.05.
Figure 2
Figure 2. Pearson correlation between measured resting energy expenditure and prediction equations. São Paulo, 2015.
Figure 3
Figure 3. Bland-Altman plots of resting energy expenditure measured by indirect calorimetry and predicted by different equations. São Paulo, 2015.
HB: Harris & Benedict equation; DRI: DRI’s equation.
See this image and copyright information in PMC

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