Karayiannis et al. (2022) conducted an interesting cohort study on the resting energy expenditure (REE) of critically intubated patients due to COVID-19. They investigated the relationship between REE and the administration of neuromuscular blockers (NMBAs). They report that REE measurements divided by body weight gradually increased after the third day in the ICU (from 17.8 kcal/kg vs. 29.3 kcal/kg in patients without obesity; and 18.1 kcal/kg vs. 30.1 kcal/kg in patients with obesity); and that the use of NMBAs was accompanied by a significant drop in the REE/body weight ratio, primarily during the first seven days of hospitalization, both in patients without obesity (22.9 kcal/kg vs. 17.9 kcal/kg) and in patients with obesity (22.5 kcal/kg vs. 19.5 kcal/kg) [1]. Despite this promising finding for clinical practice, the statistical technique of normalizing REE by dividing it by body weight can produce inconsistencies.
In several cases, researchers normalize measurements of energy expenditure (total or resting) by dividing them by the body weight of individuals to standardize possible variations due to body size. However, this practice has been debated for many years [2]. Mathematical and biological issues arise as a result of using this method to perform statistical analysis and interpretation of energy expenditure data: I) Mathematically, energy expenditure is not linearly related to body weight, and the regression line between these two variables does not pass through the intercept zero; II) biologically, such division does not account for individual differences in body composition.
The first issue generates statistical artifacts that can reveal differences between groups that do not exist and mask differences that do exist [2]. The second issue leads to the assumption that body fat and fat-free mass (FFM) portions contribute equally to REE. FFM has been shown to be more metabolically active than fat mass. However, normalization of energy expenditure by FFM, which is widely used and thought to be superior to division by body weight, also seems to result in unwanted errors. Because body fat is an endocrine tissue that secretes several adipokines, the potential influence of body fat on energy expenditure is excluded when using kcal/kg of FFM. As a result, using FFM to perform such normalization would be inadequate [3,4].
It is suggested that analyses that wish to incorporate body weight variation (or body composition) on energy expenditure results use the strategy proposed by Allison et al. (1995) [3] and Poehlman & Toth (1995) [4], performing an analysis of covariance (ANCOVA), adjusting the model by body weight, or preferably by fat mass and FFM as separate variables, bringing more reliable results that are less prone to error, due to the problems addressed on the use of the kcal/kg ratio.
Funding statement
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Author contributions
MLM and NBB conceived and participated in writing and revising the manuscript. All authors read and approved the final version of the manuscript.
Conflicts of interest
The authors have no conflicts of interest to report.
Handling Editor: M. Deutz
References
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