Prediction Equations Overestimate the Energy Requirements More for Obesity-Susceptible Individuals

Rebecca T McLay-Cooke, Andrew R Gray, Lynnette M Jones, Rachael W Taylor, Paula M L Skidmore, Rachel C Brown, Rebecca T McLay-Cooke, Andrew R Gray, Lynnette M Jones, Rachael W Taylor, Paula M L Skidmore, Rachel C Brown

Abstract

Predictive equations to estimate resting metabolic rate (RMR) are often used in dietary counseling and by online apps to set energy intake goals for weight loss. It is critical to know whether such equations are appropriate for those susceptible to obesity. We measured RMR by indirect calorimetry after an overnight fast in 26 obesity susceptible (OSI) and 30 obesity resistant (ORI) individuals, identified using a simple 6-item screening tool. Predicted RMR was calculated using the FAO/WHO/UNU (Food and Agricultural Organisation/World Health Organisation/United Nations University), Oxford and Miflin-St Jeor equations. Absolute measured RMR did not differ significantly between OSI versus ORI (6339 vs. 5893 kJ·d-1, p = 0.313). All three prediction equations over-estimated RMR for both OSI and ORI when measured RMR was ≤5000 kJ·d-1. For measured RMR ≤7000 kJ·d-1 there was statistically significant evidence that the equations overestimate RMR to a greater extent for those classified as obesity susceptible with biases ranging between around 10% to nearly 30% depending on the equation. The use of prediction equations may overestimate RMR and energy requirements particularly in those who self-identify as being susceptible to obesity, which has implications for effective weight management.

Keywords: RMR prediction equations; indirect calorimetry; obesity resistance; obesity susceptibility; resting metabolic rate.

Conflict of interest statement

The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

Figures

Figure 1
Figure 1
Scatter plot of predicted against measured RMR for each equation for obesity resistant individuals (ORI) and obesity susceptible individuals (OSI). Each individual is represented by three points and the line shows equality between the prediction equation and measured RMR values.
Figure 2
Figure 2
Biases for obesity resistant individuals (ORI) and obesity susceptible individuals (OSI) by resting metabolic rate (RMR) prediction equation for selected measured RMR values (n = 56).
Figure 3
Figure 3
Biases for obesity resistant individuals (ORI) and obesity susceptible individuals (OSI) by resting metabolic rate (RMR) prediction equation for selected measured RMR values after adjustment for sex, age, height and weight (n = 56).

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