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Metabolism and Metabolomics

Predicting resting energy expenditure: a critical appraisal

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Abstract

Background

The most commonly used prediction models for resting energy expenditure (REE) are Harris-Benedict (1919), Schofield (1985), Owen (1986), and Mifflin-St Jeor (1990), based on height, weight, age and gender, and Cunningham (1991), based on body composition.

Methods

Here, the five models are compared with reference data, consisting of individual REE measurements (n = 353) from 14 studies, covering a large range of participant characteristics.

Results

For white adults, prediction of REE with the Harris-Benedict model approached measured REE most closely, with estimates within 10% for more than 70% of the reference population.

Discussion

Sources of differences between measured and predicted REE include measurement validity and measurement conditions. Importantly, a 12- to 14-h overnight fast may not be sufficient to reach post-absorptive conditions and may explain differences between predicted REE and measured REE. In both cases complete fasting REE may not have been achieved, especially in participants with high energy intake.

Conclusion

In white adults, measured resting energy expenditure was closest to predicted values with the classic Harris-Benedict model. Suggestions for improving resting energy expenditure measurements, as well as prediction models, include the definition of post-absorptive conditions, representing complete fasting conditions with respiratory exchange ratio as indicator.

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Fig. 1: Bland-Altman plots of the % difference between predicted and measured resting energy expenditure for 353 participants.
Fig. 2: Frequency distribution of the % difference between predicted and measured resting energy expenditure for 353 participants.

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Data availability

The data generated or analysed during this study can be found within the published article.

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Authors and Affiliations

  1. NUTRIM, Maastricht University Medical Centre, Maastricht, The Netherlands

    Klaas R. Westerterp

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Westerterp, K.R. Predicting resting energy expenditure: a critical appraisal. Eur J Clin Nutr 77, 953–958 (2023). https://doi.org/10.1038/s41430-023-01299-3

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