Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Metabolism and Metabolomics

Predicting resting energy expenditure: a critical appraisal

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 (nā€‰=ā€‰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.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

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.

Similar content being viewed by others

Data availability

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

References

  1. Henry CJ. Basal metabolic rate studies in humans: measurement and development of new equations. Publ Health Nutr. 2005;8:1133ā€“52.

    ArticleĀ  CASĀ  Google ScholarĀ 

  2. FAO/WHO/UNU. Human energy requirements. FAO Food and Nutrition Technical Report Series no. 1. Rome: Joint FAO/WHO/ UNU Expert Consultation. 2004.

  3. Goldberg GR, Black AE, Jebb SA, Cole TJ, Murgatroyd PR, Coward WA, et al. Critical evaluation of energy intake data using fundamental principles of energy physiology: 1. Derivation of cut-off limits to identify underrecording. Eur J Clin Nutr. 1991;45:569ā€“81.

    CASĀ  PubMedĀ  Google ScholarĀ 

  4. Westerterp KR, Donkers JH, Fredrix EW, Boekhoudt P. Energy intake, physical activity and body weight: a simulation model. Br J Nutr. 1995;73:337ā€“47.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  5. Alcantara JM, Galgani JE, Jurado-Fasoli-L, Dote-Montero M, Merchan-Raminez E, Ravussin E, et al. Validity of four commercially available metabolic carts for asse4ssing resting metabolic rate and respiratory exchange ratio in non-ventialted humans. Clin Nutr. 2022;41:746ā€“54.

    ArticleĀ  CASĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  6. Schulz S, Westerterp KR, Bruck K. Comparison of energy expenditure by the double labeled water technique with energy intake, heart rate and activity recording in man. Am J Clin Nutr. 1989;49:1146ā€“54.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  7. Westerterp KR, Kayser B, Brouns F, Herry JP, Saris WHM. Energy expenditure climbing Mt. Everest. J Appl Physiol. 1992;73:1815ā€“9.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  8. Westerterp KR, Saris WHM, Bloemberg BPM, Kempen K, Caspersen CJ, Kromhout D. Validation of the Zutphen physical activity questionaire for the elderly with doubly labeled water. Med Sci Sports Exerc. 1992;24:S68.

    ArticleĀ  Google ScholarĀ 

  9. Pannemans DLE, Westerterp KR. Energy expenditure, physical activity and basal metabolic rate of elderly subjects. Br J Nutr. 1995;73:571ā€“81.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  10. Velthuis-te Wierik EJM, Westerterp KR, Van den Berg H. Impact of a moderately energy-restricted diet on energy metabolism and body composition in non-obese men. Int J Obes. 1995;19:318ā€“24.

    CASĀ  Google ScholarĀ 

  11. Heijligenberg R, Romijn JA, Westerterp KR, Jonkers CF, Prins JM, Sauerwijn HP. Total energy expenditure in human immunodeficiency virus-infected men and healthy controls. Metabolism 1997;46:1324ā€“6.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  12. Schuit AJ, Schouten EG, Westerterp KR, Saris WHM. Validity of the physical activity scale (PASE) for the elderly according to energy expenditure assessed by the doubly labeled water method. J Clin Epidemiol. 1997;50:541ā€“6.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  13. Fogelholm M, Hiilloskorpi H, Laukkanen R, Oja P, Van Marken Lichtenbelt W, Westerterp K. Assessment of energy expenditure in overweight women. Med Sci Sports Exerc. 1998;30:1191ā€“7.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  14. Goris AHC, Meijer EP, Westerterp KR. Repeated measurement of habitual food intake increases under-reporting and induces selective under-reporting. Br J Nutr. 2001;85:629ā€“34.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  15. Verbunt JA, Westerterp KR, Van der Heijden GJ, Seelen HA, Vlaeyen JW, Knottnerus JA. Physical activity in daily life in patients with chronic low back pain. Arch Phys Med Rehab. 2001;82:726ā€“30.

    ArticleĀ  CASĀ  Google ScholarĀ 

  16. Joosen AM, Bakker AH, Westerterp KR. Metabolic efficiency and energy expenditure during short-term overfeeding. Physiol Beh. 2005;85:593ā€“7.

    ArticleĀ  CASĀ  Google ScholarĀ 

  17. PietilƤinen KH, Kaprio J, Borg P, Plasqui G, Yki-JƤrvinen H, Kujala UM, et al. Physical inactivity and obesity: a vicious circle. Obesity 2008;16:409ā€“14.

    ArticleĀ  PubMedĀ  Google ScholarĀ 

  18. Tanskanen M, Uusitalo AL, HƤkkinen K, NissilƤ J, Santtila M, Westerterp KR, et al. Aerobic fitness, energy balance and body mass index are associated with training load assessed by activity energy expenditure. Scan J Med Sci Sports. 2009;19:871ā€“8.

    ArticleĀ  CASĀ  Google ScholarĀ 

  19. Camps SG, Verhoef SP, Westerterp KR. Weight loss-induced reduction in physical activity recovers during weight maintenance. Am J Clin Nutr. 2013;98:917ā€“23.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  20. Harris JA, Benedict FG. A biometric study of basal metabolism in man. Publication no. 297. Washington DC: Carnegie Institute of Washington. 1919.

  21. Schofield WN. Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr. 1985;39:5ā€“41.

    PubMedĀ  Google ScholarĀ 

  22. Owen OE, Kavle E, Owen RS, Polansky M, Caprio S, Mozzoli MA, et al. A reappraisal of the caloric requirements in healthy women. Am J Clin Nutr. 1986;44:1ā€“19.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  23. Owen OE, Holup JL, D'Alessio DA, Craig ES, Polansky M, Smalley KJ, et al. A reappraisal of the caloric requirements of men. Am J Clin Nutr. 1987;46:875ā€“85.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  24. Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr. 1990;51:241ā€“7.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  25. Cunningham JJ. Body composition as a determinant of energy expenditure: a synthetic review and a proposed general prediction equation. Am J Clin Nutr. 1991;54:963ā€“9.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  26. Black AE, Coward WA, Cole JJ, Prentice AM. Human energy expenditure in affluent societies: an analysis of 574 doubly-labelled water measurements. Eur J Clin Nutr. 1996;50:72ā€“92.

    CASĀ  PubMedĀ  Google ScholarĀ 

  27. Case KO, Brahler CJ, Heiss C. Resting energy expenditures in Asian women measured by indirect calorimetry are lower than expenditure calculated from prediction equations. J Am Diet Assoc. 1997;97:1288ā€“92.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  28. Frings-Meuthen P, Henkel S, Boschmann M, Chilibeck PD, Alvero Cruz JR, Hoffmann F, et al. Resting energy expenditure of master athletes: accuracy of predictive equations and primary determinants. Front Physiol. 2021;12:641455.

    ArticleĀ  PubMedĀ  PubMed CentralĀ  Google ScholarĀ 

  29. Bowes HM, Burdon CA, Taylor NAS. The scaling of human basal and resting metabolic rates. Eur J Appl Physiol. 2021;121:193ā€“208.

    ArticleĀ  PubMedĀ  Google ScholarĀ 

  30. Frankenfield D, Roth-Yousey L, Compher C. Comparison of predictive erquations for resting metabolic rate in healthy nonobese and obese adults: a systematic review. J Am Diet Assoc. 2005;105:775ā€“89.

    ArticleĀ  PubMedĀ  Google ScholarĀ 

  31. Weijs PJM. Validity of predictive equations for resting energy expenditure in US and Dutch overweight and obese class I and II adults aged 18-65 y. Am J Clin Nutr. 2008;88:959ā€“70.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  32. Leung R, Woo J, Chan D, Tang N. Validation of prediction equations for basal metabolic rate in Chinese subjects. Eur J Clin Nutr. 2000;54:551ā€“4.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  33. Soares MJ, Piers LS, O'Dea K, Shetty PS. No evidence for an ethnic influence on basal metabolism: an examination of data from India and Australia. Br J Nutr. 1998;79:333ā€“41.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  34. Nelson KM, Weinsier RL, Long CL, Schutz Y. Prediction of resting energy expenditure from fat-free mass and fat mass. Am J Clin Nutr. 1992;56:848ā€“56.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  35. Bosy-Westphal A, MĆ¼ller MJ, Boschmann M, Klaus S, Kreymann G, LĆ¼hrmann PM, et al. Grade of adiposity affects the impact of fat mass on resting energy expenditure. Br J Nutr. 2009;101:474ā€“7.

    ArticleĀ  CASĀ  PubMedĀ  Google ScholarĀ 

  36. Westerterp KR, Meijer GAL, Schoffelen P, Janssen EME. Body mass, body composition and sleeping metabolic rate before, during and after endurance training. Eur J Appl Physiol. 1994;69:203ā€“8.

    ArticleĀ  CASĀ  Google ScholarĀ 

  37. Felig P, Cunningham J, Levitt M, Hendler R, Nadel E. Energy expenditure in obesity in fasting and postprandial state. Am J Physiol. 1983;244:E45ā€“51.

    CASĀ  PubMedĀ  Google ScholarĀ 

  38. Westerterp KR. Diet induced thermogenesis. Nutr Metab. 2004;1:5.

    ArticleĀ  Google ScholarĀ 

  39. Miles-Chan JL, Dulloo AG, Schutz Y. Fasting substrate oxidation at rest assessed by indirect calorimetry: is prior dietary macronutrient level and composition a confounder? Int J Obes. 2015;39:1114ā€“7.

    ArticleĀ  CASĀ  Google ScholarĀ 

  40. Verboeket-van de Venne WPHG, Westerterp KR. Influence of the feeding frequency on nutrient utilization in man: consequences for energy metabolism. Eur J Clin Nutr. 1991;45:161ā€“9.

    CASĀ  PubMedĀ  Google ScholarĀ 

  41. Westerterp KR. Adaptive thermogenesis during energy deficits: a different explanation. Eur J Clin Nutr. 2022;76:1351ā€“2.

    ArticleĀ  PubMedĀ  Google ScholarĀ 

  42. Dahle JH, Ostendorf DM, Pan Z, MacLean PS, Bessesen DH, Heymsfield SB, et al. Weight and body composition changes affect resting energy expenditure predictive equations during a 12-month weight-loss intervention. Obesity. 2021;29:1596ā€“605.

    ArticleĀ  PubMedĀ  Google ScholarĀ 

Download references

Author information

Authors and Affiliations

Authors

Contributions

All contributions were from the single author.

Corresponding author

Correspondence to Klaas R. Westerterp.

Ethics declarations

Competing interests

The author is member of the editorial board of the journal.

Additional information

Publisherā€™s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41430-023-01299-3

Search

Quick links