Comparison of Resting Energy Expenditure Prediction Equations and Indirect Calorimetry Among Adults with Severe Obesity
Clinicians may benefit from tailoring their choice of REE prediction equation to the specific characteristics of each patient, favoring equations with lower bias and greater precision within relevant subgroups. However, because of the low precision of REE prediction equations and the systematic bias revealed at REE extremes, it is highly recommended to measure REE whenever possible.
Authors
- James D. LeCheminant (ORCID: https://orcid.org/0000-0002-2368-0374)
- Ted D. Adams (ORCID: https://orcid.org/0000-0002-9853-446X)
- Jacob G. Mabey (ORCID: https://orcid.org/0000-0003-1361-5795)
- Lance E. Davidson (ORCID: https://orcid.org/0000-0002-1383-0666)
- Joacim Larsen (ORCID: https://orcid.org/0000-0003-0622-7794)
- Steven C. Hunt
- P. Lawson
- Seth W. Rather
- Dalton L Braathen
Institutions
- Brigham Young University (US)
- University of Utah (US)
Publication Details
- Journal
- Current Developments in Nutrition
- Published
- 2025-08-26
- DOI
- https://doi.org/10.1016/j.cdnut.2025.107538
- Primary Topic
- Diet and metabolism studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- National Institute of Diabetes and Digestive and Kidney Diseases
- National Center for Advancing Translational Sciences