Best-fitting prediction equations for basal metabolic rate: informing obesity interventions in diverse populations
Open accessAbstract
Basal metabolic rate (BMR) represents the largest component of total energy expenditure and is a major contributor to energy balance. Therefore, accurately estimating BMR is critical for developing rigorous obesity prevention and control strategies. Over the past several decades, numerous BMR formulas have been developed targeted to different population groups. A comprehensive literature search revealed 248 BMR estimation equations developed using diverse ranges of age, gender, race, fat-free mass, fat mass, height, waist-to-hip ratio, body mass index and weight. A subset of 47 studies included enough detail to allow for development of meta-regression equations. Utilizing these studies, meta-equations were developed targeted to 20 specific population groups. This review provides a comprehensive summary of available BMR equations and an estimate of their accuracy. An accompanying online BMR prediction tool (available at http://www.sdl.ise.vt.edu/tutorials.html) was developed to automatically estimate BMR based on the most appropriate equation after user-entry of individual age, race, gender and weight.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Basal metabolic rate, the primary source of total energy expenditure, is primarily influenced by lean mass, so calorie restriction becomes increasingly difficult to sustain as lean mass diminishes.
“Since the basal metabolic rate, the primary source of total energy expenditure, is primarily influenced by lean mass, CR becomes increasingly difficult to sustain as lean mass diminishes (29)”
From The Benefits of Exercise Training in Combination With Weight Loss Therapies (2025) · cites this paper as [29]
The Introduction identifies BMR as the largest contributor to energy expenditure, and Results (‘Impact of Body Composition’) identifies fat-free mass as the best independent predictor of BMR. The paper does not establish that declining lean mass makes calorie restriction increasingly difficult to sustain; Methods (‘Overview’) says its analysis focuses on cross-sectional data rather than changes within individuals over time. Page numbers were unavailable in our copy. (LLM, conf=0.88)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 81 · Cited by 135
- Authors
- Sabounchi, N. S., Rahmandad, H., & Ammerman, A.
- Affiliations
- Washington University in St. Louis (US)
- Virginia Tech (US)
- University of North Carolina at Chapel Hill (US)
- Corresponding author
- Rahmandad, H
- Venue
- International Journal of Obesity
- Published
- 2013-01-15
- Volume
- 37
- Issue
- 10
- Pages
- 1364-1370
- ISSN
- 0307-0565 (ISSN-L)
- 1476-5497
- PMC
- PMC4278349
- OpenAlex
- W2012621341
- Cited by
- 135
- References
- 81
- Citations by year
- 2026: 12 · 2025: 6 · 2024: 15 · 2023: 14 · 2022: 11 · 2021: 13 · 2020: 11 · 2019: 13 · 2018: 13 · 2017: 8 · 2016: 6 · 2015: 6 · 2014: 2 · 2013: 5
- FWCI
- 0.68
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- International Journal of Obesity (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute (R21HL113680)
- Office of Behavioral and Social Sciences Research
- Topics
- Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Regulation of Appetite and Obesity
- Keywords
- basal metabolic rate, energy expenditure, obesity prevention, energy balance, equation accuracy, fat-free mass, body mass index
- MeSH terms
- Age Factors, Basal Metabolism, Body Composition, Body Weight, Calorimetry, Indirect, Female, Humans, Male, Obesity, Predictive Value of Tests, Regression Analysis, Sex Factors, United States, Reproducibility of Results, Body Mass Index, Waist-Hip Ratio
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
