Revised Harris-Benedict Equation: New Human Resting Metabolic Rate Equation
Overview
Affiliations
This paper contains a revision of the Harris-Benedict equations through the development and validation of new equations for the estimation of resting metabolic rate (RMR) in normal, overweight, and obese adult subjects, taking into account the same anthropometric parameters. A total of 722 adult Caucasian subjects were enrolled in this analysis. After taking a detailed medical history, the study enrolled non-hospitalized subjects with medically and nutritionally controlled diseases such as diabetes mellitus, cardiovascular disease, and thyroid disease, excluding subjects with active infections and pregnant or lactating women. Measurement of somatometric characteristics and indirect calorimetry were performed. The values obtained from RMR measurement were compared with the values of the new equations and the Harris-Benedict, Mifflin-St Jeor, FAO/WHO/UNU, and Owen equations. New predictive RMR equations were developed using age, body weight, height, and sex parameters. RMR males: (9.65 × weight in kg) + (573 × height in m) - (5.08 × age in years) + 260; RMR females: (7.38 × weight in kg) + (607 × height in m) - (2.31 × age in years) + 43; RMR males: (4.38 × weight in pounds) + (14.55 × height in inches) - (5.08 × age in years) + 260; RMR females: (3.35 × weight in pounds) + (15.42 × height in inches) - (2.31 × age in years) + 43. The accuracy of the new equations was tested in the test group in both groups, in accordance with the resting metabolic rate measurements. The new equations showed more accurate results than the other equations, with the equation for men (R-squared: 0.95) showing better prediction than the equation for women (R-squared: 0.86). The new equations showed good accuracy at both group and individual levels, and better reliability compared to other equations using the same anthropometric variables as predictors of RMR. The new equations were created under modern obesogenic conditions, and do not exclude individuals with regulated (dietary or pharmacological) Westernized diseases (e.g., cardiovascular disease, diabetes, and thyroid disease).
Zhang J Int J Chron Obstruct Pulmon Dis. 2025; 20:487-496.
PMID: 40046826 PMC: 11881604. DOI: 10.2147/COPD.S494323.
The Human Energy Balance: Uncovering the Hidden Variables of Obesity.
Theodorakis N, Nikolaou M Diseases. 2025; 13(2).
PMID: 39997062 PMC: 11854607. DOI: 10.3390/diseases13020055.
Deep learning reveals diverging effects of altitude on aging.
Teklu A, Heckenbach I, Petr M, Bakula D, Keijzers G, Scheibye-Knudsen M Geroscience. 2025; .
PMID: 39815037 DOI: 10.1007/s11357-024-01502-8.
Hans Chinese consume less O for muscular work than european-american.
Guo M, Montero D Mil Med Res. 2024; 11(1):73.
PMID: 39574181 PMC: 11580354. DOI: 10.1186/s40779-024-00578-9.
Lim J, Williams A, Burgess J, OConnell J, James M, Cross A Clin Obes. 2024; 15(1):e12703.
PMID: 39287006 PMC: 11706736. DOI: 10.1111/cob.12703.