The DOI matches its Crossref record; 18 of the 19 references it cites were found in a registry or an index.
The Harris Benedict equation reevaluated: resting energy requirements and the body cell mass
Abstract
The Harris Benedict equations (HBE) were derived from indirect calorimetric data obtained in 239 normal subjects. Using these data and additional data published by Benedict, which were obtained from subjects spanning a wider age range (n = 98), the present study evaluated the relationship between measured resting energy expenditure and age, sex, and predicted body cell mass (BCM). When the additional subjects from the subsequently published series are included, the regression equations, standard error of the estimate, and 95% confidence limits are similar to the original equations. The HBE estimate resting energy expenditure of a normal subject with a precision of 14%. Resting energy expenditure is directly related to the size of the BCM and is independent of age and sex. The variables of height, weight, age, and sex in the HBE reflect the relationship between body weight and the BCM. Indirect calorimetry and body composition measurements were performed in both normally nourished and malnourished patients (n = 74) to assess the accuracy of the HBE in malnourished patients. Malnutrition is associated with an increase in resting oxygen consumption (VO2) which becomes apparent only when VO2 is expressed as a function of the BCM. There is no difference in resting VO2 between the sexes when expressed as a function of BCM. A regression equation was derived from the Harris Benedict data to predict resting VO2 from age, height, weight, and sex. Predicted VO2 was not significantly different from measured VO2 for the normally nourished patients (n = 33) whereas in the malnourished (n = 41) predicted VO2 underestimated the measured value. The HBE accurately predict resting energy expenditure in normally nourished individuals with a precision of +/- 14%, but are unreliable in the malnourished patient.
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“Interestingly, resting metabolic rate varies between groups of different age, sex, and body composition [132]”
From Drivers of diversity in human thermal perception – A review for holistic comfort models (2018) · cites this paper as [132]
Citations
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Thomas, D. T., Erdman, K. A., & Burke, L. M. (2016) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2015.12.006 · Cited by 1,359
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“5.”
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“After adjusting for maintenance calories (MC) for each individual (Roza and Shizgal, 1984), the average cumulative percentage of”
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“The total energy content of all the drinks provided 75% of the daily energy requirements based on the Harris–Benedict equation (Roza & Shizgal, 1984), using a physical activity level of 1.5 (providing 1.1 g of protein per kg body mass).”
MethodInfluentialRelationship of genetics, age, and physical fitness to daily energy expenditure and fuel utilization
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Metadata
- Authors
- Roza, A. M., & Shizgal, H. M.
- Corresponding author
- Shizgal, H M
- Venue
- The American Journal of Clinical Nutrition
- Publisher
- Elsevier BV
- Published
- 1984-07
- Volume
- 40
- Issue
- 1
- Pages
- 168-182
- ISSN
- 0002-9165 (ISSN-L)
- OpenAlex
- W2125884465
- Semantic Scholar
- 379f53c98ea8429493ffe111f85b57dd87adcaeb
- Cited by
- 824
- References
- 19
- Citations by year
- 2026: 31 · 2025: 45 · 2024: 40 · 2023: 45 · 2022: 42 · 2021: 45 · 2020: 58 · 2019: 48 · 2018: 41 · 2017: 52 · 2016: 35 · 2015: 48 · 2014: 25 · 2013: 24 · 2012: 16
- FWCI
- 9.64
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Clinical Nutrition (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Nursing › Nutrition and Dietetics › Clinical Nutrition and Gastroenterology
- Health Sciences › Medicine › Physiology (medical) › Body Composition Measurement Techniques
- Health Sciences › Medicine › Physiology (medical) › Nutrition and Health in Aging
- Keywords
- Harris-Benedict equation, resting energy expenditure, body cell mass, indirect calorimetry, resting oxygen consumption, malnutrition, body composition, load forecasting, regression equations, sex differences
- MeSH terms
- Adult, Age Factors, Aged, Body Composition, Body Weight, Calorimetry, Indirect, Deficiency Diseases, Energy Metabolism, Female, Humans, Male, Middle Aged, Oxygen Consumption, Regression Analysis, Sex Factors
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