Underestimation of resting metabolic rate using equations compared to indirect calorimetry in normal-weight subjects: Consideration of resting metabolic rate as a function of body composition
Summary: Background & aims: Resting metabolic rate (RMR) can either be estimated using specific equations or measured with indirect calorimetry (iCal). The calculation formulas usually exclude body composition. In addition to age, height, weight, sex and disease, fat-free mass (FFM) and fat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-02-01
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| Series: | Clinical Nutrition Open Science |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667268521000048 |
| _version_ | 1818944729862111232 |
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| author | Hannes Nösslinger Ewald Mair Hermann Toplak Marlies Hörmann-Wallner |
| author_facet | Hannes Nösslinger Ewald Mair Hermann Toplak Marlies Hörmann-Wallner |
| author_sort | Hannes Nösslinger |
| collection | DOAJ |
| description | Summary: Background & aims: Resting metabolic rate (RMR) can either be estimated using specific equations or measured with indirect calorimetry (iCal). The calculation formulas usually exclude body composition. In addition to age, height, weight, sex and disease, fat-free mass (FFM) and fat mass (FM), in particular, influence energy expenditure. The aim of the present study was to compare the difference between calculated RMR using various predictive formulas reported in the literature and the values from measured iCal. Additionally, differing muscle mass and FM were considered in the calculations. Our hypothesis was that the accuracy of the calculation formulas depends on body constitution. Methods: This monocentric exploratory pilot study with an observational cross-sectional design included 69 healthy normal-weight adults. Participants were assigned to groups depending on constitution (slender, athletic, full slender). RMR was estimated with a set of 12 clinically relevant predictive equations. Results: The comparison of the calculated and measured values showed that the prevalent equations under-rather than overestimated the RMR. The equation from the World Health Organization (WHO) had the most accurate prediction range, from 90% to 110% of the RMR measured by iCal, followed by the Harris–Benedict formula and its modifications according to Roza–Shizgal and Mifflin. The agreement between predicting formulas and measured RMR improved in the group with higher fat mass. Conclusions: Body composition has a significant influence on RMR, mainly through muscle mass. The equations used correlated well with iCal in only 40%–60% of the studied population. Measurements and calculations varied considerably for subjects with greater muscle mass, whereas they were more consistent for subjects with greater FM. Increased emphasis should be placed on the measurement of RMR using iCal. |
| first_indexed | 2024-12-20T07:47:51Z |
| format | Article |
| id | doaj.art-6f9d2e223336458abe993e91de2a6b99 |
| institution | Directory Open Access Journal |
| issn | 2667-2685 |
| language | English |
| last_indexed | 2024-12-20T07:47:51Z |
| publishDate | 2021-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Clinical Nutrition Open Science |
| spelling | doaj.art-6f9d2e223336458abe993e91de2a6b992022-12-21T19:47:56ZengElsevierClinical Nutrition Open Science2667-26852021-02-01354866Underestimation of resting metabolic rate using equations compared to indirect calorimetry in normal-weight subjects: Consideration of resting metabolic rate as a function of body compositionHannes Nösslinger0Ewald Mair1Hermann Toplak2Marlies Hörmann-Wallner3Dienst für Diät und Ernährung, Hospital Franz Tappeiner, Meran, Italy; Corresponding author. Franz von Defregger Street No. 7, 39011, Lana, Italy.Resident Pediatrician, Bruneck, ItalyDepartment of Medicine, Division of Endocrinology and Diabetology, Medical University of Graz, AustriaInstitute of Dietetics and Nutrition, University of Applied Sciences JOANNEUM, Graz, AustriaSummary: Background & aims: Resting metabolic rate (RMR) can either be estimated using specific equations or measured with indirect calorimetry (iCal). The calculation formulas usually exclude body composition. In addition to age, height, weight, sex and disease, fat-free mass (FFM) and fat mass (FM), in particular, influence energy expenditure. The aim of the present study was to compare the difference between calculated RMR using various predictive formulas reported in the literature and the values from measured iCal. Additionally, differing muscle mass and FM were considered in the calculations. Our hypothesis was that the accuracy of the calculation formulas depends on body constitution. Methods: This monocentric exploratory pilot study with an observational cross-sectional design included 69 healthy normal-weight adults. Participants were assigned to groups depending on constitution (slender, athletic, full slender). RMR was estimated with a set of 12 clinically relevant predictive equations. Results: The comparison of the calculated and measured values showed that the prevalent equations under-rather than overestimated the RMR. The equation from the World Health Organization (WHO) had the most accurate prediction range, from 90% to 110% of the RMR measured by iCal, followed by the Harris–Benedict formula and its modifications according to Roza–Shizgal and Mifflin. The agreement between predicting formulas and measured RMR improved in the group with higher fat mass. Conclusions: Body composition has a significant influence on RMR, mainly through muscle mass. The equations used correlated well with iCal in only 40%–60% of the studied population. Measurements and calculations varied considerably for subjects with greater muscle mass, whereas they were more consistent for subjects with greater FM. Increased emphasis should be placed on the measurement of RMR using iCal.http://www.sciencedirect.com/science/article/pii/S2667268521000048Basal metabolismEnergy metabolismBody compositionCalorimetryIndirectAdult |
| spellingShingle | Hannes Nösslinger Ewald Mair Hermann Toplak Marlies Hörmann-Wallner Underestimation of resting metabolic rate using equations compared to indirect calorimetry in normal-weight subjects: Consideration of resting metabolic rate as a function of body composition Clinical Nutrition Open Science Basal metabolism Energy metabolism Body composition Calorimetry Indirect Adult |
| title | Underestimation of resting metabolic rate using equations compared to indirect calorimetry in normal-weight subjects: Consideration of resting metabolic rate as a function of body composition |
| title_full | Underestimation of resting metabolic rate using equations compared to indirect calorimetry in normal-weight subjects: Consideration of resting metabolic rate as a function of body composition |
| title_fullStr | Underestimation of resting metabolic rate using equations compared to indirect calorimetry in normal-weight subjects: Consideration of resting metabolic rate as a function of body composition |
| title_full_unstemmed | Underestimation of resting metabolic rate using equations compared to indirect calorimetry in normal-weight subjects: Consideration of resting metabolic rate as a function of body composition |
| title_short | Underestimation of resting metabolic rate using equations compared to indirect calorimetry in normal-weight subjects: Consideration of resting metabolic rate as a function of body composition |
| title_sort | underestimation of resting metabolic rate using equations compared to indirect calorimetry in normal weight subjects consideration of resting metabolic rate as a function of body composition |
| topic | Basal metabolism Energy metabolism Body composition Calorimetry Indirect Adult |
| url | http://www.sciencedirect.com/science/article/pii/S2667268521000048 |
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