A Comparison Of Resting Metabolic Rate Using Indirect Calorimetry, Bioelectrical Impedance And Prediction Equations.

PURPOSE: Many equations exist to predict resting metabolic rate (RMR) when it is not possible to measure it using indirect calorimetry with a metabolic cart or handheld device. Additionally, specialized whole-body bioelectrical impedance (BIA) machines can utilize measured body composition parameters to estimate RMR. However, how the estimations compare to measured RMR via indirect calorimetry is not clear. The purpose of this study was to compare RMR values from BIA, prediction equations and different forms of indirect calorimetry. METHODS: Adult males (n = 22; age: 33 ± 13 years; height: 180 ± 8 cm; weight: 85 ± 16 kg) and females (n = 37; age: 33 ± 13 years; height: 165 ± 6 cm; weight: 75 ± 25 kg) reported to the lab for a BIA analysis (InBody 770) followed by 40 minutes of RMR measurement via indirect calorimetry with a metabolic cart (IC; MCG Ultima) and a handheld device (MedGem). Comparisons between measured RMR, predicted RMR provided by the BIA (BMR + 10%), and published RMR prediction equations based on age and gender were made. SUMMARY OF RESULTS: There was no significant difference measured RMR values from the IC and BIA (p = 0.27, mean difference (md): 35 kcal/day). However, IC RMR was significantly greater than estimation equations (De Lorenzo (p < 0.001, md = 123 kcal/day), FAO Age 18-30 (p < 0.001, md = 693 kcal/day), FAO Age 30-60 (p < 0.001, md = 848 kcal/day), Oxford Age 18-30 (p < 0.001, md = 732 kcal/day), and Oxford Age 30-60 (p < 0.0.025, md = 882 kcal/day)), while being significantly lower than Harris-Benedict (p = 0.002, md = 92 kcal/day) and Livingston equations (p < 0.001, md = 650 kcal/day). There was a significant difference in the measured values from the IC and the MedGem (p < 0.001, md = 341 kcal/day). CONCLUSION: In comparison to measured RMR from the metabolic cart, most of the prediction equations overestimated RMR (average 279 kcal/day). Furthermore, the measured RMR from IC using the MGC Ultima was significantly higher than the value calculated from the MedGem. The RMR estimated from the InBody 770 BIA appeared to be accurate compared to the MGC Ultima.

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Publication Details

Journal
Medicine & Science in Sports & Exercise
Published
2024-09-16
DOI
https://doi.org/10.1249/01.mss.0001055984.71110.84
Primary Topic
Adipose Tissue and Metabolism
Type
article
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article

A Comparison Of Resting Metabolic Rate Using Indirect Calorimetry, Bioelectrical Impedance And Prediction Equations.

Angela R. Hillman, K. I. Golden
Medicine & Science in Sports & Exercise
Adipose Tissue and Metabolism
article

A Comparison Of Resting Metabolic Rate Using Indirect Calorimetry, Bioelectrical Impedance And Prediction Equations.

Angela R. Hillman, K. I. Golden
article en

Abstract

PURPOSE: Many equations exist to predict resting metabolic rate (RMR) when it is not possible to measure it using indirect calorimetry with a metabolic cart or handheld device. Additionally, specialized whole-body bioelectrical impedance (BIA) machines can utilize measured body composition parameters to estimate RMR. However, how the estimations compare to measured RMR via indirect calorimetry is not clear. The purpose of this study was to compare RMR values from BIA, prediction equations and different forms of indirect calorimetry. METHODS: Adult males (n = 22; age: 33 ± 13 years; height: 180 ± 8 cm; weight: 85 ± 16 kg) and females (n = 37; age: 33 ± 13 years; height: 165 ± 6 cm; weight: 75 ± 25 kg) reported to the lab for a BIA analysis (InBody 770) followed by 40 minutes of RMR measurement via indirect calorimetry with a metabolic cart (IC; MCG Ultima) and a handheld device (MedGem). Comparisons between measured RMR, predicted RMR provided by the BIA (BMR + 10%), and published RMR prediction equations based on age and gender were made. SUMMARY OF RESULTS: There was no significant difference measured RMR values from the IC and BIA (p = 0.27, mean difference (md): 35 kcal/day). However, IC RMR was significantly greater than estimation equations (De Lorenzo (p < 0.001, md = 123 kcal/day), FAO Age 18-30 (p < 0.001, md = 693 kcal/day), FAO Age 30-60 (p < 0.001, md = 848 kcal/day), Oxford Age 18-30 (p < 0.001, md = 732 kcal/day), and Oxford Age 30-60 (p < 0.0.025, md = 882 kcal/day)), while being significantly lower than Harris-Benedict (p = 0.002, md = 92 kcal/day) and Livingston equations (p < 0.001, md = 650 kcal/day). There was a significant difference in the measured values from the IC and the MedGem (p < 0.001, md = 341 kcal/day). CONCLUSION: In comparison to measured RMR from the metabolic cart, most of the prediction equations overestimated RMR (average 279 kcal/day). Furthermore, the measured RMR from IC using the MGC Ultima was significantly higher than the value calculated from the MedGem. The RMR estimated from the InBody 770 BIA appeared to be accurate compared to the MGC Ultima.

Medicine & Science in Sports & ExerciseVol. 56(10S)
Ohio University (US)
Openalex Percentile: Top 78%
Adipose Tissue and Metabolism
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