Abstract
BackgroundMany studies have been performed over time in order to determine the reliability of metabolic rate prediction equations.PurposeTo evaluate the agreement, in terms of bias, absolute bias and accuracy between metabolic rate prediction equations and measured metabolic rate using indirect calorimetry system (IC), investigating also the factors affecting this agreement.MethodsThe anthropometric features of 383 Caucasian participants of all Body Mass Index (BMI) classes were recorded and Resting Metabolic Rate (RMR) was measured by using the IC Fitmate portable device. The resulting values were compared with the predictive values of Harris & Benedict, Schofield, Owen, FAO-WHO-UNU, Mifflin and Harrington equations.ResultsA closer approximation in agreement was obtained using the Harrington equation (based on BMI, age and gender). The equations using variables, such as weight, height, age and gender demonstrated higher agreement than the equations using merely weight and gender. Higher educational level was associated with normal weight, while higher calorific ratio was found in the class of normal-weighted individuals. An inverse relationship between ΒΜΙ and RMR was also observed and a logarithmic equation for calculating RMR was created, which was differentiated in relation to BMI classes, using the weight and gender variables.ConclusionA better measurement agreement between RMR prediction equations and IC may be achieved due to BMI consideration. The present findings contributed to a better understanding of the measured parameters, confirming the inverse relationship between BMI and RMR. Age group and gender variables may also exert significant role on the bias response of some RMR equations.
Highlights
Many studies have been performed over time in order to determine the reliability of metabolic rate prediction equations.Purpose: To evaluate the agreement, in terms of bias, absolute bias and accuracy between metabolic rate prediction equations and measured metabolic rate using indirect calorimetry system (IC), investigating the factors affecting this agreement
The present findings contributed to a better understanding of the measured parameters, confirming the inverse relationship between Body Mass Index (BMI) and Resting Metabolic Rate (RMR)
Terms such as Basal Metabolic Rate (BMR) [1,2,3,4] or Resting Metabolic Rate (RMR) [5, 2] are used to define this energy expenditure and are often confused with each other, they vary by approximately 10%
Summary
Many studies have been performed over time in order to determine the reliability of metabolic rate prediction equations.Purpose: To evaluate the agreement, in terms of bias, absolute bias and accuracy between metabolic rate prediction equations and measured metabolic rate using indirect calorimetry system (IC), investigating the factors affecting this agreement. The highest amount of this energy (50–75%) is essential for the development and maintenance of basic organic functions, while the person is at rest. Terms such as Basal Metabolic Rate (BMR) [1,2,3,4] or Resting Metabolic Rate (RMR) [5, 2] are used to define this energy expenditure and are often confused with each other, they vary by approximately 10%. The rest of metabolic rate is the amount of energy expended for the individual’s physical activity and is expressed as Total Energy Expenditure (ΤΕΕ). TEE is the sum of BMR or RMR, taking into account physical activity or exercise (20–40%), Thermic Effect of Food (TEF) which ranges between 5 and 30% and sometimes adaptive thermogenesis or/and Stress [9, 10]
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