Estimating the agreement between the metabolic rate calculated from prediction equations and from a portable indirect calorimetry device: an effort to develop a new equation for predicting resting metabolic rate
Abstract Background 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 i...
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| Format: | Article |
| Language: | English |
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BMC
2018-06-01
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| Series: | Nutrition & Metabolism |
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| Online Access: | http://link.springer.com/article/10.1186/s12986-018-0278-7 |
| _version_ | 1818040333374586880 |
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| author | Eleni Pavlidou Dimitris Petridis Maria Tolia Nikolaos Tsoukalas Antigoni Poultsidi Aristeidis Fasoulas George Kyrgias Constantinos Giaginis |
| author_facet | Eleni Pavlidou Dimitris Petridis Maria Tolia Nikolaos Tsoukalas Antigoni Poultsidi Aristeidis Fasoulas George Kyrgias Constantinos Giaginis |
| author_sort | Eleni Pavlidou |
| collection | DOAJ |
| description | Abstract Background 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 also the factors affecting this agreement. Methods The 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. Results A 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. Conclusion A 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. |
| first_indexed | 2024-12-10T08:12:52Z |
| format | Article |
| id | doaj.art-b1459893ee944f1eb74c9e88b56213c4 |
| institution | Directory Open Access Journal |
| issn | 1743-7075 |
| language | English |
| last_indexed | 2024-12-10T08:12:52Z |
| publishDate | 2018-06-01 |
| publisher | BMC |
| record_format | Article |
| series | Nutrition & Metabolism |
| spelling | doaj.art-b1459893ee944f1eb74c9e88b56213c42022-12-22T01:56:33ZengBMCNutrition & Metabolism1743-70752018-06-011511910.1186/s12986-018-0278-7Estimating the agreement between the metabolic rate calculated from prediction equations and from a portable indirect calorimetry device: an effort to develop a new equation for predicting resting metabolic rateEleni Pavlidou0Dimitris Petridis1Maria Tolia2Nikolaos Tsoukalas3Antigoni Poultsidi4Aristeidis Fasoulas5George Kyrgias6Constantinos Giaginis7Department of Food Science and Nutrition, University of AegeanDepartment of Food Technology, Technological Educational InstituteDepartment of Radiotherapy, School of Health Sciences, Faculty of Medicine, University of ThessalyDepartment of Oncology, Veterans Hospital (NIMTS)Surgery Clinic, School of Health Sciences, Faculty of Medicine, University of ThessalyDepartment of Food Science and Nutrition, University of AegeanDepartment of Radiotherapy, School of Health Sciences, Faculty of Medicine, University of ThessalyDepartment of Food Science and Nutrition, University of AegeanAbstract Background 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 also the factors affecting this agreement. Methods The 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. Results A 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. Conclusion A 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.http://link.springer.com/article/10.1186/s12986-018-0278-7Basal metabolic rateIndirect calorimetryPredictive equationResting energy expenditureResting metabolic rate |
| spellingShingle | Eleni Pavlidou Dimitris Petridis Maria Tolia Nikolaos Tsoukalas Antigoni Poultsidi Aristeidis Fasoulas George Kyrgias Constantinos Giaginis Estimating the agreement between the metabolic rate calculated from prediction equations and from a portable indirect calorimetry device: an effort to develop a new equation for predicting resting metabolic rate Nutrition & Metabolism Basal metabolic rate Indirect calorimetry Predictive equation Resting energy expenditure Resting metabolic rate |
| title | Estimating the agreement between the metabolic rate calculated from prediction equations and from a portable indirect calorimetry device: an effort to develop a new equation for predicting resting metabolic rate |
| title_full | Estimating the agreement between the metabolic rate calculated from prediction equations and from a portable indirect calorimetry device: an effort to develop a new equation for predicting resting metabolic rate |
| title_fullStr | Estimating the agreement between the metabolic rate calculated from prediction equations and from a portable indirect calorimetry device: an effort to develop a new equation for predicting resting metabolic rate |
| title_full_unstemmed | Estimating the agreement between the metabolic rate calculated from prediction equations and from a portable indirect calorimetry device: an effort to develop a new equation for predicting resting metabolic rate |
| title_short | Estimating the agreement between the metabolic rate calculated from prediction equations and from a portable indirect calorimetry device: an effort to develop a new equation for predicting resting metabolic rate |
| title_sort | estimating the agreement between the metabolic rate calculated from prediction equations and from a portable indirect calorimetry device an effort to develop a new equation for predicting resting metabolic rate |
| topic | Basal metabolic rate Indirect calorimetry Predictive equation Resting energy expenditure Resting metabolic rate |
| url | http://link.springer.com/article/10.1186/s12986-018-0278-7 |
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