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      Resting Metabolic Rate in Elite Rowers and Canoeists: Difference between Indirect Calorimetry and Prediction

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          Abstract

          Background: Athletes may differ in their resting metabolic rate (RMR) from the general population. However, to estimate the RMR in athletes, prediction equations that have not been validated in athletes are often used. The purpose of this study was therefore to verify the applicability of commonly used RMR predictions for use in athletes. Methods: The RMR was measured by indirect calorimetry in 17 highly trained rowers and canoeists of the German national teams (BMI 24 ± 2 kg/m<sup>2</sup>, fat-free mass 69 ± 15 kg). In addition, the RMR was predicted using Cunningham (CUN) and Harris-Benedict (HB) equations. A two-way repeated measures ANOVA was calculated to test for differences between predicted and measured RMR (α = 0.05). The root mean square percentage error (RMSPE) was calculated and the Bland-Altman procedure was used to quantify the bias for each prediction. Results: Prediction equations significantly underestimated the RMR in males (p < 0.001). The RMSPE was calculated to be 18.4% (CUN) and 20.9% (HB) in the entire group. The bias was 133 kcal/24 h for CUN and 202 kcal/24 h for HB. Conclusions: Predictions significantly underestimate the RMR in male heavyweight endurance athletes but not in females. In athletes with a high fat-free mass, prediction equations might therefore not be applicable to estimate energy requirements. Instead, measurement of the resting energy expenditure or specific prediction equations might be needed for the individual heavyweight athlete.

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          Comparing methods of measurement: why plotting difference against standard method is misleading

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            Predicted and measured resting metabolic rate of male and female endurance athletes.

            To measure the resting metabolic rate (RMR) of a group of endurance-trained male and female athletes and to compare it with values predicted using published equations. RMR was measured twice: 1 week apart for the men and approximately 1 month apart for the women. RMR was predicted using equations of Harris and Benedict, Owen et al, Mifflin et al, and Cunningham. Subjects were 37 trained endurance athletes (24 men, 13 women) who had participated in studies previously completed in our laboratory. The primary outcome measure was the comparison of predicted RMR with measured RMR. An exploratory procedure for the determination of predictive variables in these athletes was also performed. The Root Mean Squared Prediction Error method was used to compare predicted RMR with measured RMR. The maximum R2 procedure method was used to determine the best possible combination of four variables that explained the largest amount of variance in RMR. The Cunningham equation was found to predict measured RMR most accurately (within 158 kcal/d for men and 103 kcal/d for women). Fat-free mass was the best predictor of RMR in men, whereas energy intake was the best predictor in women. The Cunningham equation provides an accurate estimate of RMR when determining energy needs of highly active people. Equations specific to athletes need to be developed. Factors in addition to body weight, height, and age should be investigated as possible predictor variables in athletes.
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              Resting energy expenditure in children and adolescents: agreement between calorimetry and prediction equations.

              To assess the degree of agreement between indirect calorimetry and five equations commonly used to predict resting energy expenditure (REE) in obese and non-obese children and adolescents. In 116 children and adolescents (57 obese and 59 non-obese) aged between 7.8 and 16.6 years, REE was measured (MREE) by open-circuit indirect calorimetry under standardized conditions. REE was predicted (PREE) in all subjects with equations from the Food and Agriculture/World Health Organization/United Nations University (FAO/WHO/UNU), Maffeis et al., Harris and Benedict, and two from Schofield: one using weight (W) and one using height and weight (H-W). Agreement between indirect calorimetry and equations was assessed following the Bland-Altman method. In the entire cohort group, only data from FAO/WHO/UNU, Schofield-W and Schofield-HW equations showed non-statistic differences against calorimetry results. When agreement between equations and calorimetry was tested, Schofield-HW equation showed the lowest mean MREE-PREE difference: 3.7 kcal/d (limits of agreement -293 and 300 kcal/d; 95% confidence interval for the bias -24.0 to 31.5 kcal/d) and the best agreement. Group by group, equations which obtained the best agreement were: FAO/WHO/UNU in girls, Schofield-HW in boys, Schofield-HW in obese, and Schofield-W in non-obese. Until more accurate prediction equations are developed, we recommend Schofield-HW equations for REE studies with a mixed population of obese and non-obese children and adolescents; however, FAO/WHO/UNU equation may also be useful in girls and Schofield-W equation in non-obese children.
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                Author and article information

                Journal
                ANM
                Ann Nutr Metab
                10.1159/issn.0250-6807
                Annals of Nutrition and Metabolism
                S. Karger AG
                0250-6807
                1421-9697
                2011
                August 2011
                28 July 2011
                : 58
                : 3
                : 239-244
                Affiliations
                University Outpatient Clinic Potsdam, Sports Medicine and Sports Orthopaedics, University of Potsdam, Potsdam, Germany
                Author notes
                *Anja Carlsohn, E-Mail carlsohn@uni-potsdam.de
                Article
                330119 Ann Nutr Metab 2011;58:239–244
                10.1159/000330119
                21811063
                9a4b9113-056e-4d06-b567-d6cba8dc56df
                © 2011 S. Karger AG, Basel

                Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher. Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug. Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.

                History
                : 14 April 2011
                : 27 May 2011
                Page count
                Figures: 3, Tables: 1, Pages: 6
                Categories
                Original Paper

                Nutrition & Dietetics,Health & Social care,Public health
                Calorimetry,Energy requirement,Fat-free mass,Nutritional counseling,Athletes

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