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Balci A, Badem EA, Yılmaz AE, Devrim-Lanpir A, Akınoğlu B, Kocahan T, Hasanoğlu A, Hill L, Rosemann T, Knechtle B. Current Predictive Resting Metabolic Rate Equations Are Not Sufficient to Determine Proper Resting Energy Expenditure in Olympic Young Adult National Team Athletes. Front Physiol 2021; 12:625370. [PMID: 33613316 PMCID: PMC7890252 DOI: 10.3389/fphys.2021.625370] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 01/12/2021] [Indexed: 12/31/2022] Open
Abstract
Predictive resting metabolic rate (RMR) equations are widely used to determine athletes’ resting energy expenditure (REE). However, it remains unclear whether these predictive RMR equations accurately predict REE in the athletic populations. The purpose of the study was to compare 12 prediction equations (Harris-Benedict, Mifflin, Schofield, Cunningham, Owen, Liu’s, De Lorenzo) with measured RMR in Turkish national team athletes and sedentary controls. A total of 97 participants, 49 athletes (24 females, 25 males), and 48 sedentary (28 females, 20 males), were recruited from Turkey National Olympic Teams at the Ministry of Youth and Sports. RMR was measured using a Fitmate GS (Cosmed, Italy). The results of each 12 prediction formulas were compared with the measured RMR using paired t-test. The Bland-Altman plot was performed to determine the mean bias and limits of agreement between measured and predicted RMRs. Stratification according to sex, the measured RMR was greater in athletes compared to controls. The closest equation to the RMR measured by Fitmate GS was the Harris-Benedict equation in male athletes (mean difference -8.9 (SD 257.5) kcal/day), and Liu’s equation [mean difference -16.7 (SD 195.0) kcal/day] in female athletes. However, the intra-class coefficient (ICC) results indicated that all equations, including Harris-Benedict for male athletes (ICC = 0.524) and Liu’s for female athletes (ICC = 0.575), had a moderate reliability compared to the measured RMR. In sedentary subjects, the closest equation to the measured RMR is the Nelson equation in males, with the lowest RMSE value of 118 kcal/day [mean difference: 10.1 (SD 117.2) kJ/day], whereas, in females, all equations differ significantly from the measured RMR. While Nelson (ICC = 0.790) had good and Owen (ICC = 0.722) and Mifflin (calculated using fat-free mass) (ICC = 0.700) had moderate reliability in males, all predictive equations showed poor reliability in females. The results indicate that the predictive RMR equations failed to accurately predict RMR levels in the participants. Therefore, it may not suitable to use them in determining total energy expenditure.
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Affiliation(s)
- Aydın Balci
- Department of Sports Medicine, Ankara Yıldırım Beyazıt University, Yenimahalle Training and Research Hospital, Ankara, Turkey
| | - Ebru Arslanoğlu Badem
- Department of Health Services, Sports General Directorship, The Ministry of Youth and Sports, Center of Athlete Training and Health Research, Ankara, Turkey
| | | | - Aslı Devrim-Lanpir
- Department of Nutrition and Dietetics, Faculty of Health Sciences, Istanbul Medeniyet University, Istanbul, Turkey
| | - Bihter Akınoğlu
- Department of Health Services, Sports General Directorship, The Ministry of Youth and Sports, Center of Athlete Training and Health Research, Ankara, Turkey.,Department of Physiotherapy and Rehabilitation, Faculty of Health Sciences, Ankara Yıldırım Beyazıt University, Ankara, Turkey
| | - Tuğba Kocahan
- Department of Health Services, Sports General Directorship, The Ministry of Youth and Sports, Center of Athlete Training and Health Research, Ankara, Turkey
| | - Adnan Hasanoğlu
- Department of Health Services, Sports General Directorship, The Ministry of Youth and Sports, Center of Athlete Training and Health Research, Ankara, Turkey
| | - Lee Hill
- Division of Gastroenterology and Nutrition, Department of Pediatrics, McMaster University, Hamilton, ON, Canada
| | - Thomas Rosemann
- Institute of Primary Care, University of Zurich, Zurich, Switzerland
| | - Beat Knechtle
- Institute of Primary Care, University of Zurich, Zurich, Switzerland
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Chang CH, Hsu YJ, Li F, Tu YT, Jhang WL, Hsu CW, Huang CC, Ho CS. Reliability and validity of the physical activity monitor for assessing energy expenditures in sedentary, regularly exercising, non-endurance athlete, and endurance athlete adults. PeerJ 2020; 8:e9717. [PMID: 32904158 PMCID: PMC7450994 DOI: 10.7717/peerj.9717] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 07/23/2020] [Indexed: 12/24/2022] Open
Abstract
Background Inertial sensors, such as accelerometers, serve as convenient devices to predict the energy expenditures (EEs) during physical activities by a predictive equation. Although the accuracy of estimate EEs especially matter to athletes receive physical training, most EE predictive equations adopted in accelerometers are based on the general population, not athletes. This study included the heart rate reserve (HRR) as a compensatory parameter for physical intensity and derived new equations customized for sedentary, regularly exercising, non-endurance athlete, and endurance athlete adults. Methods With indirect calorimetry as the criterion measure (CM), the EEs of participants on a treadmill were measured, and vector magnitudes (VM), as well as HRR, were simultaneously recorded by a waist-worn accelerometer with a heart rate monitor. Participants comprised a sedentary group (SG), an exercise-habit group (EHG), a non-endurance group (NEG), and an endurance group (EG), with 30 adults in each group. Results EE predictive equations were revised using linear regression with cross-validation on VM, HRR, and body mass (BM). The modified model demonstrates valid and reliable predictions across four populations (Pearson correlation coefficient, r: 0.922 to 0.932; intraclass correlation coefficient, ICC: 0.919 to 0.930). Conclusion Using accelerometers with a heart rate monitorcan accurately predict EEs of athletes and non-athletes with an optimized predictive equation integrating the VM, HRR, and BM parameters.
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Affiliation(s)
- Chun-Hao Chang
- Graduate Institute of Sports Science, National Taiwan Sport University, Taoyuan, Taiwan
| | - Yi-Ju Hsu
- Graduate Institute of Sports Science, National Taiwan Sport University, Taoyuan, Taiwan
| | - Fang Li
- Graduate Institute of Sports Science, National Taiwan Sport University, Taoyuan, Taiwan
| | - Yu-Tsai Tu
- Graduate Institute of Sports Science, National Taiwan Sport University, Taoyuan, Taiwan.,Department of Physical Medicine and Rehabilitation, Taipei City Hospital, Zhongxiao Branch, Taipei, Taiwan
| | - Wei-Lun Jhang
- Graduate Institute of Sports Science, National Taiwan Sport University, Taoyuan, Taiwan
| | - Chih-Wen Hsu
- Graduate Institute of Sports Science, National Taiwan Sport University, Taoyuan, Taiwan
| | - Chi-Chang Huang
- Graduate Institute of Sports Science, National Taiwan Sport University, Taoyuan, Taiwan
| | - Chin-Shan Ho
- Graduate Institute of Sports Science, National Taiwan Sport University, Taoyuan, Taiwan
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