Literature DB >> 31868121

Are predictive equations a valid method of assessing the resting metabolic rate of overweight or obese former athletes?

Filipe Jesus1,2, Catarina L Nunes2, Catarina N Matias2, Ruben Francisco2, Bárbara Carapeto2, Hugo Macias2, Diogo Müller2, Miguel Cardoso2, Maria J Valamatos3, Gil Rosa2, Luís B Sardinha2, Paulo Martins4, Cláudia S Minderico2, Analiza M Silva2.   

Abstract

Athletes retiring from their sports career, an understudied population, are susceptible to become overweight/obese because of decreased energy expenditure not followed by a reduction in energy intake. Therefore, their energy requirements, through resting metabolic rate (RMR), should be accurately addressed for weight management purposes. This study aimed to determine the validity of predictive equations (PEq) for RMR estimation using indirect calorimetry as the reference method in a sample of overweight/obese former athletes. The study uses cross-sectional data collected during baseline measurements of a lifestyle intervention (NCT03031951). The RMR of 56 overweight/obese (31.5 (4.0 kg/m2)) individuals (78.6% male, 37.5% obese, 95.8 (14.8 kg), 174.2 (8.7 cm)) was measured by indirect calorimetry and predicted using seven PEq: Harris-Benedict, Cunningham, Schofield, FAO/WHO/UNU, Owen, Mifflin-St. Jeor, and Katch-McArdle. Dual-energy X-ray absorptiometry was used to assess body composition. The PEq overestimated the RMR measured by the indirect calorimetry, 70-300 kcal/day (4.3-14.9%). The linear regression between the reference and each of the PEq did not differ from the identity line with estimated values explaining around 50% of the variability of the measured values. The agreement between the methods was weak for all the PEq showing wide limits of agreement. The Harris-Benedict equation was the only one in which the difference between the methods was not related to the magnitude of the measured RMR. Given the weak performance of the various RMR models in overweight/obese former athletes, an effective weight management intervention based on estimated resting energy requirements may be compromised.

Entities:  

Keywords:  Assessment; metabolism; nutrition; obesity; prediction

Year:  2020        PMID: 31868121     DOI: 10.1080/17461391.2019.1708974

Source DB:  PubMed          Journal:  Eur J Sport Sci        ISSN: 1536-7290            Impact factor:   4.050


  1 in total

1.  The Association Between Low Carbohydrate Diet and Resting Metabolic Rate in Overweight and Obese Women: A Cross-Sectional Study.

Authors:  Seyedeh Forough Sajjadi; Atieh Mirzababaei; Sara Pooyan; Niloufar Rasaei; Mir-Saeed Yekaninejad; Farideh Shiraseb; Khadijeh Mirzaei
Journal:  Clin Nutr Res       Date:  2022-01-31
  1 in total

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