Guillermo Sanchez-Delgado1, Juan M A Alcantara2, Lourdes Ortiz-Alvarez2, Huiwen Xu2, Borja Martinez-Tellez3, Idoia Labayen4, Jonatan R Ruiz2. 1. PROFITH "PROmoting FITness and Health Through Physical Activity" Research Group, Department of Physical Education and Sport, Faculty of Sport Sciences, University of Granada, Ctra de Alfacar s/n, C.P. 18071, Spain. Electronic address: gsanchezdelgado@ugr.es. 2. PROFITH "PROmoting FITness and Health Through Physical Activity" Research Group, Department of Physical Education and Sport, Faculty of Sport Sciences, University of Granada, Ctra de Alfacar s/n, C.P. 18071, Spain. 3. PROFITH "PROmoting FITness and Health Through Physical Activity" Research Group, Department of Physical Education and Sport, Faculty of Sport Sciences, University of Granada, Ctra de Alfacar s/n, C.P. 18071, Spain; Department of Medicine, Division of Endocrinology, Leiden University Medical Center, Albinusdreef 2, 2333, Leiden, The Netherlands. 4. Department of Health Sciences, Public University of Navarra, Pamplona, Avda. Barañáisn s/n., 31008, Spain.
Abstract
BACKGROUND & AIMS: A high inter-day reliability is a key factor to analyze the magnitude of change in resting metabolic rate (RMR) after an intervention, and the impact of using different methods for data analysis is not known. The aims of this study were: i) to analyze the impact of methods for data analysis on RMR and respiratory exchange ratio (RER) estimation; ii) to analyze the impact of methods for data analysis on inter-day RMR and RER reliability; iii) to compare inter-day RMR and RER reliability across methods for data analysis in participants who achieved steady state (SS) vs. participants who did not achieve SS. METHODS: Seventeen young healthy adults completed two 30-min indirect calorimetry (IC) measures on two consecutive mornings, using two metabolic carts each day. Two methods for data analysis were used: i) Selection of a predefined time interval (TI) every 5 min (1-5 min, 6-10 min, 11-15 min, 16-20 min, 21-25 min, 26-30 min); and TI representing the whole measurement period (0-30 min, 5-30 min, 5-25 min); and ii) Methods based on the selection of the most stable period (SSt methods) (3 min SSt, 4 min SSt, 5 min SSt, 10 min SSt). Additionally, participants were classified as those achieving SS (CV < 10% for VO2, VCO2 and VE, and CV < 5% for RER) and those who did not. RESULTS: RMR and RER measurements were lower when following SSt methods than when following TI methods (all P < 0.01). Although no significant differences were found between different lengths of SSt, 5 min SSt presented the lowest RMR. There were no differences on the inter-day reliability across methods for data analysis (TI and SSt) (all P > 0.2), and there was no systematic bias when comparing RMR and RER day 1 and day 2 measurements (all P > 0.1). Inter-day reliability was similar in individuals who achieved the SS and individuals who did not achieve it. The results were consistent independently of the metabolic cart used. CONCLUSIONS: The 5 min SSt approach should be the method of choice for analyzing IC measures with metabolic carts. However, achieving SS should not be an inclusion criterion in an IC study with young healthy adults.
BACKGROUND & AIMS: A high inter-day reliability is a key factor to analyze the magnitude of change in resting metabolic rate (RMR) after an intervention, and the impact of using different methods for data analysis is not known. The aims of this study were: i) to analyze the impact of methods for data analysis on RMR and respiratory exchange ratio (RER) estimation; ii) to analyze the impact of methods for data analysis on inter-day RMR and RER reliability; iii) to compare inter-day RMR and RER reliability across methods for data analysis in participants who achieved steady state (SS) vs. participants who did not achieve SS. METHODS: Seventeen young healthy adults completed two 30-min indirect calorimetry (IC) measures on two consecutive mornings, using two metabolic carts each day. Two methods for data analysis were used: i) Selection of a predefined time interval (TI) every 5 min (1-5 min, 6-10 min, 11-15 min, 16-20 min, 21-25 min, 26-30 min); and TI representing the whole measurement period (0-30 min, 5-30 min, 5-25 min); and ii) Methods based on the selection of the most stable period (SSt methods) (3 min SSt, 4 min SSt, 5 min SSt, 10 min SSt). Additionally, participants were classified as those achieving SS (CV < 10% for VO2, VCO2 and VE, and CV < 5% for RER) and those who did not. RESULTS: RMR and RER measurements were lower when following SSt methods than when following TI methods (all P < 0.01). Although no significant differences were found between different lengths of SSt, 5 min SSt presented the lowest RMR. There were no differences on the inter-day reliability across methods for data analysis (TI and SSt) (all P > 0.2), and there was no systematic bias when comparing RMR and RER day 1 and day 2 measurements (all P > 0.1). Inter-day reliability was similar in individuals who achieved the SS and individuals who did not achieve it. The results were consistent independently of the metabolic cart used. CONCLUSIONS: The 5 min SSt approach should be the method of choice for analyzing IC measures with metabolic carts. However, achieving SS should not be an inclusion criterion in an IC study with young healthy adults.
Authors: Michelle I Cardel; Greg Pavela; David Janicke; Tianyao Huo; Darci Miller; Alexandra M Lee; Matthew J Gurka; Emily Dhurandhar; John C Peters; Ann E Caldwell; Eric Krause; Alicia Fernandez; David B Allison Journal: Obesity (Silver Spring) Date: 2020-11 Impact factor: 5.002
Authors: Borja Martinez-Tellez; Guillermo Sanchez-Delgado; Mariëtte R Boon; Patrick C N Rensen; José M Llamas-Elvira; Jonatan R Ruiz Journal: Mol Imaging Biol Date: 2020-04 Impact factor: 3.488
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Authors: Guillermo Sanchez-Delgado; Borja Martinez-Tellez; Yolanda Garcia-Rivero; Juan M A Alcantara; Francisco M Acosta; Francisco J Amaro-Gahete; Jose M Llamas-Elvira; Jonatan R Ruiz Journal: Front Physiol Date: 2018-11-16 Impact factor: 4.566
Authors: A M Coletta; B Sanchez; A O'Connor; R Dalton; S Springer; M S Koozehchian; P S Murano; C R Woodman; C Rasmussen; R B Kreider Journal: Obes Sci Pract Date: 2018-11-26