Guillermo Sanchez-Delgado1, Juan M A Alcantara2, Francisco M Acosta2, Borja Martinez-Tellez3, Francisco J Amaro-Gahete4, Lourdes Ortiz-Alvarez2, Marie Löf5, Idoia Labayen6, 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, Granada, 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, Granada, 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, Granada, Spain; Department of Medicine, Division of Endocrinology and Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, The Netherlands. 4. PROFITH (PROmoting FITness and Health through Physical Activity) Research Group, Department of Physical Education and Sport, Faculty of Sport Sciences, University of Granada, Granada, Spain; Department of Medical Physiology, School of Medicine, University of Granada, Granada, Spain. 5. Department of Biosciences and Nutrition, Karolinska Institutet, NOVUM, Huddinge, Sweden; Department of Medical and Health Sciences, Linköping University, 581 83, Linköping, Sweden. 6. Institute for Innovation & Sustainable Development in Food Chain (IS-FOOD), Public University of Navarra, 31006 Pamplona, Navarra, Spain.
Abstract
BACKGROUND & AIMS: Since the discovery of active brown adipose tissue in human adults, non-shivering cold-induced thermogenesis (CIT) has been regarded as a promising tool to combat obesity. However, there is a lack of consensus regarding the method of choice to analyze indirect calorimetry data from a CIT study. We analyzed the impact of methods for data selection and methods for data analysis on measures of cold-induced energy expenditure (EE) and nutrient oxidation rates. METHODS: Forty-four young healthy adults (22.1 ± 2.1 years old, 25.6 ± 5.2 kg/m2, 29 women) participated in the study. Resting metabolic rate (RMR), cold-induced thermogenesis (CIT), and cold-induced nutrient oxidation rates were estimated by indirect calorimetry under fasting conditions during 1 h of cold exposure combining air conditioning (19.5-20 °C) and a water perfused cooling vest set at a temperature of 4 °C above the individual shivering threshold. We applied three methods for data selection: (i) time intervals every 5 min (5min-TI), (ii) the most stable 5-min period of every forth part of the cold exposure (5min-SS-4P), and (iii) the most stable 5-min period of every half part of the cold exposure (5min-SS-2P). Lately we applied two methods for data analysis: (i) area under the curve as a percentage of the baseline RMR (AUC) and; (ii) the difference between EE at the end of the cold exposure and baseline RMR (Last-RMR). RESULTS: Mean overall CIT estimation ranged from 11.6 ± 10.0 to 20.1 ± 17.2 %RMR depending on the methods for data selection and analysis used. Regarding methods for data selection, 5min-SS-2P did not allow to observe physiologically relevant phenomena (e.g. metabolic shift in fuel oxidation; P = 0.547) due to a lack of resolution. The 5min-TI and 5min-SS-4P methods for data selection seemed to be accurate enough to observe physiologically relevant phenomena (all P < 0.014), but not comparable for estimating over-all CIT and cold-induced nutrient oxidation rates (P < 0.01). Regarding methods for data analysis, the AUC seemed to be less affected for data artefacts and to be more representative in participants with a non-stable energy expenditure during cold exposure. CONCLUSIONS: The methods for data selection and analysis can have a profound impact on CIT and cold-induced nutrient oxidation rates estimations, and therefore, it is mandatory to unify it across scientific community to allow inter-study comparisons. Based on our findings, 5min-TI should be considered the method of choice to study dynamics (i.e. changes across time) of CIT and cold-induced nutrient oxidation rates, while 5min-SS-4P and AUC should be the method of choice when computing CIT and cold-induced nutrient oxidation rates as a single value.
BACKGROUND & AIMS: Since the discovery of active brown adipose tissue in human adults, non-shivering cold-induced thermogenesis (CIT) has been regarded as a promising tool to combat obesity. However, there is a lack of consensus regarding the method of choice to analyze indirect calorimetry data from a CIT study. We analyzed the impact of methods for data selection and methods for data analysis on measures of cold-induced energy expenditure (EE) and nutrient oxidation rates. METHODS: Forty-four young healthy adults (22.1 ± 2.1 years old, 25.6 ± 5.2 kg/m2, 29 women) participated in the study. Resting metabolic rate (RMR), cold-induced thermogenesis (CIT), and cold-induced nutrient oxidation rates were estimated by indirect calorimetry under fasting conditions during 1 h of cold exposure combining air conditioning (19.5-20 °C) and a water perfused cooling vest set at a temperature of 4 °C above the individual shivering threshold. We applied three methods for data selection: (i) time intervals every 5 min (5min-TI), (ii) the most stable 5-min period of every forth part of the cold exposure (5min-SS-4P), and (iii) the most stable 5-min period of every half part of the cold exposure (5min-SS-2P). Lately we applied two methods for data analysis: (i) area under the curve as a percentage of the baseline RMR (AUC) and; (ii) the difference between EE at the end of the cold exposure and baseline RMR (Last-RMR). RESULTS: Mean overall CIT estimation ranged from 11.6 ± 10.0 to 20.1 ± 17.2 %RMR depending on the methods for data selection and analysis used. Regarding methods for data selection, 5min-SS-2P did not allow to observe physiologically relevant phenomena (e.g. metabolic shift in fuel oxidation; P = 0.547) due to a lack of resolution. The 5min-TI and 5min-SS-4P methods for data selection seemed to be accurate enough to observe physiologically relevant phenomena (all P < 0.014), but not comparable for estimating over-all CIT and cold-induced nutrient oxidation rates (P < 0.01). Regarding methods for data analysis, the AUC seemed to be less affected for data artefacts and to be more representative in participants with a non-stable energy expenditure during cold exposure. CONCLUSIONS: The methods for data selection and analysis can have a profound impact on CIT and cold-induced nutrient oxidation rates estimations, and therefore, it is mandatory to unify it across scientific community to allow inter-study comparisons. Based on our findings, 5min-TI should be considered the method of choice to study dynamics (i.e. changes across time) of CIT and cold-induced nutrient oxidation rates, while 5min-SS-4P and AUC should be the method of choice when computing CIT and cold-induced nutrient oxidation rates as a single value.
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