|Title:||Anthropometric and body composition equations to predict resting energy expenditure in overweight and obese men and women living in a temperate climate||Authors:||Galván Álvarez, Víctor
Perez Valera, Mario
Morales Álamo, David
De Pablos Velasco, Pedro Luis
López Calbet, José Antonio
Martín Rincón, Marcos
|UNESCO Clasification:||241106 Fisiología del ejercicio||Issue Date:||2020||Project:||Viabilidad y sostenibilidad del adelgazamiento mediante tratamiento intensificado en pacientes con sobrepeso u obesidad: mecanismos neuroendocrinos y moleculares
Estudio longitudinal de los efectos de una modificación intensiva del estilo de vida en la composición corporal e indicadores bioquímicos y moleculares de salud en pacientes con sobrepeso y obesidad: aplicación para la evaluación fisiológica de rutas y sistemas de monitorización del esfuerzo ...
|Conference:||25th Annual Congress of the European College of Sport Science (ECSS 2020)||Abstract:||The resting energy expenditure (REE) is commonly determined by indirect calorimetry. However, in clinical and nutrition settings, it is usually unfeasible and thus prediction equations are employed using anthropometric (ANT) and/or body composition (BC) data. Epidemiological evidence has shown an association between ambient temperature and body weight in humans, and particularly high prevalence of obesity when living in temperate climates. The aim was to develop equations to predict REE of overweight and obese living in a temperate climate all-year round and to determine the accuracy of traditional equations in this population. METHODS: Overweight and obese men and women (n=174) living permanently in Gran Canaria agreed to participate (age: 18-70 yr; BMI>27 kg.m2). REE was measured in fasting conditions by indirect calorimetry (Vmax N29). For anthropometric assessment, body weight and height were measured with a balance scale while body composition by DXA. Stepwise multiple regression analysis was used to determine the best predictors of REE in our population by two models (ANT and BC-based). The agreement of our measured REE was compared to the estimation by 20 widely employed ANT-based equations by calculating: bias (absolute values and %), the limit of agreement (LA) (upper LA=bias+1.96xSD; lower LA=bias-1.96xSD), concordance correlation coefficient (CCC). The % of subjects whose predicted REE fell within 10% of the measured REE was taken as a measure of accuracy. Statistical significance was set at p<0.05.||URI:||http://hdl.handle.net/10553/119851||ISBN:||9783981841435||Source:||25th Annual Congress of the European College of Sport Science (ECSS 2020)|
|Appears in Collections:||Actas de congresos|
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