Literature DB >> 30035381

Human energy expenditure: advances in organ-tissue prediction models.

S B Heymsfield1, C M Peterson2, B Bourgeois1, D M Thomas3, D Gallagher4, B Strauss5, M J Müller6, A Bosy-Westphal6.   

Abstract

Humans expend energy at rest (REE), and this major energy exchange component is now usually estimated using statistical equations that include weight and other predictor variables. While these formulas are useful in evaluating an individual's or group's REE, an important gap remains: available statistical models are inadequate for explaining underlying organ-specific and tissue-specific mechanisms accounting for resting heat production. The lack of such systems level REE prediction models leaves many research questions unanswered. A potential approach that can fill this gap began with investigators who first showed in animals and later in humans that REE reflects the summated heat production rates of individual organs and tissues. Today, using advanced imaging technologies, REE can be accurately estimated from the measured in vivo mass of 10 organ-tissue mass components combined with their respective mass-specific metabolic rates. This review examines the next frontier of energy expenditure models and discusses how organ-tissue models have the potential not only to better predict REE but also to provide insights into how perturbations in organ mass lead to structure-function changes across other interacting organ systems. The introductory ideas advanced in this review provide a framework for future human energy expenditure modelling research.
© 2018 World Obesity Federation.

Entities:  

Keywords:  Body composition; energy metabolism; obesity; resting energy expenditure

Mesh:

Year:  2018        PMID: 30035381      PMCID: PMC6107421          DOI: 10.1111/obr.12718

Source DB:  PubMed          Journal:  Obes Rev        ISSN: 1467-7881            Impact factor:   9.213


  63 in total

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