title: Resting energy expenditure: systematic organization and critique of prediction methods.
abstract: There are many published methods for predicting resting energy expenditure (REE) from measured body composition. Although these published reports extend back almost a century, new related studies appear on a regular basis. It remains unclear what the similarities and differences are among these various methods and what, if any, advantages the newly introduced REE prediction models offer. These issues led us to develop an organizational system for REE prediction methods with the goal of clarifying prevailing ambiguities in the field. Our classification scheme is founded on body composition level (whole-body, tissue-organ, cellular, and molecular) and related components as the REE predictor variables. Each existing REE prediction method by body composition must belong to one body composition level. The suggested classification system, founded on a conceptual basis, highlights similarities and differences among the diverse REE-body composition prediction methods, provides a framework for teaching REE-body composition relationships, and identifies important future research opportunities.
authors.affiliation: Obesity Research Center, St. Luke's-Roosevelt Hospital, Columbia University College of Physicians and Surgeons, New York, NY, USA. ZW28@Columbia.edu
authors.forename: Z
authors.initials: Z
authors.lastname: Wang
authors.forename: S
authors.initials: S
authors.lastname: Heshka
authors.forename: K
authors.initials: K
authors.lastname: Zhang
authors.forename: C N
authors.initials: CN
authors.lastname: Boozer
authors.forename: S B
authors.initials: SB
authors.lastname: Heymsfield
mesh_terms: D000818:Animals; D001481:Basal Metabolism; D001823:Body Composition; D006801:Humans; D008954:Models, Biological; D008962:Models, Theoretical