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Predictive Mathematical Models of Weight Loss.
Thomas, Diana M; Scioletti, Michael; Heymsfield, Steven B.
Afiliação
  • Thomas DM; Department of Mathematical Sciences, United States Military Academy, West Point, NY, 10996, USA. diana.thomas@westpoint.edu.
  • Scioletti M; Department of Mathematical Sciences, United States Military Academy, West Point, NY, 10996, USA.
  • Heymsfield SB; Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA.
Curr Diab Rep ; 19(10): 93, 2019 08 31.
Article em En | MEDLINE | ID: mdl-31473830
PURPOSE OF REVIEW: Validated thermodynamic energy balance models that predict weight change are ever more in use today. Delivery of model predictions using web-based applets and/or smart phones has transformed these models into viable clinical tools. Here, we provide the general framework for thermodynamic energy balance model derivation and highlight differences between thermodynamic energy balance models using four representatives. RECENT FINDINGS: Energy balance models have been used to successfully improve dietary adherence, estimate the magnitude of food waste, and predict dropout from clinical weight loss trials. They are also being used to generate hypotheses in nutrition experiments. Applications of thermodynamic energy balance weight change prediction models range from clinical applications to modify behavior to deriving epidemiological conclusions. Novel future applications involve using these models to design experiments and provide support for treatment recommendations.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Redução de Peso / Metabolismo Energético / Sobrepeso / Modelos Biológicos Tipo de estudo: Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Curr Diab Rep Assunto da revista: ENDOCRINOLOGIA Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Redução de Peso / Metabolismo Energético / Sobrepeso / Modelos Biológicos Tipo de estudo: Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Curr Diab Rep Assunto da revista: ENDOCRINOLOGIA Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Estados Unidos