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Predicting energy intake in adults who are dieting and exercising.
Gerving, Corey; Lasater, Robert; Starling, James; Ostendorf, Danielle M; Redman, Leanne M; Estabrooks, Chad; Cummiskey, Kevin; Antonetti, Vincent; Thomas, Diana M.
Affiliation
  • Gerving C; Department of Physics and Nuclear Engineering, United States Military Academy, West Point, NY, 10996, USA.
  • Lasater R; Department of Mathematical Sciences, United States Military Academy, West Point, NY, US.
  • Starling J; Department of Mathematical Sciences, United States Military Academy, West Point, NY, US.
  • Ostendorf DM; Department of Medicine, Division of Endocrinology, Metabolism, and Diabetes, University of Colorado-Anschutz Medical Campus, Aurora, CO, USA.
  • Redman LM; Pennington Biomedical Research Center, Baton Rouge, LA, USA.
  • Estabrooks C; Belmont Abbey College, Belmont, NC, USA.
  • Cummiskey K; Department of Mathematical Sciences, United States Military Academy, West Point, NY, US.
  • Antonetti V; Department of Mechanical Engineering, Manhattan College, New York City, NY, USA.
  • Thomas DM; Department of Mathematical Sciences, United States Military Academy, West Point, NY, US. diana.thomas@westpoint.edu.
Int J Obes (Lond) ; 46(12): 2095-2101, 2022 12.
Article de En | MEDLINE | ID: mdl-35987955
BACKGROUND: When a lifestyle intervention combines caloric restriction and increased physical activity energy expenditure (PAEE), there are two components of energy balance, energy intake (EI) and physical activity energy expenditure (PAEE), that are routinely misreported and expensive to measure. Energy balance models have successfully predicted EI if PAEE is known. Estimating EI from an energy balance model when PAEE is not known remains an open question. OBJECTIVE: The objective was to evaluate the performance of an energy balance differential equation model to predict EI in an intervention that includes both calorie restriction and increases in PAEE. DESIGN: The Antonetti energy balance model that predicts body weight trajectories during weight loss was solved and inverted to estimate EI during weight loss. Using data from a calorie restriction study that included interventions with and without prescribed PAEE, we tested the validity of the Antonetti weight predictions against measured weight and the Antonetti EI model against measured EI using the intake-balance method at 168 days. We then evaluated the predicted EI from the model against measured EI in a study that prescribed both calorie restriction and increased PAEE. RESULTS: Compared with measured body weight at 168 days, the mean (±SD) model error was 1.30 ± 3.58 kg. Compared with measured EI at 168 days, the mean EI (±SD) model error in the intervention that prescribed calorie restriction and did not prescribe increased PAEE, was -84.9 ± 227.4 kcal/d. In the intervention that prescribed calorie restriction combined with increased PAEE, the mean (±SD) EI model error was -155.70 ± 205.70 kcal/d. CONCLUSION: The validity of the newly developed EI model was supported by experimental observations and can be used to determine EI during weight loss.
Sujet(s)

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Ration calorique / Exercice physique Type d'étude: Prognostic_studies / Risk_factors_studies Limites: Adult / Humans Langue: En Journal: Int J Obes (Lond) Sujet du journal: METABOLISMO Année: 2022 Type de document: Article Pays d'affiliation: États-Unis d'Amérique Pays de publication: Royaume-Uni

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Ration calorique / Exercice physique Type d'étude: Prognostic_studies / Risk_factors_studies Limites: Adult / Humans Langue: En Journal: Int J Obes (Lond) Sujet du journal: METABOLISMO Année: 2022 Type de document: Article Pays d'affiliation: États-Unis d'Amérique Pays de publication: Royaume-Uni