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Accumulating Data to Optimally Predict Obesity Treatment (ADOPT): Recommendations from the Biological Domain.
Rosenbaum, Michael; Agurs-Collins, Tanya; Bray, Molly S; Hall, Kevin D; Hopkins, Mark; Laughlin, Maren; MacLean, Paul S; Maruvada, Padma; Savage, Cary R; Small, Dana M; Stoeckel, Luke.
Afiliação
  • Rosenbaum M; Columbia University, Vagelos College of Physicians & Surgeons, New York, New York, USA.
  • Agurs-Collins T; National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.
  • Bray MS; Department of Nutritional Sciences, University of Texas at Austin, Austin, Texas, USA.
  • Hall KD; National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, USA.
  • Hopkins M; School of Food Science and Nutrition, University of Leeds, Leeds, England.
  • Laughlin M; National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, USA.
  • MacLean PS; School of Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA.
  • Maruvada P; School of Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA.
  • Savage CR; Center for Brain, Biology and Behavior, Department of Psychology, University of Nebraska, Lincoln, Nebraska, USA.
  • Small DM; Yale University Medical School, New Haven, Connecticut, USA.
  • Stoeckel L; National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, USA.
Obesity (Silver Spring) ; 26 Suppl 2: S25-S34, 2018 04.
Article em En | MEDLINE | ID: mdl-29575784
ABSTRACT

BACKGROUND:

The responses to behavioral, pharmacological, or surgical obesity treatments are highly individualized. The Accumulating Data to Optimally Predict obesity Treatment (ADOPT) project provides a framework for how obesity researchers, working collectively, can generate the evidence base needed to guide the development of tailored, and potentially more effective, strategies for obesity treatment.

OBJECTIVES:

The objective of the ADOPT biological domain subgroup is to create a list of high-priority biological measures for weight-loss studies that will advance the understanding of individual variability in response to adult obesity treatments. This list includes measures of body composition, energy homeostasis (energy intake and output), brain structure and function, and biomarkers, as well as biobanking procedures, which could feasibly be included in most, if not all, studies of obesity treatment. The recommended high-priority measures are selected to balance needs for sensitivity, specificity, and/or comprehensiveness with feasibility to achieve a commonality of usage and increase the breadth and impact of obesity research.

SIGNIFICANCE:

The accumulation of data on key biological factors, along with behavioral, psychosocial, and environmental factors, can generate a more precise description of the interplay and synergy among them and their impact on treatment responses, which can ultimately inform the design and delivery of effective, tailored obesity treatments.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Obesidade Tipo de estudo: Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Obesity (Silver Spring) Assunto da revista: CIENCIAS DA NUTRICAO / FISIOLOGIA / METABOLISMO Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Obesidade Tipo de estudo: Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Obesity (Silver Spring) Assunto da revista: CIENCIAS DA NUTRICAO / FISIOLOGIA / METABOLISMO Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos