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Accumulating Data to Optimally Predict Obesity Treatment (ADOPT): Recommendations from the Biological Domain
- Source :
- Obesity. 26:S25-S34
- Publication Year :
- 2018
- Publisher :
- Wiley, 2018.
-
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.
- Subjects :
- 0301 basic medicine
030109 nutrition & dietetics
Nutrition and Dietetics
business.industry
Endocrinology, Diabetes and Metabolism
Medicine (miscellaneous)
030209 endocrinology & metabolism
Adult obesity
medicine.disease
Obesity
Biobank
Energy homeostasis
03 medical and health sciences
0302 clinical medicine
Endocrinology
Risk analysis (engineering)
medicine
business
Psychosocial
Subjects
Details
- ISSN :
- 19307381
- Volume :
- 26
- Database :
- OpenAIRE
- Journal :
- Obesity
- Accession number :
- edsair.doi...........3ca48ff9b52537bc59d3a2ecab2de84b
- Full Text :
- https://doi.org/10.1002/oby.22156