Predicting Weight Regain Following Weight Loss Using Physiological Measures of Appetite and Energy Expenditure
- Institution
- Drexel University, PA
- Principal investigator
- Michael R Lowe
- Funding
- $1.1M
- Duration
- 2021–2026
Moonbase score
Still being scored
Abstract
PROJECT SUMMARY / ABSTRACT The success of behavioral weight loss programs is undermined by weight regain. Controversy exists about how much physiological adaptations to the weight reduced state contribute to weight regain. Further, little is known about the relative contributions to relapse of increased metabolic efficiency and increased appetitive drive. Even if metabolic efficiency increases with weight loss, this does not necessarily mean that successful dieters are hypo- metabolic in their weight-reduced state. To address these scientific questions, we will recruit 100 individuals into a weight loss program based on a modified version of the Diabetes Prevention Program. Qualified participants will be assessed at baseline and reassessed if they attain a minimum 7% weight loss (called month 0) and undergo follow- up assessments 4 and 12-months later. Reassessment at month 4 will allow us to study the transition to maintenance as a dynamic process (i.e., change from month 0 to 4), not just as a discrete change of state (from baseline to month 0). Changes in physiological measures of metabolism and appetite during weight loss will be used to predict individual differences in weight regain. Physiological outcome measures will include: 1) energy metabolism (e.g., resting and non-resting energy expenditure, 2) neural indicators of appetitive drive (e.g., striatal activation to food cues and food tastes) and 3) samples will be collected for studies of neuroendocrine responses to fasting and fed states (e.g., leptin, GLP-1). A comprehensive biobank of blood, fecal, muscle and adipose tissue will also be collected for future discovery studies. Our measures and expertise will provide new insight into the physiological determinants of weight regain following weight loss that could help improve obesity treatments in the future.
Research team
- Kelly C AllisonPI
- Matthew R HayesPI
- Michael R LowePI
- Susan B RobertsPI
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