# Predicting Weight Regain Following Weight Loss Using Physiological Measures of Appetite and Energy Expenditure

> **NIH NIH UG3** · DREXEL UNIVERSITY · 2021 · $250,000

## Abstract

PROJECT SUMMARY
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 2 and 18-months later.
Reassessment at month 2 will allow us to study the transition to maintenance as a dynamic
process (i.e., change from month 0 to 2), not just as a discrete change of state (from baseline to
month 0). A control group of 33 weight-stable overweight individuals, matched to successful
weight losers on BMI and other variables, will be recruited at time 0 and compared to weight
losers on all outcome measures. Changes in physiological measures of metabolism and
appetite during weight loss will be used to predict individual differences in weight regain. By
comparing weight-losing to weight-stable individuals, we will develop a unique reference point
for interpreting the results of the within-group predictive analyses. 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) 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.

## Key facts

- **NIH application ID:** 10189945
- **Project number:** 1UG3DK128298-01
- **Recipient organization:** DREXEL UNIVERSITY
- **Principal Investigator:** MATTHEW R HAYES
- **Activity code:** UG3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $250,000
- **Award type:** 1
- **Project period:** 2021-04-24 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10189945

## Citation

> US National Institutes of Health, RePORTER application 10189945, Predicting Weight Regain Following Weight Loss Using Physiological Measures of Appetite and Energy Expenditure (1UG3DK128298-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10189945. Licensed CC0.

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