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Updated: Jun 23, 2025

Control of Eating Behavior Using a Novel Feedback System
Published on: May 8, 2018
A predictive model for medium-term weight loss response in people with type 2 diabetes engaging in behavioural weight
Lulwa Al-Abdullah1,2, Amy Ahern3, Paul Welsh1
1School of Cardiovascular and Metabolic Health, University of Glasgow, BHF Glasgow Cardiovascular Research Centre, Glasgow, UK.
Aims:
To develop and evaluate prediction models for medium-term weight loss response in behavioural weight management programmes.
Materials And Methods:
We conducted three longitudinal analyses using the Action for HEalth in Diabetes (LookAHEAD) trial, Weight loss Referrals for Adults in Primary care (WRAP) trial, and routine data from the National Health Service Greater Glasgow and Clyde Weight Management Service (NHS-GGCWMS). We investigated predictors of medium-term weight loss (>5% body weight) over 3 years in NHS-GGCWMS and, separately, predictors of weight loss response in LookAHEAD over 4 years. We validated predictors in both studies using WRAP over 5 years. Predictors of interest included demographic and clinical variables, early weight change in-programme (first 4 weeks) and overall in-programme weight change.
Results:
In LookAHEAD and WRAP the only baseline variables consistently associated with weight loss response were female sex and older age. Of 1152 participants in NHS-GGCWMS (mean age 57.8 years, 60% female, type 2 diabetes diagnosed for a median of 5.3 years), 139 lost weight over 3 years (12%). The strongest predictor of weight loss response was early weight change (odds ratio 2.22, 95% confidence interval 1.92-2.56) per 1% weight loss. Losing 0.5% weight in the first 4 weeks predicted medium-term weight loss (sensitivity 89.9%, specificity 49.5%, negative predictive value 97.3%). Overall in-programme weight change was also associated with weight loss response over 3 years in NHS-GGCWMS and over 5 years in WRAP.
Conclusions:
Not attaining a weight loss threshold of 0.5% early in weight management programmes may identify participants who would benefit from alternative interventions.
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