Differential impact of glucagon-like peptide-1 (GLP-1) receptor agonists for weight loss in the type 2 diabetic and non-diabetic populations.

BACKGROUND: Glucagon-like peptide-1 (GLP-1) receptor agonists have emerged as a cornerstone therapy for obesity management, yet long-term comparative effectiveness across diabetes status, adherence, and specific agents remains unclear. This study evaluates multi-year weight-loss outcomes associated with GLP-1 therapy and characterizes medication- and phenotype-specific differences. METHODS: This study represents a subgroup analysis of a large-scale meta-analysis including clinical trials, observational and case-control studies published from 2010 to 2025 reporting long-term weight outcomes for GLP-1 agents. Outcomes were evaluated across mixed, intention-to-treat (ITT), and treatment-adherent populations and stratified by diabetes status. Mixed-effects meta-regression was performed to evaluate independent predictors of weight loss. RESULTS: A total of 56,580 patients from 45 studies were included. GLP-1 therapy consistently produced greater weight loss than placebo across all populations. Non-diabetic participants achieved the greatest reductions, losing 15.7% of baseline weight at 12 months versus 5.1% in diabetic users in the mixed cohort. ITT results were similar but modestly attenuated, whereas adherent patients demonstrated the largest reductions. Diabetes status was a strong effect modifier: non-diabetic individuals achieved 2.5-4 × greater reductions than diabetics receiving the same agents. Meta-regression confirmed diabetes status as an independent negative predictor of weight loss (β =  - 1.77, p < 0.001). Semaglutide produced significantly greater reductions than liraglutide after adjustment (β =  + 1.67, p < 0.001), while baseline BMI was inversely associated with percent weight change (β =  + 0.46, p < 0.001). CONCLUSION: GLP-1 therapies produce durable weight loss with outcomes strongly influenced by diabetes status, adherence, and agent selection. These findings support a personalized, phenotype-based approach to GLP-1 prescribing.