Changes in Body Composition Assessed by Bioelectrical Impedance Analysis in Patients Treated With Glucagon-Like Peptide-1 Receptor Agonists: A Real-World Experience
Authors' conclusion
In real-world clinical practice, GLP-1 RA therapy combined with lifestyle interventions led to substantial improvements in body composition, characterized by predominant fat and visceral fat loss, with minimal skeletal muscle reduction.
Study context
- Population
- Adults with obesity treated with GLP-1 RAs in a specialized endocrinology clinic; 40.7% women, mean age 50.3 years
- Participants
- 388 adults
- Outcome
- Body composition changes by multifrequency bioelectrical impedance analysis
- Follow-up
- 6 months
Methodological detailsreal-world observational, single-group, specialized endocrinology clinic, Assessments at baseline, 6 weeks, 3 months and 6 months, Linear mixed models with a random intercept per patient; fully adjusted model for adherence and obesity phenotype
- Real-world observational
- Single-group
- Specialized endocrinology clinic
- Assessments at baseline, 6 weeks, 3 months and 6 months
- Linear mixed models with a random intercept per patient; fully adjusted model for adherence and obesity phenotype
Main finding
As reported in the abstract
Body composition changes
Mean weight loss (P < .001)
11.3%
Fat mass reduction
−22%
Visceral fat area decrease
−40.6 cm²
Skeletal muscle mass decrease, modest relative to fat mass reduction
−1.46 kg
Observational data: associations, not effects.
Further findings
Fat loss by adherence
- Adherent patients had greater fat loss than non-adherent patients
Anxiety and binge eating behaviors
- Improvements in anxiety and binge eating behaviors
Obesity phenotype
- Baseline differences and distinct patterns of fat and muscle loss by phenotype
Original publication
Changes in Body Composition Assessed by Bioelectrical Impedance Analysis in Patients Treated With Glucagon-Like Peptide-1 Receptor Agonists: A Real-World Experience. Endocr Pract. Published 19 September 2026. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →