Presentation (CTI)

OBJECTIVES: Social Determinants of Health (SDOH) influence quality and access to medical care. Recently, several GLP-1 (glucagon-like peptide-1) medications have been approved to manage type 2 diabetes (T2D) and later to manage obesity. SDOH indicators, such as income, influence how clinicians prescribe medication and the likelihood that patients will fill their prescriptions. The goal of this analysis was to evaluate how SDOH influence prescribing behavior for GLP-1 medications.
METHODS: This analysis used the TriNetX Linked Network, which includes approximately 21 million de-identified US-based patients, with electronic health record data linked to insurance claims and SDOH data. The target trial emulation approach was used to reduce bias. Logistic regression (LR) methods were used to evaluate the association between SDOH factors and medication prescriptions among a cohort of patients with evidence of type 2 diabetes or obesity. We also assessed whether Bayesian Network (BN) analysis can enrich our understanding of this relationship.
RESULTS: About 1 million patients had a diagnosis of obesity or type 2 diabetes during the study period, which included patients with clinical encounters between 2022 and 2025. The rate of GLP-1 prescription ranged from 3% to 20% based on patient diagnoses and characteristics, with a combined diagnosis of T2D and obesity showing the highest rate. Female patients were more likely to be prescribed GLP-1 medications than male patients, especially those with an obesity diagnosis and higher income. Among the key SDOHs, higher income increased the probability of GLP-1 prescription, while education level was not associated with it.
CONCLUSIONS: Patient demographic and social characteristics influence GLP-1 medication prescription. Analyzing data using LR and BN provides complementary information.