{"doi":"10.1101/2024.10.28.24316312","title":"Racial and Ethnic Disparities in Prescribing of GLP-1 Receptor Agonists in the United States: A Retrospective Cohort Analysis","abstract":"Background: Type 2 diabetes (T2D) represents a major public health burden in the United States, with racial disparities in medication use potentially exacerbating inequities in health outcomes. This study examined racial/ethnic differences in the prescription of high-efficacy glucose-lowering medications for T2D using a large EHR network (TriNetX). Methods: A retrospective cohort study included adults with uncomplicated T2D (ICD-10: E11.9), categorized as Hispanic or Latino (Hispanic) or non-Hispanic American Indian/Alaska Native (AI/AN), Asian, Black, Native Hawaiian/Pacific Islander (NH/PI), and White. Adjusted odds ratios for GLP-1 receptor agonist medications (tirzepatide, semaglutide, and dulaglutide) prescriptions in 2022-2023 were calculated by race/ethnicity, controlling for age, sex, and Charlson Comorbidity Index. Findings: Among 57,320 patients included in the analysis, we observed significant racial disparities in the prescribing of GLP-1 medications. Compared to White patients, for tirzepatide, adjusted odds ratios prescriptions were 0.6 (95% CI: 0.4-0.9) for AI/AN, 0.3 (95% CI: 0.3-0.4) for Asian, 0.7 (95% CI: 0.6-0.9) for Black, 0.4 (95% CI: 0.3-0.5) for Hispanic, and 0.4 (95% CI: 0.3-0.6) for NH/PI. For semaglutide, adjusted odds ratios were 0.8 (95% CI: 0.7-0.9) for AI/AN, 0.5 (95% CI: 0.5-0.6) for Asian, 0.8 (95% CI: 0.7-0.9) for Black, 0.6 (95% CI: 0.6-0.7) for Hispanic, and 0.6 (95% CI: 0.5-0.8) for NH/PI. For dulaglutide, adjusted odds ratios were 1.2 (95% CI: 1.0-1.4) for AI/AN, 0.5 (95% CI: 0.4-0.5) for Asian, 1.0 (95% CI: 0.9-1.1) for Black, 0.9 (95% CI: 0.8-1.0) for Hispanic, and 0.5 (95% CI: 0.4-0.6) for NH/PI. Interpretation: Racial disparities in high-efficacy diabetes medication prescriptions may contribute to unequal health outcomes in T2D, highlighting the need for targeted research and interventions for equitable diabetes care.","journal":"medRxiv","year":2024,"id":485755,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":5,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.654,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":361483,"name":"Julio C. Facelli","orcid":"0000-0003-1449-477X","position":1,"is_corresponding":false},{"id":473372,"name":"Matthew J. O’Brien","orcid":"0000-0001-8882-9865","position":2,"is_corresponding":false},{"id":361482,"name":"Ramkiran Gouripeddi","orcid":"0000-0002-4345-9669","position":3,"is_corresponding":false},{"id":32954,"name":"Kensaku Kawamoto","orcid":"0000-0003-4282-9338","position":4,"is_corresponding":false},{"id":424143,"name":"Yue Zhang","orcid":"0000-0002-4124-4816","position":5,"is_corresponding":false},{"id":1142945,"name":"Deepika Reddy","orcid":"0000-0001-6889-0378","position":6,"is_corresponding":false},{"id":72920,"name":"Daniel C. Malone","orcid":"0000-0002-5006-9394","position":7,"is_corresponding":false},{"id":336637,"name":"Polina Kukhareva","orcid":"0000-0002-5576-1486","position":0,"is_corresponding":true}],"reference_count":13,"raw_metadata":null,"created_at":"2026-07-19T02:07:52.536246Z","pmid":"39574878","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}