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01 · ABSTRACT

Abstract

Obesity is a major contributor to ill health. Until recently, the number of individuals developing obesity has continued to rise, contributing to the global burden of many common and serious conditions including premature cardiovascular disease, type 2 diabetes (T2D), and some cancers. However, in 2023 in the United States (U.S.), evidence suggests that there has been a decline in the number of obese adults. One factor to which this reduction has been attributed has been the introduction of a new class of drugs for the treatment of obesity and T2D, known as Glucagon Like Peptide-1 Receptor Agonists (GLP-1 RA’s). These drugs are undoubtedly effective in promoting weight loss 1, and clinical outcomes have been favorable (2-6), including reducing the risk of progression to T2D in adults with obesity and prediabetes 7  as well as beneficial effects on lowering the burden of cardio-renal disease.  Although there have been many studies of the clinical benefits of GLP-1 drugs, there have been fewer focusing on their economic effectiveness. There is also a paucity of published research into the potential of stratifying and targeting individuals with T2D and/or obesity into sub-populations to produce a focused financial return on investment.  Our analysis of US commercial claims data shows that many patients transition between different categories of obesity over time; only the highest obesity class (BMI 40.0 and over) show persistency in the highest class over time, indicating that the focus of treatment with GLP-1 RAs should be on the severely obese.

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02 · PUBLICATION RECORD

Article details

JournalMedical Research Archives
IssueVol 13 No 1 (2025): Vol.13 issue 1 January 2025
SectionResearch Articles
Published30 January 2025
DOI10.18103/mra.v13i1.6138
ISSN2375-1924
03 · RIGHTS & REUSE

Rights & reuse

This article is published under a Creative Commons Attribution License (CC BY 3.0) and may be shared or distributed by anyone as long as attribution is given to the journal.

Authors & affiliations

ID

Ian Duncan, PhD FSA MAAA

Dept. of Statistics & Applied Probability, University of California, Santa Barbara CA 2 Sutter Health, San Francisco CA

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