Obesity management for the treatment of type 2 diabetes: emerging evidence and therapeutic approaches
Open accessAbstract
Excess adiposity can contribute to metabolic complications, such as type 2 diabetes mellitus (T2DM), which poses a significant global health burden. Traditionally viewed as a chronic and irreversible condition, T2DM management has evolved and new approaches emphasizing reversal and remission are emerging. Bariatric surgery demonstrates significant improvements in body weight and glucose homeostasis. However, its complexity limits widespread implementation as a population-wide intervention. The identification of glucagon-like peptide 1 (GLP-1) and the development of GLP-1 receptor agonists (GLP-1RAs) have improved T2DM management and offer promising outcomes in terms of weight loss. Innovative treatment approaches combining GLP-1RA with other gut and pancreatic-derived hormone receptor agonists, such as glucose-dependant insulinotropic peptide (GIP) and glucagon (GCG) receptor agonists, or coadministered with amylin analogues, are demonstrating enhanced efficacy in both weight loss and glycemic control. This review aims to explore the benefits of bariatric surgery and emerging pharmacological therapies such as GLP-1RAs, and dual and triple agonists in managing obesity and T2DM while highlighting the caveats and evolving landscape of treatment options.
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Within the same category of GLP-1 mono-agonists or dual-agonists, there was considerable variability in weight reduction effects, which may be related to different affinities of drugs for receptors.
“Additionally, even within the same category of GLP-1 mono-agonists or dual-agonists, there was considerable variability in weight reduction effects, which may be related to the different affinities of drugs for receptors [23,24].”
From Comparative efficacy and safety of GLP-1 receptor agonists for weight reduction: A model-based meta-analysis of placebo-controlled trials (2025) · cites this paper as [23]
The GLP-1RA-based therapies section reports different weight-loss results for the mono-agonists liraglutide (6%) and semaglutide (9.6%) in separate trials. It does not establish variability among dual-agonists or suggest that differences in receptor affinity explain the weight-loss results. The copy provides no page numbers for these passages. (LLM, conf=0.84)
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- Authors
- Morissette, A., & Mulvihill, E. E.
- Affiliations
- Ottawa Heart Institute (CA)
- University of Ottawa (CA)
- Corresponding author
- Mulvihill, Erin E.
- ORCID
- Mulvihill, Erin E.
- Venue
- Journal of Pharmacy & Pharmaceutical Sciences
- Publisher
- Frontiers Media SA
- Published
- 2024-06-06
- Volume
- 27
- Pages
- 13065-13065
- ISSN
- 1482-1826 (ISSN-L)
- PMC
- PMC11186996
- OpenAlex
- W4399527310
- Cited by
- 8
- References
- 77
- Citations by year
- 2026: 3 · 2025: 5
- FWCI
- 0.47
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Pharmacy & Pharmaceutical Sciences (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Diabetes Canada
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Health Sciences › Medicine › Pharmacology › Pharmacology and Obesity Treatment
- Health Sciences › Medicine › Surgery › Bariatric Surgery and Outcomes
- Keywords
- type 2 diabetes, obesity, bariatric surgery, GLP-1 receptor agonists, glucagon-like peptide-1, glucose-dependent insulinotropic polypeptide, glucagon receptor agonist, amylin analogues, weight loss, glycemic control, diabetes remission
- MeSH terms
- Glucagon-Like Peptide-1 Receptor, Obesity Management, Glucagon-Like Peptide-1 Receptor Agonists, Diabetes Mellitus, Type 2, Humans, Hypoglycemic Agents, Obesity, Weight Loss, Bariatric Surgery, Glucagon-Like Peptide 1
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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