Associations between CT-based body composition parameters and glycemic control in adults with type 2 diabetes mellitus: a retrospective cohort study
Li Z., Xing Y., Chen Y., Jiang S.
Laboratory Study on Type 2 Diabetes, published in Endocr Connect (2026) — summary generated from the PubMed abstract.
Evidence from laboratory and animal studies provides groundwork for understanding mechanisms and potential before human studies continue.
- Level A · Stronger Clinical Evidence
- Level B · Emerging clinical evidence with positive signals
- Level C · Early human research exploring benefits
- Level D · Scientific groundwork from lab and animal studies
- Emerging · Emerging topic under active research
This page is generated from the PubMed record. The Thai description is an automated summary of bibliographic fields and the abstract, not a full translation, and is not medical advice.
- Study type
- Laboratory Study
- Journal
- Endocr Connect (2026)
- Reported sample size
- —
- Source database
- Europe PMC
- PMID
- 41543021
- PMCID
- PMC12862201
- DOI
- 10.1530/ec-25-0772
Abstract (original English)
Background Type 2 diabetes mellitus (T2DM) is characterized by insulin resistance and impaired insulin secretion, leading to persistent hyperglycemia and multisystem complications. Adipose tissue distribution - visceral, subcutaneous, and intermuscular - varies in metabolic and inflammatory activity, influencing insulin sensitivity and systemic glucose homeostasis. Skeletal muscle also plays a critical role in glucose disposal. This study aims to evaluate the associations between CT-derived body composition metrics and glycemic control in adults with T2DM and to explore inter-individual variations in fat and muscle distribution. Methods In this retrospective cohort study, 651 adults with T2DM underwent chest CT imaging. Body composition - including visceral, subcutaneous, intermuscular, and total adipose tissue areas, along with skeletal muscle area - was quantified at the T8 vertebral level. Glycemic control was assessed using HbA1c (>7% indicating suboptimal control). Multivariable logistic regression models were employed to evaluate associations between body composition metrics and glycemic status, with adjustment for cardiometabolic and lifestyle covariates. The correlation between body composition and HbA1c was analyzed using dose-response relationships and smooth curve fitting. Subgroup analysis was then performed based on gender, age, diabetes duration, hypertension, lif
What this study does not prove
- • This study does not prove SVF is an approved treatment or a replacement for standard care.
- • This is preclinical work; animal or laboratory results cannot be applied to humans.
Evidence level
Evidence from laboratory and animal studies provides groundwork for understanding mechanisms and potential before human studies continue.
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