Association Between Body Composition and Cardiometabolic Outcomes : A Prospective Cohort Study.

ABSTRACT:

Background

Current measures of adiposity have limitations. Artificial intelligence (AI) models may accurately and efficiently estimate body composition (BC) from routine imaging.

Objective

To assess the association of AI-derived BC compartments from magnetic resonance imaging (MRI) with cardiometabolic outcomes.

Design

Prospective cohort study.

Setting

UK Biobank (UKB) observational cohort study.

Participants

33 432 UKB participants with no history of diabetes, myocardial infarction, or ischemic stroke (mean age, 65.0 years [SD, 7.8]; mean body mass index [BMI], 25.8 kg/m² [SD, 4.2]; 52.8% female) who underwent whole-body MRI.

Measurements

An AI tool was applied to MRI to derive 3-dimensional (3D) BC measures, including subcutaneous adi

SUBMITTER: Jung M 

PROVIDER: S-EPMC12560800 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature