Observational studyAnnals of internal medicine2025
Association Between Body Composition and Cardiometabolic Outcomes : A Prospective Cohort Study.
Observational study in Annals of internal medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Opportunistic screening for incident cardiometabolic disease in metabolically healthy non-obese individuals: a prospective cohort study.Cardiovascular diabetology · 2026Article
- Application of Artificial Intelligence in the Diagnosis, Prediction, and Management of Metabolic Syndrome: A Systematic Review.Health science reports · 2026Review
- Serum metabolite patterns of adipose tissue distribution and body composition subphenotypes.Lipids in health and disease · 2026Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundCurrent measures of adiposity have limitations. Artificial intelligence (AI) models may accurately and efficiently estimate body composition (BC) from routine imaging.
objectiveTo assess the association of AI-derived BC compartments from magnetic resonance imaging (MRI) with cardiometabolic outcomes.
designProspective cohort study.
settingUK Biobank (UKB) observational cohort study.
participants33 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/m MEASUREMENTS: An AI tool was applied to MRI to derive 3-dimensional (3D) BC measures, including subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), skeletal muscle (SM), and SM fat fraction (SMFF), and then calculate their relative distribution. Sex-stratified associations of these relative compartments with incident diabetes mellitus (DM) and major adverse cardiovascular events (MACE) were assessed using restricted cubic splines.
resultsAdipose tissue compartments and SMFF increased and SM decreased with age. After adjustment for age, smoking, and hypertension, greater adiposity and lower SM proportion were associated with higher incidence of DM and MACE after a median follow-up of 4.2 years in sex-stratified analyses; however, after additional adjustment for BMI and waist circumference (WC), only elevated VAT proportions and high SMFF (top fifth percentile in the cohort for each) were associated with increased risk for DM (respective adjusted hazard ratios [aHRs], 2.16 [95% CI, 1.59 to 2.94] and 1.27 [CI, 0.89 to 1.80] in females and 1.84 [CI, 1.48 to 2.27] and 1.84 [CI, 1.43 to 2.37] in males) and MACE (1.37 [CI, 1.00 to 1.88] and 1.72 [CI, 1.23 to 2.41] in females and 1.22 [CI, 0.99 to 1.50] and 1.25 [CI, 0.98 to 1.60] in males). In addition, in males only, those in the bottom fifth percentile of SM proportion had increased risk for DM (aHR for the bottom fifth percentile of the cohort, 1.96 [CI, 1.45 to 2.65]) and MACE (aHR, 1.55 [CI, 1.15 to 2.09]). LIMITATION: Results may not be generalizable to non-Whites or people outside the United Kingdom.
conclusionArtificial intelligence-derived BC proportions were strongly associated with cardiometabolic risk, but after BMI and WC were accounted for, only VAT proportion and SMFF (both sexes) and SM proportion (males only) added prognostic information. PRIMARY FUNDING SOURCE: None.
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