ArticleThe Journal of clinical endocrinology and metabolism2024
Skewness in Body fat Distribution Pattern Links to Specific Cardiometabolic Disease Risk Profiles.
Article in The Journal of clinical endocrinology and metabolism, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- Associations between fat distribution and obstructive sleep apnea severity among individuals with type 2 diabetes: an MRI-based study.Scientific reports · 2026Article
- Optimal visceral adipose tissue thresholds that minimize risk for osteoporosis and/or diabetes in midlife women.Journal of the Endocrine Society · 2026Article
- Hepatic and abdominal adiposity in type 2 diabetes as assessed with machine learning on computed tomography scans.Diabetes, obesity & metabolism · 2026Article
- The Multiscale Heterogeneity of Adipose Tissue in Health and Disease.Research (Washington, D.C.) · 2026Review
- Advances in Molecular Mechanisms and Precision Interventions of Cardiovascular Injuries Related to Glucose and Lipid Metabolism Disorders.Reviews in cardiovascular medicine · 2025Review
- Longitudinal changes in regional fat and muscle composition and cardiometabolic biomarkers over 5 years of hormone therapy in transgender individuals.Journal of internal medicine · 2025Article
- Liver transplant recipients have worse metabolic body phenotype compared with matched non-transplant controls.JGH open : an open access journal of gastroenterology and hepatology · 2024Article
- Skewness in Body fat Distribution Pattern Links to Specific Cardiometabolic Disease Risk Profiles.The Journal of clinical endocrinology and metabolism · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
Abstract
objectiveFat distribution pattern could help determine cardiometabolic risk profile. This study aimed to evaluate the association of balance/imbalance between visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (aSAT), and liver fat (LF) with incident type 2 diabetes (T2D) and cardiovascular disease (CVD) in the UK Biobank prospective cohort study.
methodsMagnetic resonance images of 40 174 participants were analyzed for VAT, aSAT, and LF using AMRA® Researcher. To assess fat distribution patterns independent of body mass index (BMI), fat z-scores (z-VAT, z-aSAT, z-LF) were calculated. Participants without prevalent T2D/CVD (N = 35 138) were partitioned based on balance between (1) z-VAT and z-LF (z-scores = 0 as cut-points for high/low), (2) z-VAT and z-aSAT, and (3) z-LF and z-aSAT. Associations with T2D/CVD were investigated using Cox regression (crude and adjusted for sex, age, BMI, lifestyle, arterial hypertension, statin treatment).
resultsT2D was significantly associated with z-LF (hazard ratio, [95% CI] 1.74 [1.52-1.98], P < .001) and z-VAT (1.70 [1.49-1.95], P < .001). Both remained significant after full adjustment. For z-scores balance, strongest associations with T2D were z-VAT > 0 and z-LF > 0 (4.61 [2.98-7.12]), z-VAT > 0 and z-aSAT < 0 (4.48 [2.85-7.06]), and z-LF > 0 and z-aSAT < 0 (2.69 [1.76-4.12]), all P < .001. CVD was most strongly associated with z-VAT (1.22 [1.16-1.28], P < .001) which remained significant after adjustment for sex, age, BMI, and lifestyle. For z-scores balance, strongest associations with CVD were z-VAT > 0 and z-LF < 0 (1.53 [1.34-1.76], P < .001) and z-VAT > 0 and z-aSAT < 0 (1.54 [1.34-1.76], P < .001). When adjusted for sex, age, and BMI, only z-VAT > 0 and z-LF < 0 remained significant.
conclusionHigh VAT in relation to BMI (z-VAT > 0) was consistently linked to both T2D and CVD; z-LF > 0 was linked to T2D only. Skewed fat distribution patterns showed elevated risk for CVD (z-VAT > 0 and z-LF < 0 and z-VAT > 0 and z-aSAT < 0) and T2D (z-VAT > 0 and z-aSAT < 0).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.