| Title: | Association between triglyceride glucose-body mass index and the trajectory of cardio-renal-metabolic multimorbidity: insights from multi-state modelling |
| Journal: | Cardiovascular Diabetology |
| Published: | 21 Mar 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40119385/ |
| DOI: | https://doi.org/10.1186/s12933-025-02693-w |
| URL: | https://link.springer.com/content/pdf/10.1186/s12933-025-02693-w.pdf |
Publication 15539
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Abstract
BackgroundAlthough some studies have examined the association between the triglyceride glucose-body mass index (TyG-BMI) and cardiovascular outcomes in the cardio-renal-metabolic (CRM) background, none have explored its role in the progression of CRM multimorbidity. In addition, prior research is limited by small sample sizes and a failure to account for the competitive effects of other CRM diseases.MethodsIn this study, data obtained from the large-scale, prospective UK Biobank cohort were used. CRM multimorbidity was defined as the new-onset of ischemic heart disease, type 2 diabetes mellitus, or chronic kidney disease during follow-up. Multivariable Cox regression was used to analyse the independent association between TyG-BMI and each CRM multimorbidity (first, double, or triple CRM diseases). The C-statistic was calculated for each model, and a restricted cubic spline was applied to assess the dose-response relationship. A multi-state model was used to investigate the association between TyG-BMI and the trajectory of CRM multimorbidity (from baseline [without CRM disease] to the first CRM disease, the first CRM disease to double disease, and double disease to triple disease), with disease-specific analyses.ResultsThis study included 349,974 participants, with a mean age of 56.05 (standard deviation [SD], 8.08), 55.93% of whom were female. Over a median follow-up of approximately 14 years, 56,659 (16.19%) participants without baseline CRM disease developed at least one CRM disease, including 8451 (14.92%) who progressed to double CRM disease and 789 (9.34%) who further developed triple CRM disease. In the crude model, each SD increase in TyG-BMI was associated with a 47% higher risk of the first CRM disease, a 72% higher risk of double CRM disease, and a 95% higher risk of triple CRM disease, with C-statistics of 0.625, 0.694, and 0.764, respectively. Multi-state model analysis showed a 32% increased risk of new CRM disease, a 24% increased risk of progression to double CRM disease, and a 23% increased risk of further progression for those with double CRM diseases. TyG-BMI was significantly associated with the onset of all individual first CRM diseases (except for stroke) and with the transition to double CRM disease. Significant interactions were also observed, but TyG-BMI remained significantly associated with CRM multimorbidity across subgroups. Sensitivity analyses, including varying time intervals for entering states and an expanded CRM definition (including atrial fibrillation, heart failure, peripheral vascular disease, obesity, and dyslipidaemia), confirmed these findings.ConclusionTyG-BMI remarkably influences the onset and progression of CRM multimorbidity. Incorporating it into CRM multimorbidity prevention and management could have important public health implications.Graphical abstract</p>
20 Keywords
- Aged
- Biomarkers
- Blood Glucose
- Body Mass Index
- Cardiometabolic Risk Factors
- Diabetes Mellitus, Type 2
- Disease Progression
- Female
- Humans
- Male
- Middle Aged
- Multimorbidity
- Prognosis
- Prospective Studies
- Renal Insufficiency, Chronic
- Risk Assessment
- Risk Factors
- Time Factors
- Triglycerides
- United Kingdom
19 Authors
- Haoxian Tang
- Jingtao Huang
- Xuan Zhang
- Xiaojing Chen
- Qinglong Yang
- Nan Luo
- Hanyuan Lin
- Jianan Hong
- Shiwan Wu
- Cuihong Tian
- Mengyue Lin
- Junshuang Tang
- Jiasheng Wen
- Pan Chen
- Liwen Jiang
- Youti Zhang
- Kaihong Yi
- Xuerui Tan
- Yequn Chen
1 Application
| Application ID | Title |
|---|---|
| 205837 | Integrated omics to implore risk, diagnostic, and prognostic factors of cardiovascular disease |
Enabling scientific discoveries that improve human health