Association between the triglyceride–glucose body mass index (TyG-BMI) and hypertension risk: a systematic review and meta-analysis
Year: 2026
Type: review
Study designs: Systematic Review, Meta-Analysis
Abstract: Background Hypertension (HTN) is a major modifiable risk factor for cardiovascular disease. Insulin resistance, closely linked to adiposity and blood pressure regulation, plays an important role in the pathogenesis of HTN. The triglyceride–glucose (TyG) index combined with body mass index (BMI), known as the TyG-BMI index, has been proposed as a surrogate marker of insulin resistance and a potential indicator of HTN risk. This meta-analysis aimed to evaluate the association between TyG-BMI and HTN. Method This study was designed and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Systematic searches were conducted in Google Scholar, PubMed/Medline, and Scopus, identifying nine observational studies (three cohort and six cross-sectional) examining the association between TyG-BMI and HTN. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using random-effects models in STATA 18. Between-study heterogeneity was assessed using the I² statistic, and publication bias was evaluated using funnel plots and Egger’s regression test. Results The meta-analysis demonstrated a complex, non-linear association between TyG-BMI and HTN. Compared with the lowest TyG-BMI quartile (Q1), the pooled adjusted ORs for HTN were 0.39 (95% CI: 0.28–0.50) for Q2, 0.71 (95% CI: 0.55–0.78) for Q3, and 1.19 (95% CI: 0.97–1.40) for Q4. While moderate TyG-BMI levels were associated with significantly lower odds of HTN, the highest quartile showed a non-significant trend toward increased risk. No significant publication bias was detected. Conclusion This meta-analysis indicates that the association between TyG-BMI and hypertension is non-linear and heterogeneous. TyG-BMI should therefore be interpreted cautiously, and further large-scale prospective studies are needed to clarify its predictive value and underlying mechanisms in hypertension.
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7155057500