Key result
TyG-BMI outperforms lipid indices in identifying prehypertension, linked to ~385% higher odds.
Why the study?
Prehypertension frequently associates with hidden insulin resistance and dyslipidemia, creating a need for convenient, inexpensive early screening predictors, particularly in underprivileged countries.
Does TyG-BMI improve the identification of cardiometabolic risk in prehypertensive adults compared to traditional lipid indices?
Cross-Sectional (n=110)
No
Does TyG-BMI improve the identification of cardiometabolic risk in prehypertensive adults compared to traditional lipid indices?
Odds Ratio: 4.85 (95% CI 2.23–10.55)
p-value: p=<0.001
TyG-BMI is a simple, inexpensive, and highly discriminative surrogate marker for identifying early cardiometabolic risk in prehypertensive adults, outperforming traditional lipid indices.
TyG indices may aid cardiometabolic screening in prehypertension; leaves open prospective validation before practice change.
Background Prehypertension is the initial stage of the risk pathway of CVD, which commonly associates with hidden metabolic derangements such as insulin resistance and dyslipidemia. In the clinical setting, convenient, inexpensive predictors for early screening are required, particularly in underprivileged countries. This study evaluated the discriminatory performance of TyG, TyG-BMI, and lipid-derived indices for identifying cardiometabolic risk among adults with prehypertension. Methods A cross-sectional study was carried out among 110 apparently healthy adults (70 prehypertensive and 40 normotensive) in Owo, Nigeria. Anthropometric measurements, along with biochemical assessments and blood pressure readings, were collected. The TyG index, TyG-BMI, and lipid indices were estimated. Then, comparative grouping was performed, correlation analysis was conducted, logistic regression was applied, and ROC curve analysis was performed. Results In the prehypertensive group, TyG ( p = 0.001) along with TyG-BMI ( p < 0.001) was noticeably higher compared with the control group. TyG-BMI demonstrated the strongest correlation with systolic and diastolic blood pressure parameters ( p < 0.001), whereas the other measurements were not statistically significant. Looking at the ROC results, TyG-BMI performed best in terms of discriminatory capacity (AUC = 0.861), then TyG (AUC = 0.685). Meanwhile, the lipid-related indices were less convincing, with AUC values staying below 0.50. When the variables were combined, the prediction improved slightly (AUC = 0.870). Even after the adjustments, TyG-BMI remained the main independent predictor for prehypertension (adjusted OR = 4.85, p < 0.001). Conclusion TyG-BMI showed better discrimination among the evaluated indices, and may serve as a simple surrogate marker of subjects at high cardiometabolic risk. Further validation studies are required before its routine clinical application.
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A 2026 study conducted a cross-sectional in Prehypertension (n=110). TyG-BMI vs. Normotensive adults was evaluated on Independent predictor of prehypertension (adjusted OR 4.85, 95% CI 2.23-10.55, p=<0.001). TyG-BMI demonstrated the highest discriminatory capacity for identifying prehypertension (AUC 0.861) and remained the strongest independent predictor (adjusted OR 4.85).
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