Association of four Insulin Resistance Surrogate Indices and Hypertension in the MASHAD cohort study population: a cross-sectional study

Background: Insulin resistance (IR) is associated with a reduced response to insulin and an increased risk of cardiovascular disease and hypertension. The triglyceride glucose index (TyG), triglyceride to high- density lipoprotein cholesterol ratio (Tg/HDL-c), metabolic score for insulin resistance (METS-IR) and cholesterol, high-density lipoprotein, and glucose (CHG) index, are surrogate indices insulin resistance and offer a simpler approach to evaluating insulin resistance than the gold standard hyperinsulinemic-euglycemic glucose clamp technique. With the rising prevalence of metabolic syndrome and hypertension, we aimed to investigate the relationship between hypertension and IR in a large Iranian population. Method: The study cohort comprised 9438 individuals aged 35 to 65 years, who were recruited cross-sectionally from the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) cohort study. Hypertension was defined as a blood pressure reading exceeding 140/90 mmHg or the use of anti-hypertensive medications. Multivariate logistic regression analysis, receiver operating characteristic area under the curve (ROC-AUC) analysis, net reclassification index (NRI) and integrated discrimination improvement index (IDI) for incremental classification performance, restricted cubic splines (RCS), threshold effect analysis, subgroup analysis, and Poisson regression with robust variance to estimate the prevalence ratios, were employed in the statistical evaluation. Results: A total of 9438 adults were analyzed, with 2943 individuals identified as having hypertension. Spearman’s correlation coefficients indicated that all four IR indices exhibited a significantly positive correlation with both systolic and diastolic blood pressures. In multivariate analysis, after full adjustment, each 1 unit increase corresponded to 37.5% higher risk of hypertension for TyG (OR: 1.375, 95%CI: 1.256–1.505, p < 0.001), 2.8% for Tg/HDL-c (OR: 1.028, 95%CI: 1.010–1.046, p = 0.002), 3.2% for METS-IR (OR: 1.032, 95%CI: 1.022–1.042, p < 0.001), and 25.5% for CHG (OR: 1.255, 95%CI: 1.073–1.467, p = 0.004). Analysis of the ROC curve indicated that each of the four metabolic indices demonstrated a significant capacity to predict hypertension (all p < 0.001). The METS-IR index showed the highest discriminative performance among the indices, achieving an AUC of 0.642 (95%CI: 0.630–0.654). We investigated whether adding IR surrogate indices to Model 3 could improve hypertension detection. The TyG index had the highest incremental classification values (NRI: 13.58, 95%CI: [8.65–18.35]; IDI: 0.956, 95%CI: [0.834–1.079]). RCS analysis revealed a nonlinear relationship between TyG, Tg/HDL-c, and CHG with hypertension, while a linear relationship was observed between METS-IR and hypertension. Threshold effect analysis for the indices with non-linear relation with hypertension showed that these associations were strongest at lower index values and then flattened, and often lose statistical significance. The findings were consistent across various subgroups, although the effects appeared to be more pronounced in participants who did not have dyslipidemia across all indices. A sensitivity analysis employing Poisson models with robust variance validated the direction and ranking of effects, revealing smaller prevalence ratios compared to odds ratios. Conclusion: Surrogate IR indices showed a significant relationship with hypertension. They may serve as a viable option for efficiently stratifying risk in the primary prevention of hypertension.