Insulin Resistance Bio-Anthropometric Markers Predict Hypertension Control in Individuals Without Diabetes

Abstract Background and Aim Insulin resistance (IR), often associated with visceral adiposity, contributes to the development of dyslipidemia and hypertension through various mechanisms. IR bio-anthropometric indices, such as triglyceride-to-high-density lipoprotein cholesterol ratio (TG/HDL-C), triglyceride-glucose index (TyGi), TyGi-Body mass index (TyGi-BMI), TyGi-Waist circumference (TyGi-WC), lipid accumulation product (LAP), visceral adiposity index (VAI), and metabolic score for insulin resistance (METS-IR), correlate with hypertension risk and poor blood pressure control when assessed via office blood pressure (OBP). However, their associations with 24-hour ambulatory BP (ABP) and antihypertensive therapy remain unclear. This study examines the relationships between IR indices and ABP in outpatients without diabetes. Methods This cross-sectional study included 1,336 outpatients undergoing ABP monitoring. IR indices were calculated, and antihypertensive therapy was assessed by medication count and treatment intensity score (TIS). After log-transformation and centering of the IR indexes, logistic regression models analysed associations between IR and uncontrolled 24-hour ABP. Following a likelihood ratio test, restricted cubic spline (RCS) analyses were performed to model the non-linear relationship between the IR indexes and the odds of uncontrolled 24-hour blood pressure (BP). Results The cohort (mean age: 54.9 years, 58.3% male, mean BMI: 27.4 kg/m²) showed median values of TG/HDL-C 2.07, TyGi-BMI 234.9, TyGi-WC 832.8, LAP 41.4, VAI 71.3, and METS-IR 41. Uncontrolled ABP (64.2%) was more prevalent in younger males with higher IR indices. METS-IR and TyGi-BMI were independently associated with uncontrolled ABP. Conclusions METS-IR and TyGi-BMI were associated with uncontrolled ABP, independently of treatment status, sex, and age. These indices, derived from widely available parameters, provide practical tools for identifying patients with an increased risk of hypertension in real-life clinical settings.