| Keywords [eng] |
Kūno masės indeksas, metabolinis sindromas, C reaktyvusis baltymas, kairiojo skilvelio hipertrofija, fenotipai, centrinis (pilvinis) nutukimas. Body mass index, metabolic syndrome, C-reactive protein, left ventricular hypertrophy, phenotypes, central obesity. |
| Abstract [eng] |
Background and Aims: Body mass index (BMI) is widely used to assess cardiometabolic risk, however, it does not fully capture its heterogeneity. This study aims to examine cardiometabolic risk across obese and non-obese individuals, focusing on how anthropometric measures, metabolic markers, and systemic inflammation interact to influence cardiometabolic risk. Methods: This cross-sectional analysis included 9,891 adults from the Lithuanian High Cardiovascular Risk Program (mean age 53.5 ± 6.5 years). Participants underwent standardized anthropometric, biochemical, and echocardiographic assessments. Multivariable regression models examined predictors of cardiometabolic outcomes. Unsupervised k-means clustering identified cardiometabolic phenotypes based on adiposity, metabolic, and inflammatory parameters. Results: Of participants, 61.5% were obese. Compared with non-obese individuals, obese participants had higher waist circumference, systolic blood pressure, fasting glucose, triglycerides, and high-sensitivity C-reactive protein (hsCRP), and lower high-density lipoprotein cholesterol (all p<0.001). Log-transformed hsCRP independently predicted fasting glucose among obese individuals (β=0.105, p<0.001) but not in non-obese participants, with significant interaction (β=0.126, p<0.001). Metabolic syndrome was prevalent in both obese (89.7%) and non-obese (76.2%) groups. LVH was present in 45.1% overall and 38.5% of non-obese individuals. Waist circumference (OR 1.01 per cm, 95% CI 1.01–1.02) and systolic blood pressure (OR 1.01 per mmHg, 95% CI 1.01–1.02) were the strongest independent predictors of left ventricular hypertrophy (LVH). Clustering identified four phenotypes, including an inflamed high-triglyceride group characterized by moderate BMI with elevated triglycerides and hsCRP. Conclusions: Cardiometabolic risk extends beyond BMI-defined obesity. Inflammation was more strongly associated with metabolic dysfunction in obese individuals, while central adiposity and blood pressure independently predicted LVH irrespective of BMI. These findings suggest that routine incorporation of waist circumference and inflammatory profiling into cardiometabolic risk assessment may identify high-risk individuals overlooked by BMI-based classification. |
