Status: published
Metabolic syndrome is a cluster of interrelated metabolic abnormalities that significantly increase the risk of cardiovascular disease, type 2 diabetes mellitus, and overall mortality. The syndrome is characterized by the coexistence of central obesity, insulin resistance, hypertension, elevated triglyceride levels, and reduced high-density lipoprotein (HDL) cholesterol levels. The prevalence of metabolic syndrome has risen globally due to increasing rates of obesity, sedentary lifestyles, unhealthy dietary habits, and population aging. Its pathophysiology involves complex interactions among genetic, environmental, and behavioral factors, leading to chronic low-grade inflammation and metabolic dysfunction. Early identification and management are essential to prevent long-term complications. Lifestyle modifications, including regular physical activity, weight reduction, and dietary changes, remain the cornerstone of treatment, while pharmacological interventions may be required to address specific risk factors. Understanding the epidemiology, risk factors, diagnostic criteria, and preventive strategies of metabolic syndrome is crucial for reducing its growing public health burden and improving health outcomes worldwide.
Keywords: Blood Test Analysis, Generative Artificial Intelligence (GenAI), Health Test Analytics, Metabolic Syndrome