Body Composition and Its Predictive Value for Metabolic Syndrome Risk in Overweight and Obese Populations

Background and objective Metabolic syndrome (MetS) is highly prevalent among overweight and obese populations, and accurate non-invasive screening is critical for clinical metabolic intervention. This study focused on overweight and obese individuals attending a weight management clinic in Northwest China. We aimed to explore the distribution characteristics of MetS risk, systematically analyze the associations of demographic characteristics, biochemical indicators, and multi-dimensional body composition parameters with MetS risk, and identify the core body composition risk factors for MetS in this population. The findings intend to establish a simple and efficient metabolic risk screening strategy, providing evidence-based references for early non-invasive screening, risk stratification, and individualized clinical intervention for MetS among overweight and obese individuals. Methods This study adopted a single-center cross-sectional design. Overweight and obese patients who presented to a weight management outpatient clinic were enrolled. Baseline demographic data, blood pressure, fasting blood glucose, triglycerides, and other biochemical indicators were collected. Meanwhile, anthropometric and body composition parameters including body mass index (BMI), body fat mass, visceral fat index, waist-to-height ratio, and waist-to-hip ratio were systematically recorded. All participants were stratified into low-, moderate-, and high-metabolic risk groups according to metabolic risk scores. Intergroup comparisons were performed to examine the correlations of clinical and body composition indicators with graded metabolic risk. Multiple linear regression analysis was applied to screen the independent influencing factors of MetS, and receiver operating characteristic (ROC) curves were constructed to evaluate the individual and combined predictive efficacy of each indicator for MetS. Results A total of 121 participants were included in the final analysis, including 8 (6.6%) in the low-risk group, 60 (49.6%) in the medium-risk group, and 53 (43.8%) in the high-risk group. Overall, 81.8% of participants had an excessive waist circumference, nearly 86% presented elevated blood pressure, and approximately 20% had impaired glucose regulation. Male sex, middle and advanced age, obesity, hypertriglyceridemia, abnormal blood pressure, and hyperglycemia were significantly associated with a higher probability of high MetS risk (all p < 0.05). Key body composition indicators, including BMI, skeletal muscle mass index, fat mass index, and visceral fat index, increased significantly with the elevation of metabolic risk grade ( p < 0.05). Grouping by BMI: 23 cases of overweight and 98 cases of obesity; grouping by BF%: 13 cases of overweight and 108 cases of obesity. Multiple linear regression analysis yielded a well-fitted model (F=19.150, p < 0.001, adjusted R²=0.454). The body composition factors influencing MetS, ranked by the absolute value of standardized regression coefficients, were BMI ( p =0.010), body fat mass ( p =0.016), waist-to-height ratio (WHtR, p =0.028), and waist-to-hip ratio (WHR, p =0.021). MetS risk was positively correlated with WHtR, WHR and BMI, while negatively correlated with body fat mass. ROC curve analysis demonstrated that triglycerides (area under the curve [AUC]=0.852), visceral fat index (AUC=0.790), and diastolic blood pressure (AUC=0.693) had significant predictive efficacy for MetS. Triglycerides exhibited a sensitivity of 100%, qualifying it as a high-efficiency screening marker. The visceral fat index showed balanced sensitivity (76.5%) and specificity (78.8%), with moderate diagnostic value and suitability for clinical metabolic risk stratification. Conclusion Overweight and obese patients attending weight management clinics in Northwest China exhibit a considerably high risk of MetS. Abnormal body composition is closely implicated in the occurrence and progression of metabolic disorders, and abdominal obesity indicators represented by body mass index, waist-to-height ratio, and waist-to-hip ratio are core risk factors for MetS in this population. Compared with traditional invasive biochemical tests, the visceral fat index obtained via multifrequency bioelectrical impedance analysis possesses unique advantages including non-invasiveness, convenient operation, and low cost. The simple screening strategy established by combining visceral fat index and triglyceride indicators enables accurate early screening and precise risk stratification of MetS among overweight and obese individuals. Although this study is a single-center cross-sectional investigation without external cohort validation, the enrolled participants were specialized clinical outpatients with strong pertinence for clinical intervention. The research findings hold significant practical value for individualized clinical metabolic intervention.