Abstract
BACKGROUND: Metabolic syndrome (MetS) represents a constellation of metabolic abnormalities. Perirenal fat is a type of visceral fat surrounding the kidneys and possesses distinct anatomical and physiological features. This study aims to investigate the association between perirenal fat volume (PrFV) and MetS in Chinese adults. METHODS: We conducted a post-hoc cross-sectional analysis within a multicenter, randomized clinical trial. Demographic information, anthropometric data and laboratory tests were obtained from the electronic data capture system. PrFV was assessed and measured by ultrasonography. Subcutaneous and visceral fat volume were quantified by abdominal MRI. Individuals were categorized according to PrFV tertiles, and Spearman correlation analysis was performed to investigate the correlation between PrFV and metabolic profiles. Adjusted multivariable regression models were employed to investigate the relationship of PrFV with MetS. The receiver operating characteristic curve was used to identify the value of PrFV for predicting MetS. RESULTS: Among 100 enrolled subjects, the median age was 50.0 (40.0-60.0) years, and 75% were male. Spearman correlation analysis revealed significant positive correlations between PrFV and total cholesterol (r = 0.24, P = 0.02), triglycerides (r = 0.32, P = 0.001), LDL-C (r = 0.21, P = 0.04), diastolic blood pressure (r = 0.24, P = 0.02), BMI (r = 0.39, P < 0.001), waist circumference (r = 0.39, P < 0.001), and uric acid (r = 0.40, P < 0.001). In the fully-adjusted multivariable regression model, individuals in the highest tertile of PrFV exhibited a higher risk of MetS (Odds ratio = 4.48, 95% Confidence interval: 1.25-17.6). The area under the curve (AUC) of PrFV for predicting MetS was higher than subcutaneous and visceral fat volume. CONCLUSION: Increased PrFV was positively associated with a higher risk of MetS in Chinese adults. Perirenal fat may serve as a surrogate marker and potential therapeutic target for MetS. CLINICAL TRIAL REGISTRATION: https://clinicaltrials.gov/, identifier NCT05049096.