Data Sheet 1_Relationship between neck circumference and body composition: a cross-sectional study based on a Chinese population.docx

BackgroundObesity is a chronic metabolic disorder characterized by excessive fat accumulation, physiological dysfunction, and metabolic disturbances, closely associated with diabetes, cardiovascular diseases, and dyslipidemia. Currently, the primary indices for obesity screening include Body Mass Index (BMI), Waist Circumference (WC), and Percentage of Body Fat (PBF). However, these indices have certain limitations in practical application. Neck Circumference (NC), a novel anthropometric index, has garnered increasing attention in recent years.
ObjectiveThis study aims to assess the correlation between NC and several obesity-related metrics, including BMI, PBF, Fat Mass Index (FMI), and Visceral Fat Area (VFA). Furthermore, the reliability of NC as a diagnostic tool for obesity is evaluated.
MethodsThis study retrospectively analyzed body composition data from 8,319 Chinese young adults. For statistical analyses, IBM SPSS Statistics version 26.0 and R version 4.5.1 were used, which included multi-model fitting for verifying linear correlations, followed by Pearson correlation analysis, gender-stratified linear regression analysis, Receiver Operating Characteristic (ROC) curve analysis, calibration curve analysis, and Decision Curve Analysis (DCA). The optimal cut-off value of NC was determined using the Youden index, and its consistency with BMI-defined classification of obesity was validated using the Kappa test.
ResultsNC was significantly positively correlated with BMI, FMI, VFA, PBF (all p < 0.01), and its obesity diagnostic performance differed by gender. In females, NC’s AUC was 0.982 (vs. VFA 0.976), optimal cut-off 36.25 cm. Males had lower NC AUC (0.918) than BMI (0.979), PBF (0.985), VFA (0.954), optimal cut-off 38.95 cm (all p < 0.001). The female model showed better calibration (Brier = 0.0259 vs. 0.0648 in males). DCA confirmed NC’s obesity clinical utility across wide thresholds. Kappa testing revealed good consistency in obesity classification between NC and BMI (all p < 0.001), with higher Kappa in females (0.790) than males (0.644).
ConclusionNC correlates with key obesity indices. It is a simple, effective obesity screening tool for young females, while males require comprehensive assessment with BMI, PBF, and VFA.