Replication Data for: Association of Multiple Obesity-Related Composite Indices with All-Cause Mortality in Patients with Stage 0-3 Cardiovascular-Kidney-Metabolic Syndrome

This dataset is supplementary material for a study investigating the association between 8 obesity-related indicators and all-cause mortality risk in patients with CKD (Chronic Kidney Disease). It contains four core statistical analysis results tables, providing detailed data to support the study’s conclusions on the predictive value and risk correlation of obesity indices. 1. Scope of the Dataset The dataset includes results from four types of analyses, covering 8 obesity indicators: BMI (Body Mass Index) RFM (Relative Fat Mass) BRI (Body Roundness Index) LAP (Lipid Accumulation Product) VAI (Visceral Adiposity Index) CMI (Cardiometabolic Index) AIP (Atherogenic Index of Plasma) TYG (Triglyceride-Glucose Index) 2. Content of Each Table (1) Logistic_results Presents the association between obesity indicators and CKD mortality risk using multivariable logistic regression, with three adjustment models: Model 1: Adjusted for age and sex Model 2: Further adjusted for employment status, education level, sleep duration, systolic blood pressure (SBP), and diastolic blood pressure (DBP) Model 3: Additional adjustment for smoking and alcohol drinking status Each model provides OR (Odds Ratio), 95% CI (Confidence Interval), and p-value for each obesity indicator. (2) Delong_Test Compares the predictive performance (discriminatory ability) of the 8 obesity indicators for CKD all-cause mortality using DeLong’s test. Key metrics include: AUC (Area Under the ROC Curve) of each indicator AUC difference between paired indicators Z-statistic and p-value for significance testing 95% CI for AUC values (3) obesity_cox_results Uses Cox proportional hazards regression to analyze the cumulative mortality risk of CKD patients stratified by quartiles (Q1-Q4) of each obesity indicator. For each indicator and quartile group, it provides: HR (Hazard Ratio) 95% CI (Lower95CI, Upper95CI) p-value for risk significance (4) Subgroup analysis results Explores the robustness of BRI (the optimal predictive indicator) across 8 subgroups (stratified by sex, age, employment status, education level, smoking status, alcohol drinking status, sleep duration, and blood pressure). For each subgroup, it provides OR, 95% CI (CI_low, CI_high), and p-value for the nonlinear association between BRI and mortality risk. 3. Purpose and Usage This dataset is intended to: Enable reproducibility of the study’s statistical analyses; Provide raw data for further research on obesity and CKD mortality; Allow comparisons of predictive performance between different obesity indicators in similar populations. All data have passed quality control, with statistically significant results (p<0.05 unless specified otherwise) and complete confidence interval reporting.