Weight-adjusted waist index outperforms other obesity indices for cardiovascular disease prediction in cardiovascular-kidney-metabolic syndrome: insights from UK biobank.

backgroundCardiovascular-kidney-metabolic (CKM) syndrome, a systemic disorder often initiated by adipose tissue dysfunction, is an emerging concept for integrated risk assessment. Although the link between obesity and cardiovascular disease (CVD) is established, the optimal anthropometric index for predicting CVD risk across different stages of CKM syndrome remains undetermined.

methodsThis prospective cohort study utilized data of individuals with CKM syndrome in stages 0-3 from UK Biobank. Cox proportional hazards models with multi-variable adjustment were used to assess the associations of nine obesity-related indices-weight-adjusted waist index (WWI), cardiometabolic index (CMI), waist-to-height ratio (WHtR), conicity index (CI), relative fat mass (RFM), visceral adiposity index (VAI), body mass index (BMI), waist circumference (WC), and lipid accumulation product (LAP) with incident CVD risk. Potential non-linear associations were examined through restricted cubic spline (RCS) modeling. The discriminative capacity of the nine indicators was further quantified using receiver operating characteristic (ROC) analysis. Moreover, subgroup analyses and interaction tests were carried out for the indicator with the strongest predictive performance to explore its relationship with CVD risk across diverse population subgroups.

resultsA total of 13,064 participants, including 55.2% males, were enrolled in this study. During a median follow-up period of 15.4 years, 2,537 (19.42%) of them developed CVD. Multivariable Cox proportional hazards analyses revealed that WWI, CMI, WHtR, CI, RFM, VAI, and BMI were all significantly linked to an elevated risk of CVD in participants with CKM syndrome at stages 0-3. Of these indices, WWI exhibited the strongest correlation with CVD, with an adjusted hazard ratio (HR) of 1.33 and 95% confidence intervals (95% CIs) of 1.06-1.59, followed by CMI (HR: 1.27, 95% CIs: 1.08-1.51). Nonlinear thresholds were identified at CMI (1.63), WHtR (0.49), VAI (0.65) and BMI (24.88). ROC analysis demonstrated that WWI exhibited the highest discriminatory power in predicting CVD among these indices. Subgroup analyses further revealed that the association between WWI and CVD risk was most pronounced in participants under 60 years old and those with diabetes, hypercholesterolemia, or metabolic syndrome.

conclusionAmong various obesity indices, WWI showed the strongest association with incident CVD among individuals with CKM syndrome stages 0-3 and may serve as a superior simple anthropometric indicator for initial risk stratification compared with traditional measures.