The combined effects of cardiometabolic index and high sensitivity C-reactive protein on cardiometabolic multimorbidity risk: a prospective analysis based on CHARLS

Both the cardiometabolic index (CMI), which integrates measures of body fat and lipids, and high sensitivity C-reactive protein (hs-CRP), a systemic inflammatory marker, are connected to cardiometabolic risk. The established role of hs-CRP in cardiometabolic multimorbidity (CMM) is clear, but the distinct influence of CMI and its potential interaction with hs-CRP on CMM risk is still uncertain. This research examined whether CMI and hs-CRP, alone and together, predict incident CMM among an older Chinese demographic. This research consisted of 6522 adults selected from the China Health and Retirement Longitudinal Study (CHARLS) cohort. Then, cox regression assessed how CMI and hs-CRP, separately and jointly, relate to CMM risk. Additive and multiplicative interactions were examined to evaluate potential synergy. Reclassification and discrimination analyses were performed to determine the extra predictive utility of both biomarkers. During follow-up, 515 incident CMM cases (7.90%) were identified. In the completely adjusted model, CMM risk was notably higher in the top CMI quartile versus the bottom quartile (HR = 2.71, 95% CI: 2.02–3.63), and among participants with hs-CRP ≥ 3 mg/L versus those with levels < 1 mg/L (HR = 1.89, 95% CI: 1.50–2.39) (both P < 0.001). Risk peaked with concurrent elevation of both biomarkers (HR = 2.96, 95% CI: 2.16–4.07; P < 0.001). On an additive scale, a significant synergistic effect was identified between CMI and hs-CRP (relative excess risk due to interaction [RERI] = 0.70). The combination of both biomarkers improved risk stratification over either biomarker alone (integrated discrimination improvement [IDI] = 0.003, net reclassification index [NRI] = 0.171). Increased levels of CMI and hs-CRP, whether independently or combined, forecast a greater likelihood of CMM in the elderly Chinese demographic. Their additive synergistic effect and incremental predictive value suggest that these readily accessible biomarkers could enhance early screening for high-risk individuals. This integrated approach may inform targeted preventive strategies and improve health management in aging populations.