Association between cumulative lipid indices and risk of cardiometabolic multimorbidity: findings from two independent longitudinal population cohorts

Abstract

Cardiometabolic multimorbidity (CMM) is a major public health burden, with lipid metabolism disorders closely linked to its onset. Existing studies focus mostly on single lipid indicators, leaving the predictive value of cumulative composite lipid indices under-explored. We enrolled 4,782 CHARLS and 2,074 ELSA participants. Four cumulative lipid indices were calculated. We adopted logistic regression, RCS and ROC analyses, plus subgroup and sensitivity tests in CHARLS to explore links with incident CMM. Restricted cubic spline analyses revealed heterogeneous dose–response patterns between four cumulative lipid indices and incident CMM across two cohorts. Some indices presented significant nonlinear associations while others followed approximate linear trends. In ELSA, quartile analyses found positive associations of cumLAP, cumRCII and cumCHG with CMM risk, while cumLCI was significant only in categorical analysis. cumLAP was the strongest predictor, with fully adjusted ORs of 3.18 (95% CI: 2.48–4.10) and 2.81 (95% CI: 1.67–4.88) in the two cohorts. Its AUC values across three models were 0.632, 0.659, 0.712 (CHARLS) and 0.635, 0.673, 0.729 (ELSA), higher than other indices. Subgroup analyses in the CHARLS cohort demonstrated that the associations of cumLCI and cumRCII with incident CMM were significantly modified by smoking status, age ≥65 years and BMI >25, while cumLAP and cumCHG exhibited consistent predictive effects without subgroup interaction. This study demonstrates the associations of time-cumulative values of four composite lipid indices with cardiometabolic multimorbidity (CMM). Participants with elevated cumLAP are at particularly high risk of CMM and may require long-term monitoring and targeted management.