The association between different lipid indices and hyperuricemia in older adults: a cross-sectional study

Lipid-derived composite indices demonstrate robust epidemiological associations with diverse metabolic and cardiovascular disorders due to their integrative nature; however, their relationship with hyperuricemia (HUA) in older adults remains unexplored. This research examines the links between six blood lipid indices and HUA in older Chinese adults and assesses their diagnostic accuracy for HUA association stratification.

A total of 3,040 older adults from two communities in Jinan were included in this cross-sectional study. Six blood lipid indices, namely, remnant cholesterol (RC), the atherogenic index of plasma (AIP), Castelli's risk index-I (CRI-I), Castelli's risk index-II (CRI-II), the lipoprotein combination index (LCI), and the atherogenic index (AI), were calculated from the physical examination data. To assess the associations between these lipid indices and HUA, multivariate logistic regression, restricted cubic spline (RCS) analysis, and subgroup analyses were performed. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic accuracy of each lipid index for the overall cohort, male participants, and female participants, with assessments using multiple metrics.

HUA was diagnosed in 484 participants. Significant positive associations were observed between all the composite lipid indices and HUA. A nonlinear association pattern between the LCI and HUA was identified through RCS analysis, whereas linear relationships were observed for the remaining indices. Subgroup analyses revealed consistent directional associations between lipid indices and HUA across all stratified groups. ROC curve analysis demonstrated that the AIP had optimal diagnostic accuracy for HUA in both the overall cohort and the female subgroup, whereas the LCI exhibited superior discriminatory performance among males.

This research revealed statistically significant associations between multiple lipid indices and HUA, with the LCI demonstrating a nonlinear relationship with HUA. The ROC analysis revealed modest diagnostic accuracy across these indices (AUC range: 58.14%-66.03%).