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Article Abstract

Background: Cardiovascular disease (CVD) is strongly correlated with plasma atherogenic index (AIP); however, there is limited literature exploring the association between trajectories of change in AIP and the risk of CVD. This study aimed to investigate whether changes in AIP are associated with CVD in individuals with cardiovascular-kidney-metabolic (CKM) syndrome stage 0-3.

Methods: Data were sourced from the China Health and Retirement Longitudinal Study (CHARLS), aimed to compile high-quality microdata on individuals and households aged 45 and older in China. Change in AIP from 2012 to 2015 were classified employing K-means clustering analysis. Logistic regressions were employed to assess the association between different AIP change clusters and cumulative AIP and CVD incidence. Additionally, restricted cubic spline (RCS) regression was conducted to further evaluate the underlying linear relationship between cumulative AIP and CVD. Subgroup analyses were applied to verify the influence of confounding variables on the relationship between AIP and CVD. Weighted quantile sum (WGS) regressions were utilized to offer a comprehensive assessment of the overall effect.

Results: Out of 4,525 participants, 578 (12.77%) ultimately developed CVD within three years. Compared to cluster 1, which served as the best control for AIP, the odds ratio (OR) was 1.29 (1.02-1.62) for cluster 2, 1.33 (1.04-1.71) for cluster 3 and 1.35 (0.98-1.85) for cluster 4 after adjusting for several confounding variables. Categorizing the cumulative AIP into quartiles revealed an ascending trend (P for trend = 0.014). RCS regression disclosed a linear relationship between cumulative AIP and CVD. Further subgroup analyses revealed variations in these correlations modified by gender and Hukou status. WQS regression analysis highlighted the significance of triglyceride in the pathogenesis of CVD.

Conclusions: Significant changes in AIP are independently associated with the elevated risk of CVD in adults aged > 45 with CKM syndrome stage 0-3. Monitoring long-term fluctuations in AIP may aid in the early identification of individuals at high risk for CVD.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11949822PMC
http://dx.doi.org/10.3389/fendo.2025.1540241DOI Listing

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