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Background <p>Cardiometabolic multimorbidity (CMM) poses a significant global health challenge. The atherogenic index of plasma (AIP) is a promising biomarker for cardiometabolic risk, but there is limited information on its cumulative effect on CMM and the underlying mechanisms. This study investigated the association of cumulative AIP exposure with CMM risk, and explored the mediating roles of the triglyceride glucose (TyG) index and body mass index (BMI).</p> Methods <p>This study was based on data from 5,454 participants from the China Health and Retirement Longitudinal Study (CHARLS, 2011 baseline). The participants were stratified into tertiles of cumulative AIP (cuAIP) and classified into three distinct AIP trajectory groups using k-means clustering. Associations between cuAIP levels, AIP trajectories, and CMM incidence were assessed using logistic. The relationship between cuAIP and CMM was further examined using receiver operating characteristic (ROC) curve analysis and restricted cubic splines (RCS). Structural equation modeling was used to evaluate the mediating roles of the TyG index and BMI. Finally, subgroup and sensitivity analyses were conducted to validate the results.</p> Results <p>A total of 385 CMM cases were observed during the 7-year follow-up. Cluster analysis revealed the highest CMM incidence (12.1%) in the persistently high AIP trajectory group. Logistic regression models indicated that the highest cuAIP group (OR 2.81, 95% CI: 1.95–4.14) and high AIP trajectory group (OR 2.34, 95% CI: 1.68–3.28) had the highest CMM risk, with consistent results in sensitivity analyses and most subgroups. The AUC of cuAIP for predicting CMM was 0.648, and RCS curves demonstrated increasing CMM incidence with rising cuAIP levels. Mediation analysis indicated that the TyG index and BMI mediated 74% and 26% of the total effect, respectively.</p> Conclusion <p>This study establishes AIP as an independent predictor of CMM, whereby its effect is primarily mediated by the TyG index and BMI. These findings support the implementation of integrated clinical strategies to effectively prevent CMM and its associated diseases.</p>

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Association between the cumulative atherogenic index of plasma and cardiometabolic multimorbidity: the mediating effects of the TyG index and body mass index

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月28日

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  • Qinglin He,
  • Wen Yu,
  • Xiuqin Rao,
  • Dong Lin,
  • Yueyang You,
  • Lei Yan,
  • Weidong Liang,
  • Fuzhou Hua,
  • Xilong Guan,
  • Xifeng Wang

摘要

Background

Cardiometabolic multimorbidity (CMM) poses a significant global health challenge. The atherogenic index of plasma (AIP) is a promising biomarker for cardiometabolic risk, but there is limited information on its cumulative effect on CMM and the underlying mechanisms. This study investigated the association of cumulative AIP exposure with CMM risk, and explored the mediating roles of the triglyceride glucose (TyG) index and body mass index (BMI).

Methods

This study was based on data from 5,454 participants from the China Health and Retirement Longitudinal Study (CHARLS, 2011 baseline). The participants were stratified into tertiles of cumulative AIP (cuAIP) and classified into three distinct AIP trajectory groups using k-means clustering. Associations between cuAIP levels, AIP trajectories, and CMM incidence were assessed using logistic. The relationship between cuAIP and CMM was further examined using receiver operating characteristic (ROC) curve analysis and restricted cubic splines (RCS). Structural equation modeling was used to evaluate the mediating roles of the TyG index and BMI. Finally, subgroup and sensitivity analyses were conducted to validate the results.

Results

A total of 385 CMM cases were observed during the 7-year follow-up. Cluster analysis revealed the highest CMM incidence (12.1%) in the persistently high AIP trajectory group. Logistic regression models indicated that the highest cuAIP group (OR 2.81, 95% CI: 1.95–4.14) and high AIP trajectory group (OR 2.34, 95% CI: 1.68–3.28) had the highest CMM risk, with consistent results in sensitivity analyses and most subgroups. The AUC of cuAIP for predicting CMM was 0.648, and RCS curves demonstrated increasing CMM incidence with rising cuAIP levels. Mediation analysis indicated that the TyG index and BMI mediated 74% and 26% of the total effect, respectively.

Conclusion

This study establishes AIP as an independent predictor of CMM, whereby its effect is primarily mediated by the TyG index and BMI. These findings support the implementation of integrated clinical strategies to effectively prevent CMM and its associated diseases.