Cardiovascular diabetology · 2025
Association of atherogenic index of plasma and its modified indices with stroke risk in individuals with cardiovascular-kidney-metabolic syndrome stages 0-3: a longitudinal analysis based on CHARLS.
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Wang Xiaoyan, Wen Pengfei, Liao Yun, Wu Tao, Zeng Lin, Huang Yuxing, Song Xiaomei, Xiong Zhen, Deng Lisha, Li Dingjun, Miao Shuchuan
Аннотация
BACKGROUND: The association between the atherogenic index of plasma (AIP), its modified indices (such as AIP-waist circumference [AIP-WC], AIP-waist-to-height ratio [AIP-WHtR], AIP-body mass index[AIP-BMI]), and incident stroke in individuals with cardiovascular-kidney-metabolic (CKM) stages 0-3 remains understudied. This study investigated these associations and their utility for risk stratification.
METHODS: Data from 3697 China Health and Retirement Longitudinal Study (CHARLS) participants (≥ 45 years, CKM stages 0-3) were analyzed. Baseline, cumulative, and changes in AIP and its modified indices (AIP-WC, AIP-WHtR, AIP-BMI) were calculated. Logistic regression, Delong's test, integrated discrimination improvement (IDI), weighted quantile sum (WQS) regression, and mediation analysis were used to assess associations, predictive performance, component contributions, and mediation effects.
RESULTS: Stroke occurred in 4.8% of participants. Under the fully adjusted Model 3: The third level of AIP, AIP-WHtR, AIP-WC, and AIP-BMI showed increased risks (ORs 1.58 [95% CI 1.05-2.38], 1.99 [95% CI 1.31-3.02], 1.99 [95% CI 1.31-3.02], and 1.92 [95% CI 1.26-2.92], respectively); The third level of cumulative AIP, AIP-WHtR, AIP-WC, and AIP-BMI showed elevated risks (ORs 1.79 [95% CI 1.19-2.69], 2.07 [95% CI 1.37-3.13], 2.01 [95% CI 1.33-3.04], and 1.92 [95% CI 1.27-2.89], respectively); The third category of AIP, AIP-WHtR, AIP-WC, and AIP-BMI changes showed risk increases of 2.28 (95% CI 1.46-3.55), 2.39 (95% CI 1.50-3.79), 2.56 (95% CI 1.61-4.07), and 2.22 (95% CI 1.38-3.56). Modified AIP indices (especially AIP-WHtR) demonstrated superior predictive ability than AIP alone. The association was amplified in advanced CKM (stages 2-3) but not significant in early CKM (stages 0-1). Triglycerides (TG) primarily drove the AIP-WHtR-stroke risk, which was partially mediated by estimated pulse wave velocity (ePWV) (6.48%).
CONCLUSIONS: AIP and its modified indices, especially AIP-WHtR, are significantly associated with incident stroke in CKM stages 0-3. Dynamically monitoring changes in these indices is crucial for stroke risk assessment and stratification, particularly in advanced CKM. TG primarily drives this risk, while ePWV partially mediates the AIP-WHtR-stroke link.
METHODS: Data from 3697 China Health and Retirement Longitudinal Study (CHARLS) participants (≥ 45 years, CKM stages 0-3) were analyzed. Baseline, cumulative, and changes in AIP and its modified indices (AIP-WC, AIP-WHtR, AIP-BMI) were calculated. Logistic regression, Delong's test, integrated discrimination improvement (IDI), weighted quantile sum (WQS) regression, and mediation analysis were used to assess associations, predictive performance, component contributions, and mediation effects.
RESULTS: Stroke occurred in 4.8% of participants. Under the fully adjusted Model 3: The third level of AIP, AIP-WHtR, AIP-WC, and AIP-BMI showed increased risks (ORs 1.58 [95% CI 1.05-2.38], 1.99 [95% CI 1.31-3.02], 1.99 [95% CI 1.31-3.02], and 1.92 [95% CI 1.26-2.92], respectively); The third level of cumulative AIP, AIP-WHtR, AIP-WC, and AIP-BMI showed elevated risks (ORs 1.79 [95% CI 1.19-2.69], 2.07 [95% CI 1.37-3.13], 2.01 [95% CI 1.33-3.04], and 1.92 [95% CI 1.27-2.89], respectively); The third category of AIP, AIP-WHtR, AIP-WC, and AIP-BMI changes showed risk increases of 2.28 (95% CI 1.46-3.55), 2.39 (95% CI 1.50-3.79), 2.56 (95% CI 1.61-4.07), and 2.22 (95% CI 1.38-3.56). Modified AIP indices (especially AIP-WHtR) demonstrated superior predictive ability than AIP alone. The association was amplified in advanced CKM (stages 2-3) but not significant in early CKM (stages 0-1). Triglycerides (TG) primarily drove the AIP-WHtR-stroke risk, which was partially mediated by estimated pulse wave velocity (ePWV) (6.48%).
CONCLUSIONS: AIP and its modified indices, especially AIP-WHtR, are significantly associated with incident stroke in CKM stages 0-3. Dynamically monitoring changes in these indices is crucial for stroke risk assessment and stratification, particularly in advanced CKM. TG primarily drives this risk, while ePWV partially mediates the AIP-WHtR-stroke link.