Although the atherogenic index of plasma (AIP) based on a single measurement is a known risk factor for cardiovascular disease (CVD), little is known about whether changes in AIP over time are related to incident CVD. We aimed to determine whether AIP trajectory, which reflects homogenous AIP trends for a particular period, is associated with CVD risk. Data from 5,843 participants of the Korean Genome and Epidemiology Study (KoGES) were analyzed. The KoGES had been conducted biennially from the baseline survey (2001–2002) to the eighth follow-up survey (2017–2018). The research design specifies the exposure period from baseline to the third follow-up, designates the latent period at the fourth follow-up, and establishes the event accrual period from the fifth to the eighth follow-up. During the exposure period, we identified two trajectories: a decreasing (n = 3,036) and an increasing group (n = 2,807) using latent variable mixture modeling. Information on CVD was collected initially through the self-reporting, followed by in depth person-to-person interview conducted by a well-trained examiner. During the event accrual period, the cumulative incidence rates of CVD between the two AIP trajectory groups were estimated using Kaplan–Meier analysis with the log-rank test. Multiple Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). The increasing AIP trajectory group had a significantly higher cumulative incidence rate of CVD than the decreasing AIP trajectory group. Compared to the decreasing AIP trajectory group, the increasing AIP trajectory group had a higher risk of incident CVD (HR: 1.31, 95% CI: 1.02–1.69) after adjusting for confounders. The risk of incident CVD increased when the AIP level showed an increasing trend and remained high over a long period. This suggests that checking and managing the trajectory of the AIP can be a preventive strategy for incident CVD.

中文翻译：

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血浆动脉粥样硬化指数的纵向轨迹和心血管疾病的风险：韩国基因组和流行病学研究的结果

尽管基于单次测量的血浆致动脉粥样硬化指数 (AIP) 是心血管疾病 (CVD) 的已知危险因素，但对于 AIP 随时间的变化是否与 CVD 事件有关，人们知之甚少。我们的目的是确定 AIP 轨迹（反映特定时期的同质 AIP 趋势）是否与 CVD 风险相关。对韩国基因组和流行病学研究 (KoGES) 5,843 名参与者的数据进行了分析。KoGES从基线调查（2001-2002年）到第八次后续调查（2017-2018年）每两年进行一次。研究设计指定了从基线到第三次随访的暴露期，指定了第四次随访的潜伏期，并建立了从第五次到第八次随访的事件累积期。在暴露期间，我们使用潜在变量混合模型确定了两个轨迹：减少组（n = 3,036）和增加组（n = 2,807）。有关CVD的信息最初是通过自我报告收集的，然后由训练有素的检查员进行深入的面对面访谈。在事件应计期间，使用 Kaplan-Meier 分析和对数秩检验估计两个 AIP 轨迹组之间的 CVD 累积发病率。使用多个 Cox 比例风险模型来估计风险比 (HR) 和 95% 置信区间 (CI)。AIP 轨迹增加组的 CVD 累积发病率显着高于 AIP 轨迹减少组。与 AIP 轨迹减少组相比，AIP 轨迹增加组在调整混杂因素后发生 CVD 的风险更高（HR：1.31，95% CI：1.02-1.69）。当AIP水平呈上升趋势并长期保持在高位时，发生CVD的风险就会增加。这表明检查和管理 AIP 的轨迹可以成为 CVD 事件的预防策略。