Dataset Information

Longitudinal trajectories of atherogenic index of plasma and risks of cardiovascular diseases: results from the Korean genome and epidemiology study.

ABSTRACT:

Background

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.

Methods

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).

Results

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.

Conclusions

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.

SUBMITTER: Chun DW

PROVIDER: S-EPMC10506251 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Publications

Longitudinal trajectories of atherogenic index of plasma and risks of cardiovascular diseases: results from the Korean genome and epidemiology study.

Chun Dong-Wook DW Lee Yae-Ji YJ Lee Jun-Hyuk JH Lee Ji-Won JW

Thrombosis journal 20230918 1

<h4>Background</h4>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.<h4>Methods</h4>Data from 5,843 participants of the Korean Genome and Epidemiology Study (KoGES) were analyzed. The KoGES had b ...[more]

PMID: 37723571

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Project description:The atherogenic index of plasma (AIP), a novel composite lipid index, is closely linked to cardiovascular disease (CVD). However, lipid levels fluctuate dynamically, and it is unclear whether there are differences in the association of single-timescale, multiple-timescale, or AIP change trajectories with new-onset cardiovascular disease. Hence, the aim of this study was to investigate the correlation between different AIP parameters and the occurrence of CVD. Data were derived from the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011, 2015, 2018, and 2020, focusing on middle-aged and elderly populations aged over 45 years. Changes in AIP were classified into three groups using K-means cluster analysis: the low-level growth group (Class 1), the medium-level growth group (Class 2), and the high-level decline group (Class 3). Furthermore, participants were grouped based on tertiles (T) of cumulative AIP (Cum-AIP). Our multivariate logistic regression model integrated adjustments for potential confounders in order to investigate the association between Cum-AIP and the occurrence of CVD. Additionally, we employed restricted cubic spline (RCS) modeling to illustrate the dose-response relationship of baseline AIP, mean AIP, and Cum-AIP with CVD risk. During the 5-year follow-up period, 927 participants experienced the onset of CVD. After controlling for various potential confounding factors, it was observed that individuals in Class 2 demonstrated a notably heightened risk of CVD (OR = 1.23, 95% CI: 1.03, 1.46) and stroke (OR = 1.35, 95% CI: 1.02, 1.80) in comparison to those in Class 1. However, there was no significant difference in the risk of heart disease (OR = 1.21, 95% CI: 0.99, 1.48). In contrast, a noteworthy correlation was solely observed in the Class 3 group concerning the risk of stroke occurrence (OR = 1.60, 95% CI: 1.06, 2.42). The adjusted OR (95% CI) for CVD in the T2 and T3 groups were 1.21 (1.00, 1.46) and 1.30 (1.05, 1.62), respectively, compared to the T1 Cum-AIP group (P for trend = 0.017). Through the RCS model, we identified a positive and linear relationship between baseline AIP, mean AIP, and Cum-AIP with the incidence of CVD. However, the association between baseline AIP and CVD was weak. Sustained elevation of AIP is linked to a heightened risk of CVD in the general population. The elevated mean, and Cum-AIP levels are associated with a heightened risk of CVD. These findings indicate that AIP can serve as a valuable indicator of dyslipidemia, and continuous monitoring and early intervention targeting AIP may contribute to a further reduction in the incidence of CVD.

Project description:BackgroundDyslipidemia is a well-known risk factor for cardiovascular disease (CVD). Recently, atherogenic index of plasma (AIP) has been proposed as a novel predictive marker for CVD, and few cross sectional studies have demonstrated a relationship between AIP and coronary artery disease. The present study investigated the association between AIP and the progression of coronary artery calcification (CAC) in Korean adults without CVD.MethodsA total of 1124 participants who had undergone CAC measurement at least twice by multi-detector computed tomography (CT) at a health check-up center were enrolled. Their anthropometric measurements and various cardiovascular risk factors were assessed. AIP was defined as the base 10 logarithm of the ratio of the concentration of triglyceride (TG) to high-density lipoprotein-cholesterol (HDL-C). CAC progression was defined as either incident CAC in a CAC-free population at baseline, or an increase of ≥2.5 units between the square roots of the baseline and follow-up coronary artery calcium scores (CACS) in subjects with detectable CAC at baseline.ResultsCAC progression was observed in 290 subjects (25.8%) during the mean follow-up of 4.2 years. All subjects were stratified into three groups according to AIP. There were significant differences in cardiovascular parameters among groups at baseline. The follow-up CAC and the incidence of CAC progression increased gradually with rising AIP tertiles. In logistic regression analysis, the odds ratio for CAC progression was 2.27 when comparing the highest to the lowest tertile of AIP (95% CI: 1.61-3.19; P for trend < 0.01). However, this association was attenuated after adjustment for multiple risk factors (P for trend = 0.67).ConclusionsThere is a significant correlation between AIP and the progression of CAC in subjects without CVD. Although AIP was not an independent predictor of CAC progression, AIP should be considered when estimating the current as well as future CVD risk, along with other traditional risk factors.

Dataset Information

Longitudinal trajectories of atherogenic index of plasma and risks of cardiovascular diseases: results from the Korean genome and epidemiology study.

Background

Methods

Results

Conclusions

Publications

Longitudinal trajectories of atherogenic index of plasma and risks of cardiovascular diseases: results from the Korean genome and epidemiology study.

Similar Datasets

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