The atherogenic index of plasma and carotid atherosclerosis in a community population: a population-based cohort study in China

Abstract

Abstract Background The atherogenic index of plasma (AIP) is an important alternative metabolic biomarker of atherosclerosis and cardiovascular diseases. Nevertheless, the correlation between the AIP and carotid atherosclerosis is unknown among the general population. Methods A total of 52,380 community residents, aged ≥ 40 years who underwentcervical vascular ultrasound from December 2017 to December 2020 in Hunan China, were selected for retrospective analysis. The AIP was calculated as a logarithmically converted ratio of triglycerides (TG) to high-density lipoprotein-cholesterol (HDL-C). The participants were divided into AIP quartile groups (Q1-Q4). Logistic regression models and restricted cubic spline analyses were used to examine the association of the AIP with carotid atherosclerosis. Stratified analyses were applied to control for confounding factors. The incremental predictive value of the AIP was further assessed. Results After adjusting for traditional risk factors, an increased AIP was associated with a higher rate of carotid atherosclerosis (CA), increased carotid intima-media thickness (CIMT), and plaques [odds ratio, OR (95% confidence interval, CI): 1.06 (1.04, 1.08), 1.07 (1.05, 1.09), and 1.04 (1.02, 1.06) per 1-SD increase in the AIP, respectively]. Compared with those participants in the quartile 1 group, those in the quartile 4 group had a greater risk of CA [OR 1.18, 95% CI (1.12, 1.25)], increased CIMT [OR 1.20, 95% CI (1.13, 1.26)], and plaques [OR 1.13, 95% CI (1.06, 1.19)]. However, we did not observe an association between the AIP and stenosis [0.97 (0.77, 1.23), p for trend = 0.758]. Restricted cubic spline analyses also showed a cumulative increase in the risk of CA, increased CIMT, and plaques but not stenosis severity (> 50%) with an increase of the AIP. Subgroup analyses showed that a more significant association between the AIP and the prevalence of increased CA was detected in younger subjects (aged < 60 years) with a body mass index (BMI) of ≥ 24 and fewer comorbidities. Additionally, the AIP provided incremental predictive capacity over established risk factors for CA, as shown by an improvement in the net reclassification index (NRI) and integrated discrimination index (IDI) (all P < 0.05). Conclusions An elevated AIP in a community-based population is associated with a higher rate of CA. the AIP could serve as a potential biomarker for CA risk assessment.