Association between the atherogenic index of plasma and incident hypertension across different blood pressure states: a national cohort study

Abstract

Background: Hypertension is a major public health concern, making effective preventive strategies essential. The atherogenic index of plasma (AIP), a new lipid metabolic index that is associated with insulin resistance and cardiovascular diseases. However, the association between AIP and the incidence of hypertension remains unexplored. To address this knowledge gap, we designed a large-scale retrospective cohort study to investigate the association between AIP and the occurrence of hypertension across different blood pressure (BP) states, including individuals with normal BP and those with elevated BP.

Methods: This retrospective cohort study used data from the China Health and Retirement Longitudinal Study (CHARLS) involving participants aged 45 and older, assessed in 2011 and followed up in 2020. AIP was calculated using the logarithmic ratio of triglycerides (TG) to high-density lipoprotein cholesterol (HDL-C). Logistic regression models, restricted cubic splines models, and threshold analyses were employed to examine the relationship between AIP and the incidence of hypertension. Receiver Operating Characteristic analysis was utilized to assess the ability of AIP to predict the incidence of hypertension. Subgroup analyses were conducted across various demographic and health-related factors. Sensitivity analyses were employed to address biases arising from self-reported data.

Results: Among 6540 participants, 1909 (29.19%) developed hypertension over nine years. The AIP is an independent risk factor for the development of hypertension, with an adjusted odds ratio of 1.84 [95% confidence interval (CI) 1.41-2.39, p < 0.001] in individuals with normal BP and 1.88 (95% CI 1.40-2.52, p < 0.001) in those with elevated BP. A nonlinear relationship between AIP and the incidence of hypertension was identified in both normal BP and elevated BP population. AIP has a better predictive ability for the occurrence of hypertension compared to the single indicators of TG and HDL-C. Age significantly impacted AIP's predictive value, especially in those aged 45 to 60 in normal BP population. Sensitivity analyses further validated the nonlinear relationship between AIP and the occurrence of hypertension.

Conclusions: AIP is a significant predictor of hypertension, demonstrating a nonlinear association with its occurrence in normal BP and elevated BP population.

Trial registration: Not applicable.

Keywords: Atherogenic index of plasma; CHARLS; Elevated blood pressure; Hypertension; Risk assessment.

Fig. 1

The flowchart of this study

Fig. 2

Logistic regression models predicting the occurrence of hypertension based on atherogenic index of plasma. Model 1 (unadjusted), Model 2 (adjusted for age, gender, body mass index, smoking, and alcohol consumption), and Model 3 (further adjusted for SBP, residential area, education, daily sleep duration, and all comorbidities)

Fig. 3

Restricted cubic spline models. Restricted cubic spline models with multivariable-adjusted associations were adopted to demonstrate dose–response associations between atherogenic index of plasma and the prevalence of hypertension in all population (a), normal BP group (b) and elevated BP group (c)

Fig. 4

Receiver operating characteristic analysis comparing the predictive ability of atherogenic index of plasma (AIP), triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C) for hypertension

Fig. 5

Receiver operating characteristic analysis comparing the predictive ability of three logistic regression models

Fig. 6

Subgroup analyses of individuals with normal blood pressure were performed to investigate the relationship between the atherogenic index of plasma and hypertension across different subgroups

Fig. 7

Subgroup analyses of individuals with elevated blood pressure were performed to investigate the relationship between the atherogenic index of plasma and hypertension across different subgroups

Fig. 8

Restricted cubic spline models re-established based on the population defined by blood pressure measurements. a illustrates the total population that was re-included, while b represents the subset of individuals with normal blood pressure who were also re-included