Evidence Hub

Association between atherogenic index of plasma and type 2 diabetic complications: a cross-sectional study

Yue-Yang Zhang, Xiao-Yu Yang, Qin Wan

Frontiers in Endocrinology, 2025

3,094 participants · 12 citations

Abstract

Background The Atherogenic Index of Plasma (AIP) was originally developed primarily as a marker for assessing atherosclerosis. Consequently, this study investigates the potential association between AIP and type 2 diabetic complications through a cross-sectional design. Methods The National Metabolic Management Center(MMC) serves as a comprehensive platform dedicated to the establishment of standardized protocols for the diagnosis, treatment, and long-term follow-up of metabolic diseases. Following the relevant inclusion and exclusion criteria, a total of 3,094 patients were enrolled for subsequent analysis. In this study, logistic regression, restricted cubic splines, and subgroup analyses were employed to evaluate the association between the AIP and four major complications of type 2 diabetes, namely, type 2 diabetes with carotid atherosclerosis (DA), diabetic kidney disease (DKD), diabetic retinopathy (DR), and diabetic peripheral neuropathy (DPN). Results The logistic regression results demonstrate that in the fully adjusted model, each SD increase in AIP correlates with an elevated risk of type 2 diabetic kidney disease (DKD), with the risk of kidney damage intensifying alongside higher AIP groupings. The RCS analysis and subgroup analyses similarly revealed a dose-response relationship between AIP levels and the risk of DKD. Furthermore, the AIP was not found to be statistically significantly associated with DA, DR,and DPN. Conclusions The AIP may serve as a valuable…

How strong is the evidence?

Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause. Reported size: 3,094 participants or records.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free