Composite atherogenic indices reveal a superior lipid profile in a Chinese longevity population: a cross-sectional cohort study

J Jiaqi Zhang Z Zhengkang Chen B Baihua Lu Y Yaojin Huang Y Yanzhi Yang Z Zongkui Wang C Changqing Li (School of Energy and Chemical Engineering/Center for Dimension-Controllable Organic Frameworks) R Rong Zhang (Department of Materials Science and Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong 999077, China)

Abstract

Abstract Our previous work revealed differences in conventional lipid parameters between individuals from the Bama longevity hotspot and general population controls. However, their comprehensive atherogenic risk profile, as assessed by novel composite indices, remains uncharacterized. This study aimed to perform an in-depth evaluation of key composite atherogenic indices in this unique longevity cohort. A total of 2,767 participants were enrolled, including 1,007 individuals from the Bama longevity area in Guangxi and 1,760 controls from Shimen County, Hunan. This analysis presents a novel evaluation of the Atherogenic Index of Plasma (AIP), Atherogenic Index (AI), Lipoprotein Combine Index (LCI), Remnant Cholesterol (RC), and Castelli’s Risk indices (CRI-I, CRI-II). Statistical analyses included between-group comparisons (Student’s t -test, Chi-square test) and Spearman correlation analysis. The Bama cohort demonstrated a significantly less atherogenic profile across most composite indices. Specifically, AIP, AI, LCI, RC, and CRI-I were markedly lower in Bama cohort than in Controls (all P  < 0.001; Cohen’s d ranging from − 0.23 to -1.04), whereas CRI-II did not differ significantly ( P  = 0.141). AIP, LCI and RC showed strong positive correlations with TG ( r  = 0.933, 0.882 and 0.700 respectively, all P  < 0.001). In contrast, AI and CRI-I were strongly negatively correlated with HDL-C ( r = -0.728 for both; all P  < 0.001). The Bama longevity population possesses an associated capacity to regulate lipid metabolism, which may contribute to superior control of atherogenic risk, as captured by integrative indices like AIP, AI, LCI, and RC. These composite indices represent promising sensitive biomarkers that could improve clinical cardiovascular risk assessment in longevity populations, underscoring the potential translational value of identifying favorable metabolic profile shaped by genetic and local environmental factors.

Article Details

Volume / Issue Vol. 1, Issue 1
Published June 23, 2026
ISSN 2045-2322
Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (8)

J

Jiaqi Zhang

Z

Zhengkang Chen

B

Baihua Lu

Y

Yaojin Huang

Y

Yanzhi Yang

Z

Zongkui Wang

C

Changqing Li

School of Energy and Chemical Engineering/Center for Dimension-Controllable Organic Frameworks

R

Rong Zhang

Department of Materials Science and Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong 999077, China