Association between atherogenic index of plasma and physical dysfunction: a cross-sectional study of middle-aged and older adults in China
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background Physical dysfunction is common in older adults and increases disease risk. The atherogenic index of plasma (AIP) is a promising biomarker for this condition. This study explored the dose–response relationship between AIP and physical dysfunction. Methods Data from 11,369 CHARLS participants (aged ≥45 years) in 2015 and 2018 were analyzed using univariate and multivariate logistic regression, adjusting for demographics and lifestyle factors. The restricted cubic splines were used to examine possible non-linear associations and visualize the dose–response relationship between AIP and physical dysfunction. ROC curve analysis assessed AIP’s predictive performance, and subgroup analyses evaluated interactions. Results Each interquartile range (IQR) increase in AIP was associated with a 13.4% higher odds of physical dysfunction (adjusted OR = 1.134, 95% CI: 1.066–1.207, p < 0.001), with a dose–response threshold identified at an AIP value of approximately 0.37. Beyond this threshold, the odds of physical dysfunction increased steadily, confirming a non-linear relationship. AIP exhibited moderate predictive accuracy for physical dysfunction (AUC = 0.748, 95% CI: 0.738–0.758). Stratified analysis showed AIP was significantly linked to higher physical dysfunction risk in subgroups including those aged <65, females, married individuals, high school or college-educated, rural residents, non-smokers, and non-drinkers (p < 0.05), with no significance in other subgroups. Interaction analysis identified marital status (p = 0.035) and education level (p = 0.034) as significant effect modifiers, where subgroup differences notably altered the AIP-dysfunction association, warranting further study. Conclusion Elevated AIP is significantly associated with increased physical dysfunction risk, highlighting its potential as a simple, predictive biomarker.
Source: Frontiers in Public Health
Authors: Jianghui Zhou, Yun Chang, Hechen Shen, Meng Zhang, Yuchao Wang, Xiaoyu Liang, Wenqing Gao
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
Awards: G1339845211, G1586430575, G2830945780, G2994101842, G3197806988, G3375453983, Archiving & Creating User Friendly Data: the Longitudinal Aging Survey in India, G4630218722, G610613843, G8259476451, Integrating Information about Aging Surveys: Novel Integration of Contextual Data to Study Late-Life Cognition and Alzheimer’s Disease and Related Dementia and Dementia Care, G92978513
OpenAlex ID: W4410905799
