ArticleFrontiers in endocrinology2024
Evaluating atherogenic index of plasma as a predictor for metabolic syndrome: a cross-sectional analysis from Northern Taiwan.
Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Association between atherogenic index of plasma and various metabolic conditions: an umbrella review on meta-analyses.BMC cardiovascular disorders · 2025Pooled it
- Safety and Efficacy Assessment of Cannabis Plant Compared to Atorvastatin for Lipid Lowering in Diabetic and Obese Wistar Male Rats.Life (Basel, Switzerland) · 2026Article
- Impact of a Hypocaloric Diet on Prognostic Biomarkers of Endothelial Dysfunction: A Prospective Study.Journal of clinical medicine · 2026Article
- Association between cardiometabolic phenotypes with atherogenic index of plasma: a cross-sectional study from the Azar cohort population.BMC cardiovascular disorders · 2025Article
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Authors and funding
6 authors.
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Abstract
Background: The rising global prevalence of metabolic syndrome (MetS), characterized by a constellation of cardiovascular risk factors, underscores the urgent need to identify reliable predictive biomarkers. We hypothesize that an elevated atherogenic index of plasma (AIP) predicts MetS risk through lipid imbalance, but population-specific variations in its predictive strength remain unexplored. Our study aimed to assess AIP), a ratio of triglycerides to high-density lipoprotein cholesterol, as a predictor of MetS. Method: Between 2014 and 2018, our cross-sectional study collected and analyzed health examination data from 9,202 Northern Taiwan Medical Center employees without cardiovascular diseases, diabetes, and end-stage renal disease (ESRD). Our study classified AIP levels equally into three tertiles and evaluated their impact on MetS through a logistic regression model. Results: After adjusting for age, gender, BMI, SBP, FPG, and LDL in our models, the ORs for MetS in the second and third tertiles of the AIP were 3.81 (95% CI: 2.33 to 6.21; OR: 37.14, 95%: 23.22 to 59.39). In addition, women have a higher MetS risk associated with elevated AIP than men across all models. Conclusion: Our research identified the AIP as a significant predictive marker for the prevalence of MetS, suggesting its potential utility in clinical risk assessment and indicating the need for further research to explore its application in preventive strategies and therapeutic interventions.
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