Abstract
Background: The non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) plays a potential role in cardiovascular diseases. However, its association with angina pectoris remains unclear. Herein, we aimed to explore their relationship. Methods: This cross-sectional retrospective study included the 2009–2018 data from 22,562 adults diagnosed with angina pectoris, retrieved from the National Health and Nutrition Examination Survey (NHANES) database. NHHR was estimated from laboratory data, and angina pectoris diagnosis was ascertained from the NHANES questionnaire. Results: Angina pectoris risk was greater in the highest than in the lowest NHHR tertile (odds ratio [OR] = 1.61; 95% confidence interval (CI), 1.15–2.54; P = 0.006). Weighted logistic regression showed a positive association between NHHR and angina pectoris in the fully adjusted model (OR = 1.17; 95% CI, 1.07–1.28; P = 0.001). Restricted cubic spline analysis showed a linear association (P = 0.6572). Subgroup analyses indicated no significant differences across different stratifications (P > 0.05, all). Random forest analyses and Boruta algorithm corroborated that NHHR is a strong predictor of angina pectoris. Among the eight machine-learning models evaluated for predictive capabilities, the logistic regression model demonstrated the strongest predictive capability, with an area under the curve of 0.831. Conclusions: Our study suggests that NHHR is a risk factor for angina pectoris and may be used for risk prediction and to inform future intervention programs to reduce its incidence.
| Original language | English |
|---|---|
| Article number | 347 |
| Journal | Lipids in Health and Disease |
| Volume | 23 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2024 Dec |
Bibliographical note
Publisher Copyright:© The Author(s) 2024.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Angina pectoris
- Boruta algorithm
- NHANES
- NHHR
- Random forest analysis
- Restricted cubic spline model
ASJC Scopus subject areas
- Endocrinology, Diabetes and Metabolism
- Endocrinology
- Clinical Biochemistry
- Biochemistry, medical
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