Cumulative residual cholesterol predicts the risk of cardiovascular disease in the general population aged 45 years and older

• Published in: Lipids in health and disease 2024-01, Vol.23 (1), p.19-19, Article 19
• Main Authors: Zhao, Mengjie, Xiao, Mengli, Tan, Qin, Ji, Jinjin, Lu, Fang
• Format: Article
• Language: English
• Subjects: Cardiovascular disease; Cardiovascular diseases; Cardiovascular Diseases - epidemiology; CHARLS; Cholesterol; Cholesterol, HDL; Cholesterol, LDL; Clustering; Datasets; Diabetes; Education; Health aspects; Heart; High density lipoprotein; Humans; Hypertension; Incidence; K-means clustering; Lipids; Lipoproteins; Low density lipoprotein; Male; Measurement; Metabolic disorders; Middle aged persons; Missing data; Morbidity; Nonlinear systems; Population; Questionnaires; Regression analysis; Residual cholesterol; Risk Factors; Trends; Weighted quantile sum
• ISSN: 1476-511X; 1476-511X
• DOI: 10.1186/s12944-023-02000-0

Numerous studies have affirmed a robust correlation between residual cholesterol (RC) and the occurrence of cardiovascular disease (CVD). However, the current body of literature fails to adequately address the link between alterations in RC and the occurrence of CVD. Existing studies have focused mainly on individual RC values. Hence, the primary objective of this study is to elucidate the association between the cumulative RC (Cum-RC) and the morbidity of CVD. The changes in RC were categorized into a high-level fast-growth group (Class 1) and a low-level slow-growth group (Class 2) by K-means cluster analysis. To investigate the relationship between combined exposure to multiple lipids and CVD risk, a weighted quantile sum (WQS) regression analysis was employed. This analysis involved the calculation of weights for total cholesterol (TC), low-density lipoprotein (LDL), and high-density lipoprotein (HDL), which were used to effectively elucidate the RC. Among the cohort of 5,372 research participants, a considerable proportion of 45.94% consisted of males, with a median age of 58. In the three years of follow-up, 669 participants (12.45%) had CVD. Logistic regression analysis revealed that Class 2 individuals had a significantly reduced risk of developing CVD compared to Class 1. The probability of having CVD increased by 13% for every 1-unit increase in the Cum-RC according to the analysis of continuous variables. The restricted cubic spline (RCS) analysis showed that Cum-RC and CVD risk were linearly related (P for nonlinearity = 0.679). The WQS regression results showed a nonsignificant trend toward an association between the WQS index and CVD incidence but an overall positive trend, with the greatest contribution from TC (weight = 0.652), followed by LDL (weight = 0.348). Cum-RC was positively and strongly related to CVD risk, suggesting that in addition to focusing on traditional lipid markers, early intervention in patients with increased RC may further reduce the incidence of CVD.