Association Between the Copper-to-Zinc Ratio and Cardiovascular Disease Among Chinese Adults: A China Multi-ethnic Cohort (CMEC) Study

• Published in: Cardiovascular toxicology 2024-10, Vol.24 (10), p.1005-1017
• Main Authors: Shen, Yili, Hu, Yuxin, Liu, Leilei, Zhong, Jianqin, Zhang, Yuxin, Wu, Shenyan, Chen, Cheng, Hong, Feng
• Format: Article
• Language: English
• Subjects: Adult; Aged; Asian People; Biomarkers - blood; Biomarkers - urine; Biomedical and Life Sciences; Biomedicine; Cardiology; Cardiovascular disease; Cardiovascular diseases; Cardiovascular Diseases - diagnosis; Cardiovascular Diseases - epidemiology; Cardiovascular Diseases - ethnology; Cardiovascular Diseases - urine; China - epidemiology; Copper; Copper - urine; East Asian People; Female; Heart Disease Risk Factors; Humans; Male; Middle Aged; Nomograms; Pharmacology/Toxicology; Predictive Value of Tests; Prevalence; Risk Assessment; Risk Factors; Zinc; Zinc - urine
• ISSN: 1530-7905; 1559-0259; 1559-0259
• DOI: 10.1007/s12012-024-09904-y

The impact of metal exposure on cardiovascular diseases has become an increasingly concerning topic. To date, few studies have investigated the relationship between the copper-to-zinc ratio and CVD (Cardiovascular disease). This China multi-ethnic cohort study explored the association between the copper-to-zinc ratio and CVD in Chinese adults. The study included a sample size of 9878 people. Logistic regression analysis was used to examine the correlation between urinary copper, urinary zinc, and the copper-to-zinc ratio and CVD prevalence. Restricted cubic spline (RCS) analysis was used to investigate the potential dose–response relationships among copper-to-zinc ratio, urinary copper, urinary zinc, and CVD prevalence. In addition, the least absolute shrinkage and selection operator (LASSO) regression method was used to identify significant risk factors associated with CVD, leading to the development of a nomogram. The predictive performance of the nomogram model for CVD was assessed using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). Compared with the copper-to-zinc ratio in Q1, the copper-to-zinc ratio in Q4 was associated with CVD after adjusting for all potential confounders (Model 3) (Q4, odds ratio [OR] 0.608, 95% confidence interval [CI] 0.416–0.889, P  = 0.010). After adjusting for all potential confounders (Model 3), urinary copper levels in Q4 were associated with CVD (Q4, odds ratio [OR] 0.627, 95% confidence interval [CI] 0.436–0.902, P  = 0.012). No significant difference was found between urinary zinc levels and CVD. The RCS showed a linear dose–response relationship between the copper-to-zinc ratio and CVD ( P for overall = 0.01). The nomogram based on the influencing factors examined with LASSO showed good predictive power, and the AUC was 76.3% (95% CI 73.7–78.9%). Our results suggest that there is a significant linear negative correlation between the copper-to-zinc ratio and CVD in Chinese adults and that it has good predictive value for CVD.