Prediction of cardiovascular disease risk by serum zinc and copper concentrations and anthropometric measurements

Abstract

Introduction: We aimed to investigate the association between cardiovascular disease (CVD) and various anthropometric indices, as well as the serum levels of copper (Cu) and zinc (Zn), copper-zinc ratio (Cu/Zn ratio) and zinc-copper ratio (Zn/Cu ratio), in a large population sample from northeastern Iranian.

Method: 9704 individuals aged 35 to 65 were enrolled in the first phase of the study. After a 10-year follow-up, 7560 participants were enrolled into the second phase. The variables used in this study included demographic characteristics, such as gender and age; biochemical parameters including: serum Zn, Cu, Cu/Zn ratio, and Zn/Cu ratio; anthropometric parameters including: waist circumference (WC), body mass index (BMI), and waist-to-hip ratio (WHR). The relationship between the aforementioned indices and CVD was examined using decision tree (DT) and logistic regression (LR) models.

Results: A total of 837 individuals were diagnosed with CVD among the 7560 participants. LR analysis showed that BMI, age, WH zinc-copper ratio (Zn/Cu ratio), and serum Zn/Cu ratio were significantly associated the development of CVD in men, and WHR, age, BMI, serum Cu, and Cu/Zn ratio in women. DT analysis showed that, age was the most important predictor of CVD in both genders. 71% of women, older than 49 years, with a WHR≥ 0.89, serum Cu< 75 (µg/dl), BMI≥ 22.93 (kg/m²), and serum Cu≥ 14 (µg/dl), had the highest risk of CVD. In men, among those who were ≥ 53 years, with a WHR≥ 0.98, serum Zn/Cu ratio< 1.69, and BMI≥ 22.30, had the highest risk of CVD.

Conclusion: Among Iranian adult population, BMI, age, and WHR were one of the predictors of CVD for both genders. The Zn/Cu ratio was CVD predictor for men while Cu/Zn ratio was CVD predictor for women.

Keywords: Copper-zinc ratio; Machine learning; Waist-to-hip ratio; Zinc-copper ratio.