Association of Urinary Metals With Cardiovascular Disease Incidence and All-Cause Mortality in the Multi-Ethnic Study of Atherosclerosis (MESA)

Abstract

Background: Exposure to metals has been associated with cardiovascular disease (CVD) end points and mortality, yet prospective evidence is limited beyond arsenic, cadmium, and lead. In this study, we assessed the prospective association of urinary metals with incident CVD and all-cause mortality in a racially diverse population of US adults from MESA (the Multi-Ethnic Study of Atherosclerosis).

Methods: We included 6599 participants (mean [SD] age, 62.1 [10.2] years; 53% female) with urinary metals available at baseline (2000 to 2001) and followed through December 2019. We used Cox proportional hazards models to estimate the adjusted hazard ratio and 95% CI of CVD and all-cause mortality by baseline urinary levels of cadmium, tungsten, and uranium (nonessential metals), and cobalt, copper, and zinc (essential metals). The joint association of the 6 metals as a mixture and the corresponding 10-year survival probability was calculated using Cox Elastic-Net.

Results: During follow-up, 1162 participants developed CVD, and 1844 participants died. In models adjusted by behavioral and clinical indicators, the hazard ratios (95% CI) for incident CVD and all-cause mortality comparing the highest with the lowest quartile were, respectively: 1.25 (1.03, 1.53) and 1.68 (1.43, 1.96) for cadmium; 1.20 (1.01, 1.42) and 1.16 (1.01, 1.33) for tungsten; 1.32 (1.08, 1.62) and 1.32 (1.12, 1.56) for uranium; 1.24 (1.03, 1.48) and 1.37 (1.19, 1.58) for cobalt; 1.42 (1.18, 1.70) and 1.50 (1.29, 1.74) for copper; and 1.21 (1.01, 1.45) and 1.38 (1.20, 1.59) for zinc. A positive linear dose-response was identified for cadmium and copper with both end points. The adjusted hazard ratios (95% CI) for an interquartile range (IQR) increase in the mixture of these 6 urinary metals and the corresponding 10-year survival probability difference (95% CI) were 1.29 (1.11, 1.56) and -1.1% (-2.0, -0.05) for incident CVD and 1.66 (1.47, 1.91) and -2.0% (-2.6, -1.5) for all-cause mortality.

Conclusions: This epidemiological study in US adults indicates that urinary metal levels are associated with increased CVD risk and mortality. These findings can inform the development of novel preventive strategies to improve cardiovascular health.

Keywords: cadmium; cardiovascular disease; coronary disease; metals; mortality; urine metals biomarkers.

Figure 1.. Hazard ratios for incident cardiovascular disease (CVD) and all-cause mortality by baseline urine metal concentrations

The solid lines represent adjusted HRs based on restricted quadratic splines for the log-transformed concentration of urinary metals, knots were set at 10^th, 50^th and 90^th percentiles. The shadowed areas represent the upper and lower 95% confidence intervals. The reference was set at the 10^th percentile. To facilitate visualization the X axis of the figure was customized for cadmium (lower limit 0.06 ug/g, upper limit 15.0 ug/g, for uranium (lower limit 0.003 ug/g), cobalt (upper limit 10.0 ug/g), and copper (upper limit 60.0ug/g), although all models were run in the background including the full range of the data. Model 1 was adjusted by: age, sex (male, female), race (non-Hispanic White, Chinese, non-Hispanic Black, Hispanic/Latino), eGFR, smoking (none, former, current) and BMI. The model was stratified by study center. Model 2 was further adjusted by: systolic blood pressure, hypertension treatment (yes/no), total cholesterol, HDL-cholesterol, diabetes diagnosis (no, impaired fasting glucose, confirmed diabetes)

Figure 2.. 10-year survival probability (95% CI) per one IQR change in the baseline levels of individual urinary metals accounting for the other urinary metals at their median distribution in the Elastic Net Cox models.

The x-axis shows the urinary levels of metals. The Y-axis shows the 10 year survival probability. The curves represent probability of not having an event (either CVD or death) at 10 years by increasing levels of baseline urinary metals. Model 1 was adjusted by: age, sex (male, female), race (non-Hispanic White, Chinese, non-Hispanic Black, Hispanic/Latino), eGFR, smoking (none, former, current) and BMI. The model was stratified by study center. Model 2 was further adjusted by: systolic blood pressure, hypertension treatment (yes/no), total cholesterol, HDL-cholesterol, diabetes diagnosis (no, impaired fasting glucose, confirmed diabetes)