Exposure to Metal Mixtures in Association with Cardiovascular Risk Factors and Outcomes: A Scoping Review

Abstract

Since the National Institute of Environmental Health Sciences (NIEHS) declared conducting combined exposure research as a priority area, literature on chemical mixtures has grown dramatically. However, a systematic evaluation of the current literature investigating the impacts of metal mixtures on cardiovascular disease (CVD) risk factors and outcomes has thus far not been performed. This scoping review aims to summarize published epidemiology literature on the cardiotoxicity of exposure to multiple metals. We performed systematic searches of MEDLINE (PubMed), Scopus, and Web of Science to identify peer-reviewed studies employing statistical mixture analysis methods to evaluate the impact of metal mixtures on CVD risk factors and outcomes among nonoccupationally exposed populations. The search was limited to papers published on or after 1998, when the first dedicated funding for mixtures research was granted by NIEHS, through 1 October 2021. Twenty-nine original research studies were identified for review. A notable increase in relevant mixtures publications was observed starting in 2019. The majority of eligible studies were conducted in the United States (n = 10) and China (n = 9). Sample sizes ranged from 127 to 10,818. Many of the included studies were cross-sectional in design. Four primary focus areas included: (i) blood pressure and/or diagnosis of hypertension (n = 15), (ii) risk of preeclampsia (n = 3), (iii) dyslipidemia and/or serum lipid markers (n = 5), and (iv) CVD outcomes, including stroke incidence or coronary heart disease (n = 8). The most frequently investigated metals included cadmium, lead, arsenic, and cobalt, which were typically measured in blood (n = 15). The most commonly utilized multipollutant analysis approaches were Bayesian kernel machine regression (BKMR), weighted quantile sum regression (WQSR), and principal component analysis (PCA). To our knowledge, this is the first scoping review to assess exposure to metal mixtures in relation to CVD risk factors and outcomes. Recommendations for future studies evaluating the associations of exposure to metal mixtures with risk of CVDs and related risk factors include extending environmental mixtures epidemiologic studies to populations with wider metals exposure ranges, including other CVD risk factors or outcomes outside hypertension or dyslipidemia, using repeated measurement of metals to detect windows of susceptibility, and further examining the impacts of potential effect modifiers and confounding factors, such as fish and seafood intake.

Single and Combined Associations of Plasma and Urine Essential Trace Elements (Zn, Cu, Se, and Mn) with Cardiovascular Risk Factors in a Mediterranean Population

“…However, quantile-based g-computation has more advantages, including that does not require a directional homogeneity assumption that all exposures have an effect in the same direction, as modeled in other approaches [ 102 ]. Although in the last two years a number of studies employing this approach for the combined analysis of exposure to trace elements have been published [ 98 , 99 , 100 , 117 , 118 , 169 ], its use is still limited, and there are few published relationships with cardiovascular risk variables to which we can compare our findings. The results of our study’s combined analysis of trace element biomarkers in plasma using quantile-based g-computation were very enlightening.…”

“…Moreover, the majority of previous research has concentrated on the analysis of trace element associations in isolation. However, it is known that the effect of these trace elements can be joint, enhancing or inhibiting each other [ 95 , 96 , 98 , 99 ], which is why statistical analyses of association taking into account the combinations of these elements have recently been recommended [ 101 , 102 ]. Several methodological approaches have been proposed for this, and it is advised to utilize a combination of them because there is no consensus regarding the most successful [ 99 ].…”

“…However, it is known that the effect of these trace elements can be joint, enhancing or inhibiting each other [ 95 , 96 , 98 , 99 ], which is why statistical analyses of association taking into account the combinations of these elements have recently been recommended [ 101 , 102 ]. Several methodological approaches have been proposed for this, and it is advised to utilize a combination of them because there is no consensus regarding the most successful [ 99 ]. A number of more traditional investigations have employed principal component analysis [ 110 ] for investigating the combined effect of trace elements.…”

“…Second, we explored the combined association between trace elements and cardiovascular risk factors. As there is currently no consensus on the optimal statistical method for mixtures [ 99 , 102 ], we used 3 approaches to compare results: (a) principal component analysis, (b) quantile-based g-computation, and (c) calculation of the so-called TERS. (a) We performed a factor analysis on the plasma or/and urine trace elements (Zn, Cu, Se, Mn) to determine the latent multidimensionality by identifying a potentially smaller number of unobserved (latent) variables termed factors.…”

“…The majority of published studies have concentrated on trace element analyses separately. However, the significance of analyzing several combined trace elements in what is known as “mixture” analysis has been emphasized because the concentration of one element can influence the effects of the other [ 96 , 97 , 98 , 99 , 100 ]. Accordingly, current recommendations insist on conducting these combined analyses using novel statistical methodologies [ 101 , 102 , 103 ].…”