Assessment for the associations of twenty-three metal(loid)s exposures with early cardiovascular damage among Chinese urban adults with five statistical methods: Insight into assessing health effect of multipollutant exposure. (November 2022)

• Record Type: Journal Article
• Authors: Liu, Wei; Yu, Linling; Ye, Zi; Wang, Xing; Qiu, Weihong; Tan, Qiyou; Nie, Xiuquan; Li, Minjing; Wang, Bin; Chen, Weihong
• Is Part Of: Chemosphere. Volume 307:Part 2(2022)
• Publication Date: 2022-11
• Subjects: Urinary metal(loid)s -- Mean platelet volume -- Early cardiovascular damage -- Health effect -- Multipollutant mixture exposure; cardiovascular disease (CVD) mean platelet volume (MPV) -- aluminum (Al) titanium (Ti) -- vanadium (V) chromium (Cr) -- manganese (Mn) iron (Fe) -- cobalt (Co) nickel (Ni) -- copper (Cu) zinc (Zn) -- arsenic (As) selenium (Se) -- rubidium (Rb) strontium (Sr) -- molybdenum (Mo) cadmium (Cd) -- tin (Sn) antimony (Sb) -- barium (Ba) tungsten (W) -- thallium (Tl) lead (Pb) -- uranium (U) environmental risk score (ERS) -- false discovery rate (FDR) general linear model (GLM) -- Bayesian kernel machine regression (BKMR) posterior inclusion probabilities (PIPs) -- weight quartile sum (WQS) regression quantile g-computation (QGC) -- adaptive elastic network regression (AENR) limits of quantification (LOQs) -- body mass index (BMI) confidence interval (CI); Pollution -- Periodicals; Pollution -- Physiological effect -- Periodicals; Environmental sciences -- Periodicals; Atmospheric chemistry -- Periodicals; 551.511
• DOI: 10.1016/j.chemosphere.2022.135969
• Languages: English
• ISSNs: 0045-6535

Abstract

Abstract: The topic of cardiovascular hazards from multiple metal (loid)s exposures has attracted widespread attention. Here, we measured concentrations of twenty-three urinary metal (loid)s and mean platelet volume (MPV), an early cardiovascular damage biomarker, for 3396 Chinese adults. We aimed to comprehensively assess the associations of single metal (loid) and multiple metal (loid)s (as a mixture) with MPV by combined use of five statistical methods, including general linear models, Bayesian kernel machine regression (BKMR), weight quartile sum (WQS) regression, quantile g-computation (QGC), and adaptive elastic network regression (AENR). And based on that, we hope to provide insight into assessing the health effect of multipollutant exposure. After adjustment for potential covariates, at least three methods jointly suggested that of twenty-three metal (loid)s, iron, arsenic, and antimony were positively while aluminum, tungsten, and thallium were inversely associated with MPV. The environmental risk score of metal (loid)s construed by AENR was significantly positively associated with MPV, while the association between overall twenty-three metal (loid)s mixture and MPV was neutralized to be insignificant in QGC and BKMR. Conclusively, single metal (loid) may be inversely (iron, arsenic, and antimony) and positively (aluminum, tungsten, and thallium) associated with early cardiovascular damage, while the association of overall twenty-three metal (loid)s mixture with MPV was insignificant when concurrent exposures exist. It is crucial to select appropriate statistical methods based on study purpose and principles/characteristics of statistical methods, and combined employment of multimethod is insightfully suggested when assessing health effects of multipollutant exposure. Graphical abstract: Image 1 Highlights: The effect of 23 metal (loid)s exposures on early cardiovascular damage was evaluated. Single effects, interactions, and overall effect of 23 metal (loid)s were assessed. Novel statistical methods to assess health effect of multipollutant exposure were used. Insight into assessing the health effect of multipollutant exposure was given.