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

Associations of personal PM2.5-bound heavy metals and heavy metal mixture with lung function: Results from a panel study in Chinese urban residents

BACKGROUND

There are a few reports on the associations between fine particulate matter (PM2.5)-bound heavy metals and lung function.

OBJECTIVES

To evaluate the associations of single and mixed PM2.5-bound heavy metals with lung function.

METHODS

This study included 316 observations of 224 Chinese adults from the Wuhan-Zhuhai cohort over two study periods, and measured participants' personal PM2.5-bound heavy metals and lung function. Three linear mixed models, including the single constituent model, the PM2.5-adjusted constituent model, and the constituent residual model were used to evaluate the association between single metal and lung function. Mixed exposure models including Bayesian kernel machine regression (BKMR) model, weighted quantile sum (WQS) model, and Explainable Machine Learning model were used to assess the relationship between PM2.5-bound heavy metal mixtures and lung function.

RESULTS

In the single exposure analyses, significant negative associations of PM2.5-bound lead, antimony, and cadmium with peak expiratory flow (PEF) were observed. In the mixed exposure analyses, significant decreases in forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC), maximal mid-expiratory flow (MMF), and forced expiratory flow at 75% of the pulmonary volume (FEF75) were associated with the increased PM2.5-bound heavy metal mixture. The BKMR models suggested negative associations of PM2.5-bound lead and antimony with lung function. In addition, PM2.5-bound copper was positively associated with FEV1/FVC, MMF, and FEF75. The Explainable Machine Learning models suggested that FEV1/FVC, MMF, and FEF75 decreased with the elevated PM2.5-bound lead, manganese, and vanadium, and increased with the elevated PM2.5-bound copper.

CONCLUSIONS

The negative relationships were detected between PM2.5-bound heavy metal mixture and FEV1/FVC, MMF, as well as FEF75. Among the PM2.5-bound heavy metal mixture, PM2.5-bound lead, antimony, manganese, and vanadium were negatively associated with FEV1/FVC, MMF, and FEF75, while PM2.5-bound copper was positively associated with FEV1/FVC, MMF, and FEF75.

Combined exposure to multiple metals on abdominal aortic calcification: results from the NHANES study

Exposure to metals increases the risk of many diseases and has become a public health concern. However, few studies have focused on the effect of metal on abdominal aortic calcification (AAC), especially the combined effects of metal mixtures. In this study, we aim to investigate the combined effect of metals on AAC risk and determine the key components in the multiple metals. We tried to investigate the relationship between multiple metal exposure and AAC risk. Fourteen urinary metals were analyzed with five statistical models as follows: generalized linear regression, weighted quantile sum regression (WQS), quantile g-computation (Qgcomp), and Bayesian kernel machine regression (BKMR) models. A total of 838 participants were involved, of whom 241 (28.8%) had AAC. After adjusting for covariates, in multiple metal exposure logistic regression, cadmium (Cd) (OR = 1.364, 95% CI = 1.035-1.797) was positively associated with AAC risk, while cobalt (Co) (OR = 0.631, 95% CI = 0.438-0.908) was negatively associated with AAC risk. A significant positive effect between multiple metal exposure and AAC risk was observed in WQS (OR = 2.090; 95% CI = 1.280-3.420, P < 0.01), Qgcomp (OR = 1.522, 95% CI = 1.012-2.290, P < 0.05), and BKMR models. It was found that the positive association may be driven primarily by Cd, lead (Pb), uranium (U), and tungsten (W). Subgroups analysis showed the association was more significant in participants with BMI ≥ 25 kg/m2, abdominal obesity, drinking, and smoking. Our study shows that exposure to multiple metals increases the risk of AAC in adults aged ≥ 40 years in the USA and that Cd, Pb, U, and W are the main contributors. The association is stronger in participants who are obese, smoker, or drinker.

Mixture effects of trace element levels on cardiovascular diseases and type 2 diabetes risk in adults using G-computation analysis

There is an increasing concern about the health effects of exposure to a mixture of pollutants. This study aimed to evaluate the associations between serum levels of heavy/essential metals ([Arsenic (As), Cadmium (Cd), Mercury (Hg), Lead (Pb), Nickel (Ni), Chromium (Cr), Copper (Cu), Iron (Fe), and Zinc (Zn)]) and the risk of developing cardiovascular diseases (CVDs) and type 2 diabetes mellitus (T2D). Data were collected from 450 participants (150 with CVDs, 150 with T2D, and 150 healthy subjects) randomly selected from the Ravansar Non-Communicable Disease (RaNCD) cohort in Western Iran, covering the years 2018-2023. Trace element levels in the serum samples were assayed using ICP-MS. Logistic regression was performed to estimate the adjusted risk of exposure to single and multi-metals and CVD/T2D. Odds ratios were adjusted for age, sex, education, residential areas, hypertension, and BMI. The mixture effect of exposure to multi-metals and CVD/T2D was obtained using Quantile G-computation (QGC). In the logistic regression model, chromium, nickel, and zinc levels were associated with CVD, and significant trends were observed for these chemical quartiles (P < 0.001). Arsenic, chromium, and copper levels were also associated with T2D. The weight quartile sum (WQS) index was significantly associated with both CVD (OR 4.17, 95% CI 2.16-7.69) and T2D (OR 11.96, 95% CI 5.65-18.26). Cd, Pb, and Ni were the most heavily weighed chemicals in these models.The Cd had the highest weight among the metals in the CVD model (weighted at 0.78), followed by Hg weighted at 0.197. For T2D, the serum Pb (weighted at 0.32), Ni (weighted at 0.19), Cr (weighted at 0.17), and Cd (weighted at 0.14) were the most weighted in the G-computation model. The results showed the significant role of toxic and essential elements in CVDs and T2D risk. This association may be driven primarily by cadmium and mercury for CVDs and Pb, Ni, Cr, and Cd for T2D, respectively. Prospective studies with higher sample sizes are necessary to confirm or refute our preliminary results as well as to determine other important elements.

Associations of mixed urinary metals exposure with metabolic syndrome in the US adult population

BACKGROUND

Metals are harmful to human health in many ways. However, the association between metals and metabolic syndrome (MetS) remains unclear. Aims of this study is to discuss the relationship between urinary metal and MetS.

METHODS

This study included 3419 adult participants from the National Health and Nutrition Examination Survey (NHANES) (2005-2018). Logistic regression analysis, Bayesian kernel machine regression (BKMR), weighted quantile sum (WQS), and restricted cubic spline (RCS) were used to explore the associations of nine urinary metal and MetS.

RESULTS

BKMR and WQS showed the effects of combined nine urinary metal were negatively correlated with MetS. Logistic regression analysis, WQS, and BKMR all suggested that cesium (Cs) and lead (Pb) were negatively correlated with MetS (all PFDCR <0.05). And RCS suggested log2-transformed Cs (χ2 = 20, P < 0.001) and log2-transformed Pb (χ2 = 19.9, P < 0.001) were negatively and linearly associated with MetS.

CONCLUSION

Existing evidence suggests that urine metal content is related to MetS. Cs and Pb are negatively related to MetS. It is still necessary to study and further discuss the causal relationship and mechanism.

Association of exposures to serum terpenes with the prevalence of dyslipidemia: a population-based analysis

This study sought to examine hitherto unresearched relationships between serum terpenes and the prevalence of dyslipidemia. Serum terpenes such as limonene, α-pinene, and β-pinene from the 2013-2014 National Health and Nutrition Examination Survey (NHANES) were used as independent variables in this cross-sectional study. Continuous lipid variables included total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), non-HDL-C, triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), residual cholesterol (RC), and apolipoprotein B (Apo B). Binary lipid variables (elevated TC, ≥5.18 mmol/L; lowered HDL-C, <1.04 mmol/L in men, and <1.30 mmol/L in women; elevated non-HDL-C, ≥4.2 mmol/L; elevated TG, ≥1.7 mmol/L; elevated LDL-C, ≥3.37 mmol/L; elevated RC, ≥1.0 mmol/L; and elevated Apo B, ≥1.3 g/L) suggest dyslipidemia. The relationships between the mixture of serum terpenes with lipid variables were investigated using weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR). The study for TC, HDL-C, and non-HDL-C included a total of 1,528 people, whereas the analysis for TG, LDL-C, RC, and Apo B comprised 714 participants. The mean age of the overall participants was 47.69 years, and 48.77% were male. We found that tertiles of serum terpene were positively associated with binary (elevated TC, non-HDL-C, TG, LDL-C, RC, Apo B, and lowered HDL-C) and continuous (TC, non-HDL-C, TG, LDL-C, RC, and Apo B, but not HDL-C) serum lipid variables. WQS regression and BKMR analysis revealed that the mixture of serum terpenes was linked with the prevalence of dyslipidemia. According to our data, the prevalence of dyslipidemia was correlated with serum concentrations of three terpenes both separately and collectively.

Single-chemical and mixture effects of multiple volatile organic compounds exposure on liver injury and risk of non-alcoholic fatty liver disease in a representative general adult population

Evidence on liver injury and non-alcoholic fatty liver disease (NAFLD) from volatile organic compounds (VOCs) exposure is insufficient. A cross-sectional study including 3011 US adults from the National Health and Nutrition Examination Survey was conducted to explore the associations of urinary exposure biomarkers (EBs) for 13 VOCs (toluene, xylene, ethylbenzene, styrene, acrylamide, N,N-dimethylformamide, acrolein, crotonaldehyde, 1,3-butadiene, acrylonitrile, cyanide, propylene oxide, and 1-bromopropane) with liver injury biomarkers and the risk of NAFLD by performing single-chemical (survey weight regression) and mixture (Bayesian kernel machine regression [BKMR] and weighted quantile sum [WQS]) analyses. We found significant positive associations of EBs for toluene and 1-bromopropane with alanine aminotransferase (ALT), EBs for toluene, crotonaldehyde, and 1,3-butadiene with asparate aminotransferase (AST), EBs for 1,3-butadiene and cyanide with alkaline phosphatase (ALP), EBs for xylene and cyanide with hepamet fibrosis score (HFS), EBs for the total 13 VOCs (except propylene oxide) with United States fatty liver index (USFLI), and EBs for xylene, N,N-dimethylformamide, acrolein, crotonaldehyde, and acrylonitrile with NALFD; and significant inverse associations of EBs for ethylbenzene, styrene, acrylamide, acrolein, crotonaldehyde, 1,3-butadiene, acrylonitrile, cyanide, and propylene oxide with total bilirubin, EBs for ethylbenzene, styrene, acrylamide, acrolein, 1,3-butadiene, acrylonitrile, and cyanide with albumin (ALB), EBs for ethylbenzene, styrene, acrylamide, N,N-dimethylformamide, acrolein, crotonaldehyde, 1,3-butadiene, acrylonitrile, cyanide, and propylene oxide with total protein (TP), and EB for 1-bromopropane with AST/ALT (all P-FDR<0.05). In BKMR and WQS, the mixture of VOC-EBs was significantly positively associated with ALT, AST, ALP, HFS, USFLI, and the risk of NAFLD, while significantly inversely associated with TBIL, ALB, TP, and AST/ALT. VOCs exposure was associated with liver injury and increased risk of NAFLD in US adults. These findings highlight that great attention should be paid to the potential risk of liver health damage from VOCs exposure.

Association between multiple metal(loid)s exposure and renal function: a cross-sectional study from southeastern China

In the real world, humans are exposed to multiple metal(loid)s (designated hereafter metals) that contain essential metals as well as toxic metals. Exposure to the metal mixture was assumed to be associated with renal function impairment; however, there is no consensus on available studies. Therefore, we here explored the association between multiple metals exposure and indicators of renal function in the general population from southeastern China. A total of 11 metals with 6 human essential metals and 5 toxic metals were determined in the selected 720 subjects. In addition, serum uric acid (SUA), serum creatinine (SCR), and the estimated glomerular filtration rate (eGFR) were measured or calculated as indicators of renal function. Using multiple flexible statistical models of generalized linear model, elastic net regression, and Bayesian kernel machine regression, the joint as well as the individual effect of metals within the mixture, and the interactions between metals were explored. When exposed to the metal mixture, the statistically non-significantly increased SUA, the significantly increased SCR, and the significantly declined eGFR were observed. In addition, the declined renal function may be primarily attributed to lead (Pb), arsenic (As), and nickel (Ni) exposure. Finally, interactions, such as the synergistic effect between Pb and Mo on SUA, whereas the antagonistic effect between Ni and Cd on SCR and eGFR were identified. Our finding suggests that combined exposure to multiple metals would impair renal function. Therefore, reducing exposure to toxic heavy metals of Pb, As, and Cd and limiting exposure to the human essential metal of Ni would protect renal function.

Exposures to volatile organic compounds, serum vitamin D, and kidney function: association and interaction assessment in the US adult population

The relationships of exposures to volatile organic compounds (VOCs) with vitamin D and kidney function remain unclear. Our analyses included 6070 adults from 2003 to 2010 survey cycles of the National Health and Nutrition Examination Survey to explore associations of six VOCs with serum vitamin D, albumin-to-creatinine ratio (ACR), and estimated glomerular filtration rate (eGFR). The results suggested that dibromochloromethane was positively associated with ACR, and chloroform was inversely associated with ACR. U-shaped associations of toluene, m-/p-xylene, bromodichloromethane, and 1,4-dichlorobenzene with ACR were observed. Toluene, m-/p-xylene, and 1,4-dichlorobenzene were associated with eGFR in U-shaped manners, while bromodichloromethane and chloroform were inversely associated with eGFR. Elevation in 1,4-dichlorobenzene was associated with decrease in vitamin D, while chloroform and m-/p-xylene were in U-shaped associations with vitamin D. VOCs mixture was U-shaped associated with ACR, inversely associated with eGFR, and inversely associated with vitamin D. Vitamin D was in a U-shaped association with ACR. Vitamin D significantly interacted with VOCs on the two kidney parameters. In the US adult population, exposures to VOCs were associated with kidney function and serum vitamin D level decline, and the serum vitamin D may have interaction effects with VOCs exposures on kidney function.