Exposure to multiple metals in early pregnancy and gestational diabetes mellitus: A prospective cohort study

Multimetal exposure: Challenges in diagnostics, prevention, and treatment

Extensive use of heavy metals has posed a serious concern for ecosystem and human too. Heavy metals are toxic in nature and their accumulation in human body causes serious disorders such as neurological disease, cardiac disease, gastrointestinal problems, skin disorders, reproductive disease, lungs diseases, and so on. Furthermore, heavy metals not only affect the human health but also have a negative impact on the economy. In the current review, we have elaborated the impact of heavy metal exposure on human health and socioeconomics. We have discussed the molecular mechanism involved in the heavy metal-induced human disorders such as oxidative stress, neuroinflammation, and protein misfolding. Finally, we discussed the preventive measure and treatment strategy that could counter the negative effects of heavy metal intoxications. In conclusion, there is a substantial correlation between heavy metals and the onset and advancement of several health issues. Chelation treatment could be a useful tactic to lessen the toxic metal load and the difficulties that come with it.

An association between PM2.5 components and respiratory infectious diseases: A China's mainland-based study

The particulate matter with diameter of less than 2.5 µm (PM2.5) is an important risk factor for respiratory infectious diseases, such as scarlet fever, tuberculosis, and similar diseases. However, it is not clear which component of PM2.5 is more important for respiratory infectious diseases. Based on data from 31 provinces in mainland China obtained between 2013 and 2019, this study investigated the effects of different PM2.5 components, i.e., sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and organic matter (OM), and black carbon (BC), on respiratory infectious diseases incidence [pulmonary tuberculosis (PTB), scarlet fever (SF), influenza, hand, foot, and mouth disease (HFMD), and mumps]. Geographical probes and the Bayesian kernel machine regression (BKMR) model were used to investigate correlations, single-component effects, joint effects, and interactions between components, and subgroup analysis was used to assess regional and temporal heterogeneity. The results of geographical probes showed that the chemical components of PM2.5 were associated with the incidence of respiratory infectious diseases. BKMR results showed that the five components of PM2.5 were the main factors affecting the incidence of respiratory infectious diseases (PIP>0.5). The joint effect of influenza and mumps by co-exposure to the components showed a significant positive correlation, and the exposure-response curve for a single component was approximately linear. And single-component modelling revealed that OM and BC may be the most important factors influencing the incidence of respiratory infections. Moreover, respiratory infectious diseases in southern and southwestern China may be less affected by the PM2.5 component. This study is the first to explore the relationship between different components of PM2.5 and the incidence of five common respiratory infectious diseases in 31 provinces of mainland China, which provides a certain theoretical basis for future research.

Individual and joint associations of per- and polyfluoroalkyl substances (PFAS) with gallstone disease in adults: A cross-sectional study

Disturbances in the enterohepatic circulation are important biological mechanisms for causing gallstones and also have important effects on the metabolism of Per- and polyfluoroalkyl substances (PFAS). Moreover, PFAS is associated with sex hormone disorder which is another important cause of gallstones. However, it remains unclear whether PFAS is associated with gallstones. In this study, we used logistic regression, restricted cubic spline (RCS), quantile g-computation (qg-comp), Bayesian kernel machine regression (BKMR), and subgroup analysis to assess the individual and joint associations of PFAS with gallstones and effect modifiers. We observed that the individual associations of perfluorodecanoic acid (PFDeA) (OR: 0.600, 95% CI: 0.444 to 0.811), perfluoroundecanoic acid (PFUA) (OR: 0.630, 95% CI: 0.453 to 0.877), n-perfluorooctane sulfonic acid (n-PFOS) (OR: 0.719, 95% CI: 0.571 to 0.906), and perfluoromethylheptane sulfonic acid isomers (Sm-PFOS) (OR: 0.768, 95% CI: 0.602 to 0.981) with gallstones were linearly negative. Qg-comp showed that the PFAS mixture (OR: 0.777, 95% CI: 0.514 to 1.175) was negatively associated with gallstones, but the difference was not statistically significant, and PFDeA had the highest negative association. Moreover, smoking modified the association of perfluorononanoic acid (PFNA) with gallstones. BKMR showed that PFDeA, PFNA, and PFUA had the highest groupPIP (groupPIP = 0.93); PFDeA (condPIP = 0.82), n-perfluorooctanoic acid (n-PFOA) (condPIP = 0.68), and n-PFOS (condPIP = 0.56) also had high condPIPs. Compared with the median level, the joint association of the PFAS mixture with gallstones showed a negative trend; when the PFAS mixture level was at the 70th percentile or higher, they were negatively associated with gallstones. Meanwhile, when other PFAS were fixed at the 25th, 50th, and 75th percentiles, PFDeA had negative associations with gallstones. Our evidence emphasizes that PFAS is negatively associated with gallstones, and more studies are needed in the future to definite the associations of PFAS with gallstones and explore the underlying biological mechanisms.

Spatial - temporal mapping of urine cadmium levels in China during 1980 - 2040: Dietary improvements lower exposure amid rising pollution

Persistent cadmium exposure poses significant health risks to the Chinese population, underscored by its prevalence as an environmental contaminant. This study leverages a machine-learning model, fed with a comprehensive dataset of environmental and socio-economic factors, to delineate trends in cadmium exposure from 1980 to 2040. We uncovered that urinary cadmium levels peaked at 1.09 μg/g Cr in the mid-2000 s. Encouragingly, a decline is projected to 0.92 μg/g Cr by 2025, tapering further to 0.87 μg/g Cr by 2040. Despite this trend, regions heavily influenced by industrialization, such as Hunan and Guizhou, as well as industrial counties in Jilin, report stubbornly high levels of exposure. Our demographic analysis reveals a higher vulnerability among adults & adolescents over 14, with males displaying elevated cadmium concentrations. Alarmingly, the projected data suggests that by 2040, an estimated 41% of the population will endure exposure beyond the safety threshold set by the European Food Safety Authority. Our research indicates disproportionate cadmium exposure impacts, necessitating targeted interventions and policy reforms to protect vulnerable groups and public health in China.

Metalloestrogens exposure and risk of gestational diabetes mellitus: Evidence emerging from the systematic review and meta-analysis

BACKGROUND

Metalloestrogens are metals and metalloid elements with estrogenic activity found everywhere. Their impact on human health is becoming more apparent as human activities increase.

OBJECTIVE

Our aim is to conduct a comprehensive systematic review and meta-analysis of observational studies exploring the correlation between metalloestrogens (specifically As, Sb, Cr, Cd, Cu, Se, Hg) and Gestational Diabetes Mellitus (GDM).

METHODS

PubMed, Web of Science, and Embase were searched to examine the link between metalloestrogens (As, Sb, Cr, Cd, Cu, Se, and Hg) and GDM until December 2023. Risk estimates were derived using random effects models. Subgroup analyses were conducted based on study countries, exposure sample, exposure assessment method, and detection methods. Sensitivity analyses and adjustments for publication bias were carried out to assess the strength of the findings.

RESULTS

Out of the 389 articles identified initially, 350 met our criteria and 33 were included in the meta-analysis, involving 141,175 subjects (9450 cases, 131,725 controls). Arsenic, antimony, and copper exposure exhibited a potential increase in GDM risk to some extent (As: OR = 1.28, 95 % CI [1.08, 1.52]; Sb: OR = 1.73, 95 % CI [1.13, 2.65]; Cu: OR = 1.29, 95 % CI [1.02, 1.63]), although there is a high degree of heterogeneity (As: Q = 52.93, p < 0.05, I2 = 64.1 %; Sb: Q = 31.40, p < 0.05, I2 = 80.9 %; Cu: Q = 21.14, p < 0.05, I2 = 71.6 %). Conversely, selenium, cadmium, chromium, and mercury exposure did not exhibit any association with the risk of GDM in our study.

DISCUSSION

Our research indicates that the existence of harmful metalloestrogens in the surroundings has a notable effect on the likelihood of GDM. Hence, we stress the significance of environmental elements in the development of GDM and the pressing need for relevant policies and measures.

Association of exposure to multiple heavy metals during pregnancy with the risk of gestational diabetes mellitus and insulin secretion phase after glucose stimulation

BACKGROUND

Epidemiological evidence for the association between heavy metals exposure during pregnancy and gestational diabetes mellitus (GDM) is still inconsistent. Additionally, that is poorly understood about the potential cause behind the association, for instance, whether heavy metal exposure is related to the change of insulin secretion phase is unknown.

OBJECTIVES

We aimed to explore the relationships of blood levels of arsenic (As), lead (Pb), thallium (Tl), nickel (Ni), cadmium (Cd), cobalt (Co), barium (Ba), chromium (Cr), mercury (Hg) and copper (Cu) during early pregnancy with the odds of GDM, either as an individual or a mixture, as well as the association of the metals with insulin secretion phase after glucose stimulation.

METHODS

We performed a nested case-control study consisting of 302 pregnant women with GDM and 302 controls at the First Affiliated Hospital of Anhui Medical University in Hefei, China. Around the 12th week of pregnancy, blood samples of pregnant women were collected and levels of As, Pb, Tl, Ni, Cd, Co, Ba, Cr, Hg and Cu in blood were measured. An oral glucose tolerance test (OGTT) was done in each pregnant woman during the 24-28th week of pregnancy to diagnose GDM and C-peptide (CP) levels during OGTT were measured simultaneously. The four metals (As, Pb, Tl and Ni) with the highest effect on odds of GDM were selected for the subsequent analyses via the random forest model. Conditional logistic regression models were performed to analyze the relationships of blood As, Pb, Tl and Ni levels with the odds of GDM. The weighted quantile sum (WQS) regression and bayesian kernel machine regression (BKMR) were used to assess the joint effects of levels of As, Pb, Tl and Ni on the odds of GDM as well as to evaluate which metal level contributed most to the association. Latent profile analysis (LPA) was conducted to identify profiles of glycemic and C-peptide levels at different time points. Multiple linear regression models were employed to explore the relationships of metals with glycaemia-related indices (fasting blood glucose (FBG), 1-hour blood glucose (1h BG), 2-hour blood glucose (2h BG), fasting C-peptide (FCP), 1-hour C-peptide (1h CP), 2-hour C-peptide (2h CP), FCP/FBG, 1h CP/1h BG, 2h CP/2h BG, area under the curve of C-peptide (AUCP), area under the curve of glucose (AUCG), AUCP/AUCG and profiles of BGs and CPs, respectively. Mixed-effects models with repeated measures data were used to explore the relationship between As (the ultimately selected metal) level and glucose-stimulated insulin secretion phase. The mediation effects of AUCP and AUCG on the association of As exposure with odds of GDM were investigated using mediation models.

RESULTS

The odds of GDM in pregnant women increased with every ln unit increase in blood As concentration (odds ratio (OR) = 1.46, 95% confidence interval (CI) = 1.04-2.05). The joint effects of As, Pb, Tl and Ni levels on the odds of GDM was statistically significant when blood levels of four metals were exceeded their 50th percentile, with As level being a major contributor. Blood As level was positively associated with AUCG and the category of glucose latent profile, the values of AUCG were much higher in GDM group than those in non-GDM group, which suggested that As exposure associated with the odds of GDM may be due to that As exposure was related to the impairment of glucose tolerance among pregnant women. The significant and positive relationships of As level with AUCP, CP latent profile category, 2h CP and 2h CP/2h BG were observed, respectively; and the values of 1h CP/1h BG and AUCP/AUCG were much lower in GDM group than those in non-GDM group, which suggested that As exposure may not relate to the impairment of insulin secretion (pancreatic β-cell function) among pregnant women. The relationships between As level and 2h CP as well as 2h CP/2h BG were positive and significant; additionally, the values of 2h CP/2h BG in GDM group were comparable with those in non-GDM group; the peak value of CP occurred at 2h in GDM group, as well as the values of 2h CP/2h BG in high As exposure group were much higher than those in low As exposure group, which suggested that As exposure associated with the increased odds of GDM may be due to that As exposure was related to the change of insulin secretion phase (delayment of the peak of insulin secretion) among pregnant women. In addition, AUCP mediated 11% (p < 0.05) and AUCG mediated 43% (p < 0.05) of the association between As exposure and the odds of GDM.

CONCLUSION

Our results suggested that joint exposure to As, Pb, Tl and Ni during early pregnancy was positively associated with the odds of GDM, As was a major contributor; and the association of environmental As exposure with the increased odds of GDM may be due to that As exposure was related to the impairment of glucose tolerance and change of insulin secretion phase after glucose stimulation (delayment of the peak of insulin secretion) among pregnant women.

Effect of arsenic on the risk of gestational diabetes mellitus: a systematic review and meta-analysis

BACKGROUND

Gestational diabetes mellitus (GDM) is a complication of pregnancy associated with numerous adverse outcomes. There may be a potential link between GDM and arsenic (As) exposure, but this hypothesis remains controversial. This meta-analysis summarizes the latest studies evaluating the association between As and GDM.

METHODS

A comprehensive search of the PubMed, Embase, and Scopus databases up to September 2023 was performed. The pooled estimates with 95% CIs were presented using forest plots. Estimates were calculated with random effects models, and subgroup and sensitivity analyses were conducted to address heterogeneity.

RESULTS

A total of 13 eligible studies involving 2575 patients with GDM were included in this meta-analysis. The results showed that women exposed to As had a significantly increased risk of GDM (OR 1.47, 95% CI: 1.11 to 1.95, P = 0.007). Subgroup analyses suggested that the heterogeneity might be attributed to the years of publication. In addition, sensitivity analysis confirmed the robust and reliable results.

CONCLUSIONS

This analysis suggested that women exposed to As have a greater risk of GDM. However, the significant heterogeneity across studies requires careful interpretation.

REGISTRATION

The PROSPERO registration ID is CRD42023461820.

Association between exposure to multiple metals and stress urinary incontinence in women: a mixture approach

There is limited evidence linking exposure to heavy metals, especially mixed metals, to stress urinary incontinence (SUI). This study aimed to explore the relationship between multiple metals exposure and SUI in women. The data were derived from the National Health and Nutrition Examination Survey (NHANES), 2007-2020. In the study, a total of 13 metals were analyzed in blood and urine. In addition, 5155 adult women were included, of whom 2123 (41.2%) suffered from SUI. The logistic regression model and restricted cubic spline (RCS) were conducted to assess the association of single metal exposure with SUI risk. The Bayesian kernel machine regression (BKMR) and weighted quantile sum (WQS) were used to estimate the combined effect of multiple metals exposure on SUI. First, we observed that blood Pb, Hg and urinary Pb, Cd were positively related to SUI risk, whereas urinary W was inversely related by multivariate logistic regression (all p-FDR < 0.05). Additionally, a significant non-linear relationship between blood Hg and SUI risk was observed by RCS analysis. In the co-exposure models, WQS model showed that exposure to metal mixtures in blood [OR (95%CI) = 1.18 (1.06, 1.31)] and urine [OR (95%CI) = 1.18 (1.03, 1.34)] was positively associated with SUI risk, which was consistent with the results of BKMR model. A potential interaction was identified between Hg and Cd in urine. Hg and Cd were the main contributors to the combined effects. In summary, our study indicates that exposure to heavy metal mixtures may increase SUI risk in women.

Association between phthalates and sleep problems in the U.S. adult females from NHANES 2011-2014

There is little research on the relationship between phthalates exposure and sleep problems in adult females, with existing studies only assessing the association between exposure to individual phthalates with sleep problems.     We aimed to analyse the relationship between phthalates and sleep problems in 1366 US females aged 20 years and older from the 2011-2014 National Health and Nutrition Examination Survey (NHANES) by age stratification. Multivariate logistic regression showed that the fourth quartile of MECPP increased the risk of sleep problems in females aged 20-39 compared with the reference quartile (OR: 1.87, 95% CI: 1.14, 3.08). The WQS index was significantly associated with the sleep problems in females aged 20-39. In the BKMR, a positive overall trend between the mixture and sleep problems in females aged 20-39. In this study, we concluded that phthalates might increase the risk of sleep problems in females aged 20-39.

Predictors of urinary heavy metal concentrations among pregnant women in Jinan, China

BACKGROUND

Toxic heavy metal exposure and insufficiency or excess of essential heavy metals may have negative effects on pregnant women's health and fetal growth. To date, the predictors of pregnant women's heavy metal exposure levels remain unclear and vary with different regions. The study intended to explore potential predictors of exposure to heavy metals individually and high co-exposure to heavy metal mixtures.

METHODS

We recruited 298 pregnant women in first trimester from prenatal clinics in Jinan, Shandong Province, China, and collected spot urine samples and questionnaire data on their demographic characteristics, lifestyle habits, consumption of food and dietary supplement, and residential environment. All urine samples were analyzed for seven heavy metals: cobalt (Co), molybdenum (Mo), strontium (Sr), arsenic (As), cadmium (Cd), lead (Pb) and mercury (Hg).

RESULTS

Factors associated with single heavy metal concentration were as follows: a) urinary As, Sr and Cd increased with women's age respectively; b) pregnant women with higher monthly household income per capita had lower Sr and Mo levels; c) pregnant women with intermittent folic acid supplementation and those not taking tap water as domestic drinking water had lower Sr concentrations; d) Cd was positively linked with consumption frequency of rice; e) Hg was adversely related to consumption frequency of egg and the women who took purified water as domestic drinking water had lower Hg exposure. In addition, pregnant women's age was positively associated with odds of high co-exposure to Co, As, Sr, Mo, Cd and Pb; while those with an educational level of college had lower odds of high exposure to such a metal mixture compared with those whose educational levels were lower than high school.

CONCLUSION

Predictors of single urinary heavy metal concentration included pregnant women's age (As, Sr and Cd), monthly household income per capita (Sr and Mo), folic acid supplementation (Sr), rice consumption frequency (Cd), egg consumption frequency (Hg) and the type of domestic drinking water (Sr and Hg). Pregnant women with older age, lower educational level tended to have high co-exposure to Co, As, Sr, Mo, Cd and Pb.

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.

Association Between Multiple Heavy Metal Exposures and Cholesterol Levels in Residents Living Near a Smelter Plant in Korea

BACKGROUND

Considering the interactions between heavy metals, a comprehensive evaluation of the effects of exposure to various types of co-interacting heavy metals on health is required. This study assessed the association between dyslipidemia markers and blood mercury, lead, cadmium, iron, zinc, and nickel levels in residents of an abandoned refinery plant.

METHODS

A total of 972 individuals (exposed group: 567, control group: 405) living near the Janghang refinery plant in the Republic of Korea were included. Blood mercury, lead, cadmium, iron, zinc, nickel, cholesterol, and triglyceride levels were measured. The combined effect of the six heavy metals on dyslipidemia markers was evaluated using a Bayesian kernel machine regression (BKMR) model and compared with the results of a linear regression analysis. The BKMR model results were compared using a stratified analysis of the exposed and control groups.

RESULTS

In the BKMR model, the combined effect of the six heavy metals was significantly associated with total cholesterol (TC) levels both below the 45th percentile and above the 55th percentile in the total population. The combined effect range between the 25th and 75th percentiles of the six metals on TC levels was larger in the exposed group than that in the total population. In the control group, the combined effects of the changes in concentration of the six heavy metals on the TC concentration were not statistically significant.

CONCLUSION

These results suggest that the cholesterol levels of residents around the Janghang refinery plant may be elevated owing to exposure to multiple heavy metals.

Screening the critical protein subnetwork to delineate potential mechanisms and protective agents associated with arsenic-induced cutaneous squamous cell carcinoma: A toxicogenomic study

Recent studies show that complex mechanisms are involved in arsenic-induced malignant transformation of cells. This study aimed to decipher molecular mechanisms associated with arsenic-induced cutaneous squamous cell carcinoma (cSCC) and suggest potential protective factors. RNA-seq-based differentially expressed genes between arsenic-exposed human keratinocytes (HaCaT) and controls were used to construct a protein-protein interaction (PPI) network and discover critical subnetwork-based mechanisms. Protective compounds against arsenic toxicity were determined and their target interactions in the core sub-network were identified by the comparative toxicogenomic database (CTD). The binding affinity between the effective factor and target was calculated by molecular docking. A total of 15 key proteins were screened out as critical arsenic-responsive subnetwork (FN1, IL-1A, CCN2, PECAM1, FGF5, EDN1, FGF1, PXDN, DNAJB9, XBP1, ERN1, PDIA4, DNAJB11, FOS, PDIA6) and 7 effective protective agents were identified (folic acid, quercetin, zinc, acetylcysteine, methionine, catechin, selenium). The GeneMANIA predicted detailed interactions of the subnetwork and revealed terms related to unfolded protein response as the main processes. FN1, IL1A and CCN2, as top significant genes, had good docking affinity with folic acid and quercetin, as selected key compounds. Integration of gene expression and protein-protein interaction related to arsenic exposure in cSCC explored the potential mechanisms and protective agents.

Association between Mediterranean diet and metal mixtures concentrations in pregnant people from the New Hampshire Birth Cohort Study

Diet is a primary source of nutrients but also toxic metal exposure. In pregnancy, balancing essential metal exposure while reducing non-essential ones is vital for fetal and maternal health. However, the effect of metal mixtures from diets like the Mediterranean, known for health benefits, remains unclear. This study aimed to explore the association between Mediterranean diet adherence and metals exposure, both individually and as mixtures. The study involved 907 pregnant participants from the New Hampshire Birth Cohort Study. We calculated the relative Mediterranean diet score (rMED) through a validated food frequency questionnaire, which includes 8 traditional Mediterranean dietary components. Also, at ~24-28 weeks of gestation, we used ICP-MS to measure speciation of Al, Cd, Co, Cu, Fe, Hg, Mo, Ni, Sb, Se, Sn, Zn, and As in urine, as well as Pb, Hg, As, Ni, and Se in toenails. We used multiple linear regression and Weighted Quantile Sum regression to analyze the association between rMED and metal mixtures. The models were adjusted for age, pre-pregnancy BMI, smoking during pregnancy, and educational level. High adherence to the Mediterranean diet was associated with increased urinary Al (® = 0.26 (95 % confidence interval (CI) = 0.05; 0.46)), Cd (β = 0.12 (95%CI = 0.00; 0.24)), Mo (β = 0.10 (95%CI = 0.00; 0.20)), and AsB (β = 0.88 (95%CI = 0.49; 1.27)) as well as toenail Hg (β = 0.44 (95%CI = 0.22; 0.65)), Ni (β = 0.37 (95%CI = 0.06; 0.67)), and Pb (β = 0.22 (95%CI = 0.03; 0.40)) compared to those with low adherence. The intake of fruits and nuts, fish and seafood, legumes, cereals, meat, and olive oil were found to be related to the metal biomarkers within the rMED. In conclusion, the Mediterranean diet enhances essential metal intake but may also increase exposure to harmful ones.

Comparative study on anthropogenic impacts on soil PAHs: Accumulation and source apportionment in tourist and industrial cities in Hebei Province, China

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous organic contaminants in urban soils. The accumulation and source identifications of PAHs within a city have been frequently studied. However, impacts of urbanization development modes on PAHs accumulation patterns by taking a city as a whole have been seldom reported. Four cities with two development modes in Hebei province, Chengde and Zhangjiakou (tourist cities) and Handan and Tangshan (industrial cities), were selected. The concentrations of 16 priority PAHs in soils in the study areas were investigated. The results showed that the average concentrations of Σ16PAHs in Handan (2517 μg/kg) and Tangshan (2256 μg/kg) were more than twice of those in Chengde (696 μg/kg) and Zhangjiakou (926 μg/kg) approximately. Lines of evidence, provided by a combination of diagnostic ratios, pairwise correlation, and PMF methods, revealed that the dominant sources of PAHs in either city were industrial emission, vehicle emission, and petrogenic/biogenic process but with different proportions. Linear fittings based on Bayesian kernel machine regression analysis (BKMR) were constructed to illustrate the impact of industrialization on PAHs accumulation. The probability of excessing the 10 % (376 μg/kg) and 50 % (1138 μg/kg) of current ∑16PAHs would be higher than 90 % given the gross industrial production per unit area >5.00 × 106 and 20.5 × 106 CNY/km2, respectively. The proposed threshold values of industrialization are of significance for determining industrial structure and proportion in urban management.

Arsenic and adipose tissue: an unexplored pathway for toxicity and metabolic dysfunction

Arsenic-contaminated drinking water can induce various disorders by disrupting lipid and glucose metabolism in adipose tissue, leading to insulin resistance. It inhibits adipocyte development and exacerbates insulin resistance, though the precise impact on lipid synthesis and lipolysis remains unclear. This review aims to explore the processes and pathways involved in adipogenesis and lipolysis within adipose tissue concerning arsenic-induced diabetes. Although arsenic exposure is linked to type 2 diabetes, the specific role of adipose tissue in its pathogenesis remains uncertain. The review delves into arsenic's effects on adipose tissue and related signaling pathways, such as SIRT3-FOXO3a, Ras-MAP-AP-1, PI(3)-K-Akt, endoplasmic reticulum stress proteins, CHOP10, and GPCR pathways, emphasizing the role of adipokines. This analysis relies on existing literature, striving to offer a comprehensive understanding of different adipokine categories contributing to arsenic-induced diabetes. The findings reveal that arsenic detrimentally impacts white adipose tissue (WAT) by reducing adipogenesis and promoting lipolysis. Epidemiological studies have hinted at a potential link between arsenic exposure and obesity development, with limited research suggesting a connection to lipodystrophy. Further investigations are needed to elucidate the mechanistic association between arsenic exposure and impaired adipose tissue function, ultimately leading to insulin resistance.

Multivitamin consumption and childhood asthma: a cross-sectional study of the NHANES database

BACKGROUND

Dietary intakes of vitamins are associated with asthma. However, previous studies mainly explored the association between a single vitamin intake and asthma, which did not take the multivitamins into consideration. Herein, this study aims to explore the overall effect of dietary multivitamins consumption on childhood asthma.

METHODS

Data of children and adolescents (aged 2-17 years old) were extracted from the National Health and Nutrition Examination Survey (NHANES) database in 2015-2018 in this cross-sectional study. Weighted univariate logistic regression analysis was used to screen covariates. The association between multivitamins (including vitamin A, C, D, E, B1, B2, B6, B12, K, niacin, folic acid, and choline) and childhood asthma was explored using univariate and multivariate logistic regression analyses. The evaluation indexes were odds ratio (OR) and 95% confidence interval (CI). We further introduced the Bayesian kernel machine regression (BKMR) to assess the joint effect of the twelve vitamins on childhood asthma, the impact of an individual vitamin as part of a vitamin mixture, and the potential interactions among different vitamins.

RESULTS

Among 4,715 eligible children and adolescents, 487 (10.3%) had asthma. After adjusting for covariates including race, family history of asthma, pregnant smoking, BMI Z-score, energy intake, breast feeding, and low birth weight, we found that for each 1-unit increase in vitamin K consumption, the odds of childhood asthma decreased 0.99 (P=0.028). The overall effect analysis reported a trend of negative relationship between the multivitamins and childhood asthma, especially at the 75th percentile and over. According to the BKMR models, when other vitamins are fixed at the median level, the odds of childhood asthma increased along with the elevated vitamin D (VD) and vitamin B2 (VB2), whereas along with the depressed vitamin C (VC). In addition, no potential interaction has been found between every two vitamins of multivitamins on childhood asthma.

CONCLUSION

Among children and adolescents who have high-risk of asthma, it may be beneficial to increase dietary consumption of multivitamins. Our findings recommended that children and adolescents should increase the intake of VC-rich foods, whereas control the dietary consumption of VD and VB2 in daily life.

Analysis of Relationships between Metabolic Changes and Selected Nutrient Intake in Women Environmentally Exposed to Arsenic

Nutrients involved in the metabolism of inorganic arsenic (iAs) may play a crucial role in mitigating the adverse health effects associated with such exposure. Consequently, the objective of this study was to analyze the association between the intake levels of nutrients involved in iAs metabolism and alterations in the metabolic profile during arsenic exposure. The study cohort comprised environmentally exposed women: WL (lower total urinary arsenic (As), n = 73) and WH (higher As, n = 73). The analysis included urinary untargeted metabolomics (conducted via liquid chromatography-mass spectrometry) and the assessment of nutrient intake involved in iAs metabolism, specifically methionine, vitamins B2, B6, and B12, folate, and zinc (based on 3-day dietary records of food and beverages). In the WL group, the intake of all analyzed nutrients exhibited a negative correlation with 5 metabolites (argininosuccinic acid, 5-hydroxy-L-tryptophan, 11-trans-LTE4, mevalonic acid, aminoadipic acid), while in the WH group, it correlated with 10 metabolites (5-hydroxy-L-tryptophan, dihyroxy-1H-indole glucuronide I, 11-trans-LTE4, isovalerylglucuronide, 18-oxocortisol, 3-hydroxydecanedioic acid, S-3-oxodecanoyl cysteamine, L-arginine, p-cresol glucuronide, thromboxane B2). Furthermore, nutrient intake demonstrated a positive association with 3 metabolites in the WL group (inosine, deoxyuridine, glutamine) and the WH group (inosine, N-acetyl-L-aspartic acid, tetrahydrodeoxycorticosterone). Altering the intake of nutrients involved in iAs metabolism could be a pivotal factor in reducing the negative impact of arsenic exposure on the human body. This study underscores the significance of maintaining adequate nutrient intake, particularly in populations exposed to arsenic.

Update of the risk assessment of inorganic arsenic in food

The European Commission asked EFSA to update its 2009 risk assessment on arsenic in food carrying out a hazard assessment of inorganic arsenic (iAs) and using the revised exposure assessment issued by EFSA in 2021. Epidemiological studies show that the chronic intake of iAs via diet and/or drinking water is associated with increased risk of several adverse outcomes including cancers of the skin, bladder and lung. The CONTAM Panel used the benchmark dose lower confidence limit based on a benchmark response (BMR) of 5% (relative increase of the background incidence after adjustment for confounders, BMDL05) of 0.06 μg iAs/kg bw per day obtained from a study on skin cancer as a Reference Point (RP). Inorganic As is a genotoxic carcinogen with additional epigenetic effects and the CONTAM Panel applied a margin of exposure (MOE) approach for the risk characterisation. In adults, the MOEs are low (range between 2 and 0.4 for mean consumers and between 0.9 and 0.2 at the 95th percentile exposure, respectively) and as such raise a health concern despite the uncertainties.

Combined exposure to multiple essential elements and cadmium at early pregnancy on gestational diabetes mellitus: a prospective cohort study

Background

Minerals and trace elements were involved in the pathogenesis and progression of diabetes. However, the association of mixed exposure to essential elements and toxic elements with gestational diabetes mellitus (GDM) is poorly understood.

Objective

This study aims to examine the associations between serum calcium (Ca), iron (Fe), zinc (Zn), copper (Cu), magnesium (Mg), and cadmium (Cd) concentrations in early pregnancy and GDM risk in Chinese pregnant women.

Method

A total of 1,168 pregnant women were included in this prospective cohort study. The concentrations of serum elements were measured using the polarography method before 14 gestational weeks and an oral glucose tolerance test was conducted at 24-28 gestational weeks to diagnose GDM. Binary logistic regression analysis and restricted cubic spline were applied to evaluate the association between serum individual element and GDM. Bayesian kernel machine regression (BKMR) and weighted quantile sum (WQS) regression were used to assess the associations between mixed essential elements and Cd exposure and GDM risk.

Results

The mean concentrations of Zn (124.65 vs. 120.12 μmol/L), Fe (135.26 vs. 132.21 μmol/L) and Cu (23.33 vs. 23.03 μmol/L) in the GDM group were significantly higher than those in the control group. Single-element modeling results suggested that second and fourth-quartile maternal Zn and Fe concentration, third and fourth-quartile Cu concentration and fourth-quartile Ca concentration were associated with an increased risk of GDM compared to first-quartile values. Restricted cubic spline analysis showed U-shaped and non-linear relationships between Cd and GDM. According to the BKMR models and WQS analyses, a six-element mixture was significantly and positively associated with the risk of GDM. Additionally, Cd, Zn, and Cu contributed the most strongly to the association.

Conclusion

Serum Zn, Cu, Fe, and Ca exposure during early pregnancy showed a positive association with GDM in the individual evaluation. The multiple-evaluation showed that high levels of elements mixture, particularly Cd, Zn, and Cu, may promote the development of GDM.

Role of Endometrial Extracellular Vesicles in Mediating Cell-to-Cell Communication in the Uterus: A Review

There are several critical events that occur in the uterus during early pregnancy which are necessary for the establishment and maintenance of pregnancy. These events include blastocyst implantation, uterine decidualization, uterine neoangiogenesis, differentiation of trophoblast stem cells into different trophoblast cell lineages, and formation of a placenta. These processes involve several different cell types within the pregnant uterus. Communication between these cell types must be intricately coordinated for successful embryo implantation and the formation of a functional maternal-fetal interface in the placenta. Understanding how this intricate coordination transpires has been a focus of researchers in the field for many years. It has long been understood that maternal endometrial tissue plays a key role in intercellular signaling during early pregnancy, sending signals to nearby tissues in a paracrine manner. Recently, insights have been obtained into the mechanisms by which these signaling events occur. Notably, the endometrium has been shown to secrete extracellular vesicles (EVs) that contain crucial cargo (proteins, lipids, RNA, miRNA) that are taken up by recipient cells to initiate a response leading to the occurrence of critical events during implantation and placentation. In this review, we aim to summarize the role that endometrium-derived EVs play in mediating cell-to-cell communications within the pregnant uterus to orchestrate the events that must occur to establish and maintain pregnancy. We will also discuss how aberrant endometrial EV signaling may lead to pathophysiological conditions, such as endometriosis and infertility.

A Drosophila model of gestational antimony exposure uncovers growth and developmental disorders caused by disrupting oxidative stress homeostasis

The toxic heavy metal antimony (Sb) is ubiquitous in our daily lives. Various models have shown that Sb induces neuronal and reproductive toxicity. However, little is known about the developmental toxicity of Sb exposure during gestation and the underlying mechanisms. To study its effects on growth and development, Drosophila stages from eggs to pupae were exposed to different Sb concentrations (0, 0.3, 0.6 and 1.2 mg/mL Sb); RNA sequencing was used to identify the underlying mechanism. The model revealed that prenatal Sb exposure significantly reduced larval body size and weight, the pupation and eclosion rates, and the number of flies at all stages. With 1.2 mg/mL Sb exposure in 3rd instar larvae, 484 genes were upregulated and 694 downregulated compared to controls. Biological analysis showed that the disrupted transcripts were related to the oxidative stress pathway, as verified by reactive oxygen species (ROS) scavenger N-acetylcysteine (NAC) and glutathione (GSH) intervention experiments. Sb exposure induced oxidative stress imbalance could be rectified by chelation and antioxidant effects of NAC/GSH. The Drosophila Schneider 2 (S2) model further demonstrated that NAC and GSH greatly ameliorated cell death induced by Sb exposure. In conclusion, gestational Sb exposure disrupted oxidative stress homeostasis, thereby impairing growth and development.

Prediction of gestational diabetes mellitus using machine learning from birth cohort data of the Japan Environment and Children's Study

Recently, prediction of gestational diabetes mellitus (GDM) using artificial intelligence (AI) from medical records has been reported. We aimed to evaluate GDM-predictive AI-based models using birth cohort data with a wide range of information and to explore factors contributing to GDM development. This investigation was conducted as a part of the Japan Environment and Children's Study. In total, 82,698 pregnant mothers who provided data on lifestyle, anthropometry, and socioeconomic status before pregnancy and the first trimester were included in the study. We employed machine learning methods as AI algorithms, such as random forest (RF), gradient boosting decision tree (GBDT), and support vector machine (SVM), along with logistic regression (LR) as a reference. GBDT displayed the highest accuracy, followed by LR, RF, and SVM. Exploratory analysis of the JECS data revealed that health-related quality of life in early pregnancy and maternal birthweight, which were rarely reported to be associated with GDM, were found along with variables that were reported to be associated with GDM. The results of decision tree-based algorithms, such as GBDT, have shown high accuracy, interpretability, and superiority for predicting GDM using birth cohort data.

Impact of multi-heavy metal exposure on renal damage indicators in Korea: An analysis using Bayesian Kernel Machine Regression

Exposure to cadmium (Cd), arsenic (As), and mercury (Hg) is associated with renal tubular damage. People living near refineries are often exposed to multiple heavy metals at high concentrations. This cross-sectional study investigated the association between combined urinary Cd, As, and Hg levels and renal damage markers in 871 residents living near the Janghang refinery plant and in a control area. Urinary Cd, As, Hg, N-acetyl-β-D-glucosaminidase (NAG), and β2-microglobulin (β2-MG) levels were measured. The combined effects of Cd, As, and Hg on renal tubular damage markers were assessed using linear regression and a Bayesian Kernel Machine Regression (BKMR) model. The results of the BKMR model were compared using a stratified analysis of the exposure and control groups. While the linear regression showed that only Cd concentration was significantly associated with urinary NAG levels (β = 0.447, P value < .05), the BKMR model showed that Cd and Hg levels were also significantly associated with urinary NAG levels. The combined effect of the 3 heavy metals on urinary NAG levels was significant and stronger in the exposure group than in the control group. However, no relationship was observed between the exposure concentrations of the 3 heavy metals and urinary β2-MG levels. The results suggest that the BKMR model can be used to assess the health effects of heavy-metal exposure on vulnerable residents.

Metal Exposure during Early Pregnancy and Risk of Gestational Diabetes Mellitus: Mixture Effect and Mediation by Phospholipid Fatty Acids

Despite existing studies exploring the association between metal exposure and gestational diabetes mellitus (GDM), most of them have focused on a single metal or a small mixture of metals. Our prospective work investigated the joint and independent effects of early gestational exposure to 17 essential and nonessential metals on the GDM risk and potential mediation by plasma phospholipid fatty acids (PLFAs) based on a nested case-control study established with 335 GDM cases and 670 randomly matched healthy controls. The Bayesian kernel machine regression (BKMR) and quantile g-computation analyses demonstrated a joint effect from metal co-exposure on GDM risk. BKMR with hierarchical variable selection indicated that the group of essential metals was more strongly associated with GDM than the group of nonessential metals with group posterior inclusion probabilities (PIPs) of 0.979 and 0.672, respectively. Cu (0.988) and Ga (0.570) had the largest conditional PIPs within each group. We also observed significant mediation effects of selected unsaturated PLFAs on Cu-GDM and Ga-GDM associations. KEGG enrichment analysis further revealed significant enrichment in the biosynthesis of unsaturated PLFAs. C18:1 n-7 exhibited the largest proportion of mediation in both associations (23.8 and 22.9%). Collectively, our work demonstrated the joint effect of early gestational metal exposure on GDM risk and identified Cu and Ga as the key species to the joint effect. The findings lay a solid ground for further validation through multicenter investigations and mechanism exploration via laboratory studies.

Associations between multiple metals during early pregnancy and gestational diabetes mellitus under four statistical models

Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy. Metal exposure is an emerging factor affecting the risk of GDM. However, the effects of metal mixture on GDM and key metals within the mixture remain unclear. This study was aimed at investigating the association between metal mixture during early pregnancy and the risk of GDM using four statistical methods and further at identifying the key metals within the mixture associated with GDM. A nested case-control study including 128 GDM cases and 318 controls was conducted in Beijing, China. Urine samples were collected before 13 gestational weeks and the concentrations of 13 metals were measured. Single-metal analysis (unconditional logistic regression) and mixture analyses (Bayesian kernel machine regression (BKMR), quantile g-computation, and elastic-net regression (ENET) models) were applied to estimate the associations between exposure to multiple metals and GDM. Single-metal analysis showed that Ni was associated with lower risk of GDM, while positive associations of Sr and Sb with GDM were observed. Compared with the lowest quartile of Ni, the ORs of GDM in the highest quartiles were 0.49 (95% CI 0.24, 0.98). In mixture analyses, Ni and Mg showed negative associations with GDM, while Co and Sb were positively associated with GDM in BKMR and quantile g-computation models. No significant joint effect of metal mixture on GDM was observed. However, interestingly, Ni was identified as a key metal within the mixture associated with decreased risk of GDM by all three mixture methods. Our study emphasized that metal exposure during early pregnancy was associated with GDM, and Ni might have important association with decreased GDM risk.

DNA methylation analysis reveals the effect of arsenic on gestational diabetes mellitus

BACKGROUND

Arsenic (As) exposure is one of the risk factors for gestational diabetes mellitus (GDM). This study aimed to explore the effect of As-exposure on DNA methylation in GDM and to establish a risk assessment model of GDM in As exposed pregnant women.

METHOD

We collected elbow vein blood of pregnant women before delivery to measure As concentration and DNA methylation data. Then compared the DNA methylation data and established a nomogram.

RESULT

We identified a total of 10 key differentially methylated CpGs (DMCs) and found 6 corresponding genes. Functions were enriched in Hippo signaling pathway, cell tight junction, prophetic acid metabolism, ketone body metabolic process, and antigen processing and presentation. A nomogram was established that can predict GDM risks (c-index = 0.595, s:p = 0.973).

CONCLUSION

We found 6 genes associated with GDM with high As exposure. The prediction of the nomograms has been proven to be effective.

Mass spectrometry-based "omics" technologies for the study of gestational diabetes and the discovery of new biomarkers

Gestational diabetes (GDM) is one of the most common complications occurring during pregnancy. Diagnosis is performed by oral glucose tolerance test, but harmonized testing methods and thresholds are still lacking worldwide. Short-term and long-term effects include obesity, type 2 diabetes, and increased risk of cardiovascular disease. The identification and validation of sensitidve, selective, and robust biomarkers for early diagnosis during the first trimester of pregnancy are required, as well as for the prediction of possible adverse outcomes after birth. Mass spectrometry (MS)-based omics technologies are nowadays the method of choice to characterize various pathologies at a molecular level. Proteomics and metabolomics of GDM were widely investigated in the last 10 years, and various proteins and metabolites were proposed as possible biomarkers. Metallomics of GDM was also reported, but studies are limited in number. The present review focuses on the description of the different analytical methods and MS-based instrumental platforms applied to GDM-related omics studies. Preparation procedures for various biological specimens are described and results are briefly summarized. Generally, only preliminary findings are reported by current studies and further efforts are required to determine definitive GDM biomarkers.

Proteins and metabolites fingerprints of gestational diabetes mellitus forming protein-metabolite interactomes are its potential biomarkers

Gestational diabetes mellitus (GDM) is a consequence of glucose intolerance with an inadequate production of insulin that happens during pregnancy and leads to adverse health consequences for both mother and fetus. GDM patients are at higher risk for preeclampsia, and developing diabetes mellitus type 2 in later life, while the child born to GDM mothers are more prone to macrosomia, and hypoglycemia. The universally accepted diagnostic criteria for GDM are lacking, therefore there is a need for a diagnosis of GDM that can identify GDM at its early stage (first trimester). We have reviewed the literature on proteins and metabolites fingerprints of GDM. Further, we have performed protein-protein, metabolite-metabolite, and protein-metabolite interaction network studies on GDM proteins and metabolites fingerprints. Notably, some proteins and metabolites fingerprints are forming strong interaction networks at high confidence scores. Therefore, we have suggested that those proteins and metabolites that are forming protein-metabolite interactomes are the potential biomarkers of GDM. The protein-metabolite biomarkers interactome may help in a deep understanding of the prognosis, pathogenesis of GDM, and also detection of GDM. The protein-metabolites interactome may be further applied in planning future therapeutic strategies to promote long-term health benefits in GDM mothers and their children.

Short-term exposure to antimony induces hepatotoxicity and metabolic remodeling in rats

Antimony (Sb) poses a significant threat to human health due to sharp increases in its exploitation and application globally, but few studies have explored the pathophysiological mechanisms of acute hepatotoxicity induced by Sb exposure. We established an in vivo model to comprehensively explore the endogenous mechanisms underlying liver injury induced by short-term Sb exposure. Adult female and male Sprague-Dawley rats were orally administrated various concentrations of potassium antimony tartrate for 28 days. After exposure, the serum Sb concentration, liver-to-body weight ratio, and serum glucose levels significantly increased in a dose-dependent manner. Body weight gain and serum concentrations of biomarkers of hepatic injury (e.g., total cholesterol, total protein, alkaline phosphatase, and the aspartate aminotransferase/alanine aminotransferase ratio) decreased with increasing Sb exposure. Through integrative non-targeted metabolome and lipidome analyses, alanine, aspartate, and glutamate metabolism; phosphatidylcholines; sphingomyelins; and phosphatidylinositols were the most significantly affected pathways in female and male rats exposed to Sb. Additionally, correlation analysis showed that the concentrations of certain metabolites and lipids (e.g., deoxycholic acid, N-methylproline, palmitoylcarnitine, glycerophospholipids, sphingomyelins, and glycerol) were significantly associated with hepatic injury biomarkers, indicating that metabolic remodeling may be involved in apical hepatotoxicity. Our study demonstrated that short-term exposure to Sb induces hepatotoxicity, possibly through a glycolipid metabolism disorder, providing an important reference for the health risks of Sb pollution.

Arsenic in Drinking Water and Diabetes

Arsenic is ubiquitous in soil and water environments and is consistently at the top of the Agency for Toxic Substances Disease Registry (ATSDR) substance priority list. It has been shown to induce toxicity even at low levels of exposure. One of the major routes of exposure to arsenic is through drinking water. This review presents current information related to the distribution of arsenic in the environment, the resultant impacts on human health, especially related to diabetes, which is one of the most prevalent chronic diseases, regulation of arsenic in drinking water, and approaches for treatment of arsenic in drinking water for both public utilities and private wells. Taken together, this information points out the existing challenges to understanding both the complex health impacts of arsenic and to implementing the treatment strategies needed to effectively reduce arsenic exposure at different scales.

Longitudinal plasma magnesium status during pregnancy and the risk of gestational diabetes mellitus: a prospective cohort study

Emerging evidence has shown that magnesium (Mg) was associated with type 2 diabetes while few focused on abnormal glucose metabolism during pregnancy. The study is aimed at investigating the association between longitudinal changes in plasma Mg during pregnancy and subsequent risk of gestational diabetes (GDM) and exploring the possible influence of iron supplementation on the changes of plasma Mg levels. One thousand seven hundred fifty-six pregnant women from Tongji Maternal and Child Health Cohort (TMCHC) were involved. Blood samples were collected at gestational weeks 17.0 ± 0.9 and later 26.2 ± 1.4. Plasma Mg was measured by inductively coupled plasma mass spectrometry (ICP-MS) with decline rates calculated. Information on general characteristics and iron supplementation was collected by questionnaires. Oral glucose tolerance test (OGTT) was conducted at 24-28 gestational weeks to diagnose GDM. Poisson regression with robust error variance was used to estimate relative risks (RR) of GDM. Median concentrations of plasma Mg were 0.69 mmol/L and 0.63 mmol/L respectively at two collections. The prevalence of hypomagnesemia at the first collection was 73% and associated with a 1.59 (95%CI: 1.07, 2.37) fold risk of GDM. Adjusted RRs were 1.74 (95%CI: 1.06, 2.83) and 2.44 (95%CI: 1.54, 3.85) for women with hypomagnesemia and followed more tertile (T2 and T3 vs. T1) of Mg decrement. Iron supplementation above 30 mg/day was found associated with more Mg decrement (25.5% and 27.5% in T2 and T3 vs. 19.5% in T1). In conclusion, hypomagnesemia during pregnancy is prevalent and associated with increased GDM risk, especially in women followed by more plasma Mg decrement during pregnancy. High-dose iron supplementation may involve more plasma Mg decrement.

Cardiovascular Effects of Environmental Metal Antimony: Redox Dyshomeostasis as the Key Pathogenic Driver

Significance: Cardiovascular diseases (CVDs) are the leading cause of death worldwide, which may be due to sedentary lifestyles with less physical activity and over nutrition as well as an increase in the aging population; however, the contribution of pollutants, environmental chemicals, and nonessential metals to the increased and persistent CVDs needs more attention and investigation. Among environmental contaminant nonessential metals, antimony has been less addressed. Recent Advances: Among environmental contaminant nonessential metals, several metals such as lead, arsenic, and cadmium have been associated with the increased risk of CVDs. Antimony has been less addressed, but its potential link to CVDs is being gradually recognized. Critical Issues: Several epidemiological studies have revealed the significant deleterious effects of antimony on the cardiovascular system in the absence or presence of other nonessential metals. There has been less focus on whether antimony alone can contribute to the pathogenesis of CVDs and the proposed mechanisms of such possible effects. This review addresses this gap in knowledge by presenting the current available evidence that highlights the potential role of antimony in the pathogenesis of CVDs, most likely via antimony-mediated redox dyshomeostasis. Future Directions: More direct evidence from preclinical and mechanistic studies is urgently needed to evaluate the possible roles of antimony in mitochondrial dysfunction and epigenetic regulation in CVDs. Antioxid. Redox Signal. 38, 803-823.

A machine learning approach for early prediction of gestational diabetes mellitus using elemental contents in fingernails

The aim of this pilot study was to predict the risk of gestational diabetes mellitus (GDM) by the elemental content in fingernails and urine with machine learning analysis. Sixty seven pregnant women (34 control and 33 GDM patient) were included. Fingernails and urine were collected in the first and second trimesters, respectively. The concentrations of elements were determined by inductively coupled plasma-mass spectrometry. Logistic regression model was applied to estimate the adjusted odd ratios and 95% confidence intervals. The predictive performances of multiple machine learning algorithms were evaluated, and an ensemble model was built to predict the risk for GDM based on the elemental contents in the fingernails. Beryllium, selenium, tin and copper were positively associated with the risk of GDM while nickel and mercury showed opposite result. The trained ensemble model showed larger area under curve (AUC) of receiver operating characteristic curve (0.81) using fingernail Ni, Cu and Se concentrations. The model was validated by external data set with AUC = 0.71. In summary, the results of the present study highlight the potential of fingernails, as an alternative sample, together with machine learning in human biomonitoring studies.

Site-specific ecological effect assessment at community level for polymetallic contaminated soil

Current ecological risk assessment (ERA) is based more on book-keeping than on science especially for terrestrial ecosystems due to the lack of relevance to real field. Accordingly, site-specific ecological effect assessment is critical for ERA, especially at high tiers. This study developed procedures to assess ecological effect at community level based on field data. As a case study, we assessed ecological effect of polymetallic contamination in soil in the surrounding of an abandoned mining and smelting site in Hunan, China. Firstly, Zn was identified as the dominant contaminant in soil and slope gradient (SG) and pH as environmental impact factors using distance-based redundancy analysis(db-RDA). Secondly, sensitive endpoints were screened using correlation analysis between Zn and parameters of plant community composition and functional traits. Thirdly, exposure-effect curves between Zn and screened endpoints were developed by taking SG and pH as covariates using Bayesian kernel machine regression analysis (BKMR), based on which half-effect concentrations (EC₅₀s) and 10 %-effect concentrations (EC₁₀s) of soil Zn for each endpoint were calculated. Finally, site-specific hazardous concentrations (HC₅₀s) of Zn were estimated. It was revealed site-specific EC₅₀s and EC₁₀s for soil Zn ranged 80.5-201 mg kg^-1 and 342-893 mgkg^-1, respectively, and HC₅₀s based on EC₁₀s and EC₅₀s ranged 104-110 mg kg^-1 and 595-612 mg kg^-1, respectively, which are more specific and inclusive than those obtained based on crop and vegetable seed germination and seedling growth toxicity experiments.

Antimony oxidation and whole genome sequencing of Phytobacter sp. X4 isolated from contaminated soil near a flotation site

The conversion of the more toxic Sb(III) into less toxic Sb(V) is an effective strategy for the treatment of antimony-contaminated sites. In this study, a strain, Phytobacter sp. X4, which can tolerate high concentrations of antimony and can use nitrate as an electron acceptor for Sb(III) oxidation under anaerobic conditions, was isolated from the deep soil of an antimony mine flotation tailing. Unlike other antimony oxidizing bacteria, X4 oxidized better under high Sb(III) concentration, and the oxidation efficiency of 10 mM Sb(III) reached the maximum at 110 h with 61.8 %. Kinetic study showed X4 yielded a V_max of 1.093 μM∙min^-1 and a K_m of 718.2 μM. The genome of Phytobacter sp. X4 consists of a complete circular chromosome and two plasmids. In addition, X4 had more metal(loid)s resistance genes and highly expressed genes than other Phytobacter spp., reflecting its stronger adaptive advantage in harsh survival environments. We also analyzed the origin and evolution of arsB, arsC, and arsH, which may have been transferred horizontally from other species. iscR and arsH may have an important contribution to Sb(III) oxidation. Thus, Phytobacter sp. X4 has a good ability to remediate high antimony-contaminated sites and can be applied to an anaerobic environment.

Short-term impacts of air pollution on the platelet-lymphocyte ratio and neutrophil-lymphocyte ratio among urban adults in China

The short-term impacts of urban air pollution on the platelet-lymphocyte ratio (PLR) and neutrophil-lymphocyte ratio (NLR) remain obscure. In this study, we included 3487 urban adults from the Wuhan-Zhuhai cohort. Individual inhalation exposure to air pollutants was estimated by combining participants' daily breath volume and ambient concentrations of six air pollutants (including fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO) and ozone (O₃)). The cumulative impacts were assessed by applying lag structures of up to 7 days before the survey date. Associations of air pollutants with PLR and NLR were assessed using a linear mixed model and Bayesian kernel machine regression (BKMR) model. We found that PLR was negatively related to PM_2.5 (lag02-lag06), PM₁₀ (lag02-lag07), NO₂ (lag02-lag07), and SO₂ (lag03-lag05) and NLR was negatively related to PM₁₀ (lag05 and lag07). In the BKMR model, a negative joint association between the six-air-pollutant mixture and PLR and NLR was observed, whereas PM₁₀ and NO₂ appeared to be more important than the other pollutants in the mixture. The negative impact of air pollutants was stronger in males, participants with lower body mass index (< 24 kg/m²), those cooking meals at home, drinkers, and non-exercisers. In conclusion, short-term exposure to air pollutants is significantly related to PLR and NLR in peripheral blood. PLR and NLR may provide new insight into the molecular mechanism underlying the adverse health impact of air pollutants.

Arsenic and Diabetes Mellitus: A Putative Role for the Immune System

Diabetes mellitus (DM) is an enormous public health issue worldwide. Recent data suggest that chronic arsenic exposure is linked to the risk of developing type 1 and type 2 DM, albeit the underlying mechanisms are unclear. This review discusses the role of the immune system as a link to possibly explain some of the mechanisms of developing T1DM or T2DM associated with arsenic exposure in humans, animal models, and in vitro studies. The rationale for the hypothesis includes: (1) Arsenic is a well-recognized modulator of the immune system; (2) arsenic exposures are associated with increased risk of DM; and (3) dysregulation of the immune system is one of the hallmarks in the pathogenesis of both T1DM and T2DM. A better understanding of DM in association with immune dysregulation and arsenic exposures may help to understand how environmental exposures modulate the immune system and how these effects may impact the manifestation of disease.

Recent advances in the application of ionomics in metabolic diseases

Trace elements and minerals play a significant role in human health and diseases. In recent years, ionomics has been rapidly and widely applied to explore the distribution, regulation, and crosstalk of different elements in various physiological and pathological processes. On the basis of multi-elemental analytical techniques and bioinformatics methods, it is possible to elucidate the relationship between the metabolism and homeostasis of diverse elements and common diseases. The current review aims to provide an overview of recent advances in the application of ionomics in metabolic disease research. We mainly focuses on the studies about ionomic or multi-elemental profiling of different biological samples for several major types of metabolic diseases, such as diabetes mellitus, obesity, and metabolic syndrome, which reveal distinct and dynamic patterns of ion contents and their potential benefits in the detection and prognosis of these illnesses. Accumulation of copper, selenium, and environmental toxic metals as well as deficiency of zinc and magnesium appear to be the most significant risk factors for the majority of metabolic diseases, suggesting that imbalance of these elements may be involved in the pathogenesis of these diseases. Moreover, each type of metabolic diseases has shown a relatively unique distribution of ions in biofluids and hair/nails from patients, which might serve as potential indicators for the respective disease. Overall, ionomics not only improves our understanding of the association between elemental dyshomeostasis and the development of metabolic disease but also assists in the identification of new potential diagnostic and prognostic markers in translational medicine.

Associations between co-exposure to multiple metals and renal function: a cross-sectional study in Guangxi, China

The association between co-exposure to multiple metals and renal function is poorly understood. We aimed to evaluate the individual and joint effects of metal exposure on renal function in this study. We performed a cross-sectional study including 5828 participants in Guangxi, China, in 2019. Urine concentrations of 17 metals were detected by inductively coupled plasma mass spectrometry (ICP-MS). Logistic regression model and restricted cubic spline (RCS) were applied to investigate the association of individual metal exposure with renal dysfunction. Weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were used to assess the co-exposure effects of the metals. Participants with the highest quartile of urinary Cu were at 1.84-fold (95% confidence interval (CI): 1.20-2.87) increased risk of renal dysfunction compared with the lowest quartile. The highest quartiles of urinary Sr, Cs, V, Ba, and Se were associated with 0.27-fold (95% CI: 0.17-0.43), 0.33 (95% CI: 0.19-0.53), 0.41 (95% CI: 0.25-0.65), 0.58 (95% CI: 0.36-0.90), and 0.33 (95% CI: 0.19-0.56) decreased risk of renal dysfunction compared with their lowest quartile, respectively. Furthermore, urinary Ba and Cu were non-linearly correlated with renal dysfunction. The WQS analysis showed that mixed metal exposure was inversely associated with renal dysfunction (OR = 0.47, 95% CI: 0.35-0.62), and Sr accounted for the largest weight (52.2%), followed by Cs (32.3%) in the association. Moreover, we observed a potential interaction between Cu, Cs, and Ba for renal dysfunction in BKMR model. Exposure to Se, Sr, Cs, V, and Ba is associated with decreased risk of renal dysfunction, whereas an increased risk is associated with Cu exposure. Co-exposure to these metals is negatively associated with renal dysfunction, and Sr and Cs are the main contributors to the associations.

Association between Plasma Trace Element Concentrations in Early Pregnancy and Gestational Diabetes Mellitus in Shanghai, China

(1) Background: Trace elements play important roles in gestational diabetes mellitus (GDM), but the results from reported studies are inconsistent. This study aimed to examine the association between maternal exposure to V, Cr, Mn, Co, Ni, and Se in early pregnancy and GDM. (2) Methods: A nested case-control study with 403 GDM patients and 763 controls was conducted. Trace elements were measured using inductively coupled plasma-mass spectrometry in plasma collected from pregnant women in the first trimester of gestation. We used several statistical methods to explore the association between element exposure and GDM risk. (3) Results: Plasma V and Ni were associated with increased and decreased risk of GDM, respectively, in the single-element model. V and Mn were found to be positively, and Ni was found to be negatively associated with GDM risk in the multi-element model. Mn may be the main contributor to GDM risk and Ni the main protective factor against GDM risk in the quantile g computation (QGC). 6.89 μg/L~30.88 μg/L plasma Ni was identified as a safe window for decreased risk of GDM. (4) Conclusions: V was positively associated with GDM risk, while Ni was negatively associated. Ni has dual effects on GDM risk.

Association of serum per- and polyfluoroalkyl substances and gestational anemia during different trimesters in Zhuang ethnic pregnancy women of Guangxi, China

BACKGROUND

Gestational anemia is a complication of pregnancy, and a low level of hemoglobin (Hb) has been linked to adverse pregnancy outcomes. Previous studies reported that PFASs were more strongly associated with Hb than red blood cells, indicating that Hb is more susceptible to the effect of PFASs. However, the evidences regarding the effects of per- and polyfluoroalkyl substances (PFASs) on gestational anemia are currently limited. Therefore, it is important to explore the effects of PFASs on anemia in Chinese pregnant women.

METHODS

A total of 821 pregnant women were recruited between June 2015 and April 2019 in the Guangxi Zhuang Birth Cohort. The concentrations of PFASs were assessed in maternal serum before 12 gestational weeks. To determine both individual and combined associations of PFASs exposure with anemia in the three stages of pregnancy, binary logistic regression, Bayesian kernel machine regression (BKMR), and weighted quantile sum (WQS) regression models were employed.

RESULTS

In single-pollutant analysis, maternal exposure to perfluorododecanoic acid (PFDoA) and perfluoroheptanoic acid (PFHpA) were associated with anemia in the first trimester, exposure to PFHpA and perfluorobutanesulfonic acid (PFBS) were associated with anemia in the second trimester, and exposure to perfluorodecanoic acid (PFDA) and perfluorononanoic acid (PFNA) were associated with anemia in the third trimester. Notably, perfluoroundecanoic acid (PFUnA) had a nonlinear association with anemia in the third trimester. In multiple-pollutant analysis, a positive association of PFDoA with anemia in the first trimester and a negative association of PFBS with anemia in the second trimester were confirmed by BKMR. Exposure to PFASs mixture was not associated with anemia in all three trimesters. In WQS, there was a significantly negative association between the PFAS mixture and anemia in the second trimester.

CONCLUSION

Maternal exposure to PFASs is associated with gestational anemia in different trimesters.

Plasma Manganese Levels and Risk of Gestational Diabetes Mellitus: A Prospective Cohort Study

Manganese (Mn) intake has been found to be linked with risk of type 2 diabetes. However, the role of Mn in the development of gestational diabetes mellitus (GDM) remains to be investigated. This prospective study included pregnant women from the Tongji Maternal and Child Health Cohort. A total of 2327 participants with plasma specimens before 20 weeks were included. Among the pregnant women, 9.7% (225/2327) were diagnosed with GDM. After adjustment, pregnant women with the third and highest quartile of plasma Mn levels had 1.31-fold (RR, 2.31 [1.48, 3.61]) and 2.35-fold (RR, 3.35 [2.17, 5.17]) increased risk of GDM compared with those with the lowest quartile. A 1 standard deviation increment of ln-transformed plasma Mn levels (0.53 μg/L) was related to elevated risks of GDM with RRs of 1.28 [1.17, 1.40]. The positive associations between Mn and GDM remained consistent in all the subgroups. The weighted quantile sum index was significantly related to GDM (RR, 1.60 [1.37, 1.86]). The contribution of Mn (58.69%) to the metal mixture index was the highest related to GDM. Higher plasma Mn levels were found to be linked with elevated fasting and 2 h post-load blood glucose. This study revealed relationships of higher plasma Mn levels in early pregnancy and increased risk of GDM, suggesting that though essential, excess Mn in the body might be a potential important risk factor for GDM.

Cadmium exposure and the risk of GDM: evidence emerging from the systematic review and meta-analysis

Gestational diabetes mellitus (GDM) has become a global concern for its severe adverse effects on both mother and fetus. Recent epidemiological studies reported inconsistent results of the association between cadmium (Cd) exposure and GDM. Therefore, a systematic review and meta- analysis were performed. PubMed, Web of Science, Scopus, Embase, and SpringerLink were searched up to July 2021. Observational studies containing the adjusted relative risks between Cd exposure and GDM were included in the quantitative synthesis. The retrieval comprised 218 articles out of which 11 met our criteria and 9 were included in the meta-analysis, representing a total of 32,392 subjects (2881 GDM). In total, Cd exposure might increase the risk of GDM in some extent (OR = 1.21, 95% CI [0.89, 1.64]), even without statistical significance in high heterogeneity (Q = 28.45, p < 0.05, I² = 71.9%). Filtering two outliers indicated by Galbraith plot yielded a similar risk (OR = 1.19, 95% CI [1.02, 1.39]) with statistical significance. However, the heterogeneity among studies was obviously reduced (Q = 11.75, p = 0.068, I² = 48.9%). Additionally, biological specimen, study design, and diagnostic criteria contributed to the high heterogeneity according to the subgroup analysis. Since some important results do not deny that Cd exposure increases the risk of GDM, high-quality multi-centered large cohort studies are required in the future.

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

Trace elements are micronutrients that are required in very small quantities through diet but are crucial for the prevention of acute and chronic diseases. Despite the fact that initial studies demonstrated inverse associations between some of the most important essential trace elements (Zn, Cu, Se, and Mn) and cardiovascular disease, several recent studies have reported a direct association with cardiovascular risk factors due to the fact that these elements can act as both antioxidants and pro-oxidants, depending on several factors. This study aims to investigate the association between plasma and urine concentrations of trace elements and cardiovascular risk factors in a general population from the Mediterranean region, including 484 men and women aged 18−80 years and considering trace elements individually and as joint exposure. Zn, Cu, Se, and Mn were determined in plasma and urine using an inductively coupled plasma mass spectrometer (ICP-MS). Single and combined analysis of trace elements with plasma lipid, blood pressure, diabetes, and anthropometric variables was undertaken. Principal component analysis, quantile-based g-computation, and calculation of trace element risk scores (TERS) were used for the combined analyses. Models were adjusted for covariates. In single trace element models, we found statistically significant associations between plasma Se and increased total cholesterol and systolic blood pressure; plasma Cu and increased triglycerides and body mass index; and urine Zn and increased glucose. Moreover, in the joint exposure analysis using quantile g-computation and TERS, the combined plasma levels of Zn, Cu, Se (directly), and Mn (inversely) were strongly associated with hypercholesterolemia (OR: 2.03; 95%CI: 1.37−2.99; p < 0.001 per quartile increase in the g-computation approach). The analysis of urine mixtures revealed a significant relationship with both fasting glucose and diabetes (OR: 1.91; 95%CI: 1.01−3.04; p = 0.046). In conclusion, in this Mediterranean population, the combined effect of higher plasma trace element levels (primarily Se, Cu, and Zn) was directly associated with elevated plasma lipids, whereas the mixture effect in urine was primarily associated with plasma glucose. Both parameters are relevant cardiovascular risk factors, and increased trace element exposures should be considered with caution.

Co-exposure to multiple air pollutants and sleep disordered breathing in patients with or without obstructive sleep apnea: A cross-sectional study

BACKGROUND

Air pollution may be a contributing risk factor for obstructive sleep apnea (OSA). However, the health effects of co-exposure to multiple air pollutants on OSA patients remain unclear.

OBJECTIVES

To assess the joint effect of multi-pollutant on sleep disordered breathing (SDB) parameters in patients with or without OSA and identify the dominant pollutants.

METHODS

A total of 2524 outpatients from April 2020 to May 2021 were recruited in this cross-sectional study. Ambient air pollutant data were obtained from the nearest central monitoring stations to participants' residential address. SDB parameters were measured by the ApneaLink devices, including apnea-hypopnea index (AHI), hypopnea index (HI), oxygen desaturation index (ODI), average oxygen saturation (SpO₂), percentage sleep time with <90% saturation (T90), and desaturation. Bayesian kernel machine regression (BKMR) was applied to evaluate the effects of multiple pollutants.

RESULTS

Significant associations were observed between air pollutants and SDB parameters (including increases in AHI, HI, ODI, and desaturation) among patients with OSA. Co-exposure to air pollutants was positively correlated with AHI, HI, and ODI. PM₁₀ and O₃ dominated the effects of pollutant mixtures on OSA, with the highest posterior inclusion probability (PIP) values of 0.592 and 0.640, respectively. Stratified analysis showed that, compared to male patients with OSA, stronger effects on the SDB parameters were observed in female patients. Stronger associations were also found in the warm season than those in the cold season.

CONCLUSION

Co-exposure to air pollutants was associated with SDB parameters among patients with OSA, PM₁₀ and O₃ might play the dominant roles.

Association of urinary or blood heavy metals and mortality from all causes, cardiovascular disease, and cancer in the general population: a systematic review and meta-analysis of cohort studies

Amounting epidemiological evidence has shown detrimental effects of heavy metals on a wide range of diseases. However, the effect of heavy metal exposure on mortality in the general population remains unclear. The primary objective of this study was to clarify the associations between heavy metals and mortality from all causes, cardiovascular disease (CVD), and cancer based on prospective studies. We comprehensively searched Pubmed, Embase, and Web of Science electronic databases to identify studies published from their inception until 1 March 2022. Investigators identified inclusion criteria, extracted study characteristics, and assessed the methodological quality of included studies according to standardized guidelines. Meta-analysis was conducted if the effect estimates of the same outcome were reported in at least three studies. Finally, 42 original studies were identified. The results of meta-analysis showed that cadmium and lead exposure was significantly associated with mortality from all causes, CVD, and cancer in the general population. Moderate evidence suggested there was a link between arsenic exposure and mortality. The adverse effects of mercury and other heavy metals on mortality were inconclusive. Epidemiological evidence for the joint effect of heavy metal exposure on mortality was still indeterminate. In summary, our study provided compelling evidence that exposure to cadmium, lead, and arsenic were associated with mortality from all causes, CVD, and cancer, while the evidence on other heavy metals, for example mercury, was insignificant or indeterminate. Nevertheless, further prospective studies are warranted to explore the joint effects of multiple metal exposure on mortality.

Environmental health influences in pregnancy and risk of gestational diabetes mellitus: a systematic review

Background

Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications globally. Environmental risk factors may lead to increased glucose levels and GDM, which in turn may affect not only the health of the mother but assuming hypotheses of "fetal programming", also the health of the offspring. In addition to traditional GDM risk factors, the evidence is growing that environmental influences might affect the development of GDM. We conducted a systematic review analyzing the association between several environmental health risk factors in pregnancy, including climate factors, chemicals and metals, and GDM.

Methods

We performed a systematic literature search in Medline (PubMed), EMBASE, CINAHL, Cochrane Library and Web of Science Core Collection databases for research articles published until March 2021. Epidemiological human and animal model studies that examined GDM as an outcome and / or glycemic outcomes and at least one environmental risk factor for GDM were included.

Results

Of n = 91 studies, we classified n = 28 air pollution, n = 18 persistent organic pollutants (POP), n = 11 arsenic, n = 9 phthalate n = 8 bisphenol A (BPA), n = 8 seasonality, n = 6 cadmium and n = 5 ambient temperature studies. In total, we identified two animal model studies. Whilst we found clear evidence for an association between GDM and air pollution, ambient temperature, season, cadmium, arsenic, POPs and phthalates, the findings regarding phenols were rather inconsistent. There were clear associations between adverse glycemic outcomes and air pollution, ambient temperature, season, POPs, phenols, and phthalates. Findings regarding cadmium and arsenic were heterogeneous (n = 2 publications in each case).

Conclusions

Environmental risk factors are important to consider in the management and prevention of GDM. In view of mechanisms of fetal programming, the environmental risk factors investigated may impair the health of mother and offspring in the short and long term. Further research is needed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13965-5.

Co-exposure to priority-controlled metals mixture and blood pressure in Chinese children from two panel studies

Metals may affect adversely cardiovascular system, but epidemiological evidence on the associations of priority-controlled metals including antimony (Sb), arsenic (As), cadmium, lead, and thallium with children's blood pressure (BP) was scarce and inconsistent. We conducted two panel studies with 3 surveys across 3 seasons among 144 and 142 children aged 4-12 years in Guangzhou and Weinan, respectively. During each seasonal survey, urine samples were collected for 4 consecutive days and BP was measured on the 4th day. We obtained 786 BP values and urinary metals measurements at least once within 4 days, while 773, 596, 612, and 754 urinary metals measurements were effective on the health examination day (Lag 0), and the 1^st, 2^nd, and 3^rd day preceding BP measurement (Lag 1, lag 2 and lag 3), respectively. We used linear mixed-effect models, generalized estimating equations and multiple informant models to assess the associations of individual metal at each lag day and accumulated lag day (4 days averaged, lag 0-3) with BP and hypertension, and Bayesian Kernel Machine Regression to evaluate the relations of metals mixture at lag 0-3 and BP outcomes. We found Sb was positively and consistently related to systolic BP (SBP), mean arterial pressure (MAP), and odds of having hypertension within 4 days, which were the strongest at lag 0 and declined over time. And such relationships at lag 0-3 showed in a dose-response manner. Meanwhile, Sb was the only contributor to the relations of mixture with SBP, MAP, and odds of having hypertension. Also, synergistic interaction between Sb and As was significant. In addition, modification effect of passive smoking status on the association of Sb and SBP was more evident in passive smokers. Accordingly, urinary Sb was consistently and dose-responsively associated with increased BP and hypertension, of which Sb was the major contributor among children.