Abnormal erythrocyte-related parameters in children with Pb, Cr, Cu and Zn exposure.

The link between exposure to a particular heavy metal or metalloid and the development of anemia is well established. However, the association between combined exposure to multiple heavy metal(loid)s and anemia in children is still lacking in evidence. In this study, a total of 266 children aged 3 to 7 were recruited from Guiyu, China. Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure blood heavy metal(loid) concentrations. Blood cell count, hemoglobin (HGB), mean corpuscular hemoglobin (MCH), mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), hematocrit (HCT), and red blood cell distribution width (RDW) were measured by an automated hematology analyzer. Erythrocyte-related parameters were negatively correlated with the Cu and Cu/Zn ratios and positively correlated with Cr, Ni, Zn, and Se by Spearman correlation analysis. Only blood Cu level was negatively correlated with HGB [ß = -2.74, (95% Cl: -4.49, -0.995)], MCH [ß = -0.505, (95% Cl: -0.785, -0.226)], MCV [ß = -1.024, (95% Cl: -1.767, -0.281)], and MCHC [ß = -2.137, (95% Cl: -3.54, -0.734)] by multiple linear regression analysis. The Bayesian Kernel Machine Regression (BKMR) model analysis indicated a negative correlation between the combined exposure to Cu, Zn, Pb, and Cr and MCH and MCV. The single-factor analysis showed a considerable statistical difference only with Cu on MCV, MCH, and HGB. Furthermore, the interaction analysis highlighted the interdependent effects of Cu and Zn, Pb and Zn, and Cr and Zn on MCH and MCV levels. Additionally, the oxidation and/or antioxidation reactions may play a significant role in the development of metal(loid)-induced anemia risk. It is crucial to investigate the effects of co-exposure to multiple heavy metal(loid) elements on anemia, especially the interrelationships and mechanisms among them.

Ultrafine particulate matter exposure during second year of life, but not before, associated with increased risk of autism spectrum disorder in BKMR mixtures model of multiple air pollutants.

Prenatal and early postnatal air pollution exposures have been shown to be associated with autism spectrum disorder (ASD) risk but results regarding specific air pollutants and exposure timing are mixed and no study has investigated the effects of combined exposure to multiple air pollutants using a mixtures approach. We aimed to evaluate prenatal and early life multipollutant mixtures for the drivers of associations of air pollution with ASD. This study examined 484 typically developing (TD) and 660 ASD children from the CHARGE case-control study. Daily air concentrations for NO2, O3, ultrafine (PM0.1), fine (PM0.1-2.5), and coarse (PM2.5-10) particles were predicted from chemical transport models with statistical bias adjustment based on ground-based monitors. Daily averages were calculated for each exposure period (pre-pregnancy, each trimester of pregnancy, first and second year of life) between 2000 and 2016. Air pollution variables were natural log-transformed and then standardized. Individual and joint effects of pollutant exposure with ASD, and potential interactions, were evaluated for each period using hierarchical Bayesian Kernel Machine Regression (BKMR) models, with three groups: PM size fractions (PM0.1, PM0.1-2.5, PM2.5-10), NO2, and O3. In BKMR models, the PM group was associated with ASD in year 2 (group posterior inclusion probability (gPIP) = 0.75), and marginally associated in year 1 (gPIP = 0.497). PM2.5-10 appeared to drive the association (conditional PIP (cPIP) = 0.64) in year 1, while PM0.1 appeared to drive the association in year 2 (cPIP = 0.76), with both showing a moderately strong increased risk. Pre-pregnancy O3 showed a slight J-shaped risk of ASD (gPIP = 0.55). No associations were observed for exposures during pregnancy. Pre-pregnancy O3 and year 2 p.m.0.1 exposures appear to be associated with an increased risk of ASD. Future research should examine ultrafine particulate matter in relation to ASD.

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 ß-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.

Pre-pregnancy ozone and ultrafine particulate matter exposure during second year of life associated with decreased cognitive and adaptive functioning at aged 2-5 years.

BACKGROUND: This study sought to investigate the association of prenatal and early life exposure to a mixture of air pollutants on cognitive and adaptive outcomes separately in children with or without autism spectrum disorder (ASD). METHODS: Utilizing data from the CHARGE case-control study (birth years: 2000-2016), we predicted daily air concentrations of NO2, O3, and particulate matter <0.1 µm (PM0.1), between 0.1 and 2.5 µm (PM0.1-2.5), and between 2.5 and 10 µm (PM2.5-10) using chemical transport models with ground-based monitor adjustments. Exposures were evaluated for pre-pregnancy, each trimester, and the first two years of life. Individual and combined effects of pollutants were assessed with Vineland Adaptive Behavior Scales (VABS) and Mullen Scales of Early Learning (MSEL), separately for children with ASD (n = 660) and children without ASD (typically developing (TD) and developmentally delayed (DD) combined; n = 753) using hierarchical Bayesian Kernel Machine Regression (BKMR) models with three groups: PM size fractions (PM0.1, PM0.1-2.5, PM2.5-10), NO2, and O3. RESULTS: Pre-pregnancy Ozone was strongly negatively associated with all scores in the non-ASD group (group posterior inclusion probability (gPIP) = 0.83-1.00). The PM group during year 2 was also strongly negatively associated with all scores in the non-ASD group (gPIP = 0.59-0.93), with PM0.1 driving the group association (conditional PIP (cPIP) = 0.73-0.96). Weaker and less consistent associations were observed between PM0.1-2.5 during pre-pregnancy and ozone during year 1 and VABS scores in the ASD group. CONCLUSIONS: These findings prompt further investigation into ozone and ultrafine PM as potential environmental risk factors for neurodevelopment.

Joint association of heavy metals and polycyclic aromatic hydrocarbons exposure with depression in adults.

BACKGROUND: Heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs) represent significant components of environmental pollution, typically occurring as mixtures, raising concerns about their potential impact on human health. However, the combined effect of HMs and PAHs exposure on depression has not been explored. METHODS: Leveraging National Health and Nutrition Examination Survey (NHANES) data spanning 2005 to 2016, we employ survey-weighted multiple logistic regression models to probe the interrelation between HMs, PAHs, and depression. This exploration is complemented by age and gender-stratified analyses, as well as a determination of the dose-response linkage via restricted cubic spline regression. Furthermore, the combined impact of HMs and PAHs on depression was evaluated through a range of statistical methodologies. RESULTS: The study encompasses 7732 adults. Our findings unveil notable associations, indicating the significant influence of cadmium (Cd), lead (Pb), and all six PAHs metabolites on depression. Moreover, mixed exposure to HMs and PAHs emerges as a substantial contributor to an augmented depression risk, with Cd, Pb, 1-hydroxynaphthalene (1-NAP), 2-hydroxyfluorene (2-FLU), and 1-hydroxypyrene (1-PYR) likely driving this positive relationship. Intriguingly, subgroup analyses highlight greater prominence of these connections among individuals aged 20-59 and among women. Furthermore, the results tentatively suggest a potential interplay between Cd and 2-NAP in relation to depression. CONCLUSION: This study posits that exposure to both individual and combined HMs and PAHs may be associated with an elevated risk of depression. Further prospective investigations are warranted to substantiate these findings.

Association between maternal metal exposure during early pregnancy and intelligence in children aged 3-6 years: Results from a Chinese birth cohort.

OBJECTIVE: Maternal environmental metal exposure is common, but long-term prospective epidemiological evidence of its impact on children's intellectual development is still insufficient. METHODS: Data on maternal plasma metal levels and child intelligence were obtained for 211 3-6-year-old children from Guangxi Zhuang Birth Cohort. ICP-MS was employed to detect 17 metals, including 7 essential metals (Mn, Fe, Co, Ni, Cu, Zn, Mo) and 10 non-essential metals (As, Rb, Sr, Cd, Sb, Cs, Ba, W, Pb, U), in maternal plasma samples obtained before 13 weeks of gestation during the initial maternity checkup. Child intelligence was assessed using the Wechsler Intelligence Scale for Children-Fourth Edition. The GLM, RCS and mixture models were used to assess the associations of maternal plasma metal levels with child intelligence quotient (IQ) scores. RESULTS: The GLM analysis revealed that U had a significant adverse effect on child IQ scores in high-dose exposure groups (-9.236 [-18.644, -4.936], p = 0.006) after adjusting for covariates, while Sb showed a linear adverse effect on children's intelligence in the adjusted model (-4.028 [-7.432, -0.626], p = 0.021). BKMR modeling indicated that overall IQ scores decreased as concentrations of non-essential metals mixtures increased after adjusting for essential metal mixtures, consistent with findings from the WQS (ß [95% CI], -8.463 [-14.449, -2.476], p = 0.007) and Qgcomp models (-7.003 [-12.928, -1.078], p = 0.022). Among the non-essential metals, U had the highest negative weight at 37.96%, followed by Pb (23.35%) and Sb (16.91%). Furthermore, potential interactions were observed between metals (Pb and U) and Sb in the study findings. CONCLUSION: Reducing exposure to non-essential metal mixtures, especially U, Sb and Pb, during early pregnancy and ensuring adequate intake of specific essential metal elements could be a critical intervention in addressing childhood intellectual impairment.

Associations between exposure to pesticides mixture and semen quality among the non-occupationally exposed males: Four statistical models.

Most epidemiological studies on the associations between pesticides exposure and semen quality have been based on a single pesticide, with inconsistent major results. In contrast, there was limited human evidence on the potential effect of pesticides mixture on semen quality. Our study aimed to investigate the relationship of pesticide profiles with semen quality parameters among 299 non-occupationally exposed males aged 25-50 without any clinical abnormalities. Serum concentrations of 21 pesticides were quantified by gas chromatography-tandem mass spectrometry (GC-MS/MS). Semen quality parameters were abstracted from medical records. Generalized linear regression models (GLMs) and three mixture approaches, including weighted quantile sum regression (WQS), elastic net regression (ENR) and Bayesian kernel machine regression (BKMR), were applied to explore the single and mixed effects of pesticide exposure on semen quality. In GLMs, as the serum levels of Bendiocarb, ß-BHC, Clomazone, Dicrotophos, Dimethenamid, Paclobutrazole, Pentachloroaniline and Pyrimethanil increased, the straight-line velocity (VSL), linearity (LIN) and straightness (STR) decreased. This negative association also occurred between the concentration of ß-BHC, Pentachloroaniline, Pyrimethanil and progressive motility, total motility. In the WQS models, pesticides mixture was negatively associated with total motility and several sperm motility parameters (ß: -3.07∼-1.02 per decile, FDR-P<0.05). After screening the important pesticides derived from the mixture by ENR model, the BKMR models showed that the decreased qualities for VSL, LIN, and STR were also observed when pesticide mixtures were at ≥ 70th percentiles. Clomazone, Dimethenamid, and Pyrimethanil (Posterior inclusion probability, PIP: 0.2850-0.8900) were identified as relatively important contributors. The study provides evidence that exposure to single or mixed pesticide was associated with impaired semen quality.

Association between organophosphorus insecticides exposure and osteoarthritis in patients with arteriosclerotic cardiovascular disease.

BACKGROUND: Organic phosphorus insecticides (OPPs) are a class of environmental pollutants widely used worldwide with potential human health risks. We aimed to assess the association between exposure to OPPs and osteoarthritis (OA) particularly in participants with atherosclerotic cardiovascular disease (ASCVD). METHODS: Participants' information was obtained from data in the National Health and Nutrition Examination (NHANES). Weighted logistic regression models were utilized to detect associations between OPPs metabolites and OA. Restricted cubic spline plots (RCS) were drawn to visualize the dose-response relationship between each metabolite and OA prevalence. Weighted quantile sum (WQS) regression and Bayesian kernel-machine regression (BKMR), were applied to investigate the joint effect of mixtures of OPPs on OA. RESULTS: A total of 6871 samples were included in our study, no significant associations between OPPs exposure and OA incidence were found in whole population. However, in a subset of 475 individuals with ASCVD, significant associations between DMP (odds ratio [OR] as a continuous variable = 1.22, 95% confidence interval [CI]: 1.07,1.28), DEP ((odds ratio [OR] of the highest tertile compared to the lowest = 2.43, 95% confidence interval [CI]: 1.21,4.86), and OA were observed. DMP and DEP showed an increasing dose-response relationship to the prevalence of OA, while DMTP, DETP, DMDTP and DEDTP showed a nonlinear relationship. Multi-contamination modeling revealed a 1.34-fold (95% confidence intervals:0.80, 2.26) higher prevalence of OA in participants with high co-exposure to OPPs compared to those with low co-exposure, with a preponderant weighting (0.87) for the dimethyl dialkyl phosphate metabolites (DMAPs). The BKMR also showed that co-exposure of mixed OPPs was associated with an increased prevalence of OA, with DMP showing a significant dose-response relationship. CONCLUSION: High levels of urine dialkyl phosphate metabolites (DAP) of multiple OPPs are associated with an increased prevalence of OA in patients with ASCVD, suggesting the need to prevent exposure to OPPs in ASCVD patients to avoid triggering OA and further avoid the occurrence of cardiovascular events caused by OA.

Elevated levels of Zn, Cu and Co are associated with an increased risk of endometriosis: Results from a casecontrol study.

BACKGROUND: Endometriosis is a common gynecological disease that affects approximately 5 %∼10 % of reproductive-aged women. Zinc (Zn), selenium (Se), copper (Cu), cobalt (Co) and molybdenum (Mo) are essential trace elements and are very important for human health. However, studies on the relationship between mixtures of essential trace elements and the risk of endometriosis are limited and inconsistent. In particular, studies confirming the association via different sample types are limited. OBJECTIVE: This study aimed to investigate the associations between Zn, Se, Cu, Co and Mo concentrations in blood and follicular fluid (FF) and endometriosis risk in a Chinese population. METHODS: A total of 609 subjects undergoing in vitro fertilization (IVF) were recruited; 836 samples were analyzed, including 451 blood samples (234 controls and 217 cases) and 385 FF samples (203 controls and 182 cases). In addition, 227 subjects provided both blood and FF samples. Zn, Se, Cu, Co and Mo concentrations in blood and FF were quantified via inductively coupled plasma-mass spectrometry (ICP-MS). The associations between the levels of Zn, Se, Cu, Co and Mo and the risk of endometriosis were assessed using single-element models (logistic regression models), and the combined effect of the trace elements on endometriosis risk was assessed using multielement models (Bayesian kernel machine regression (BKMR) and weighted quantile sum (WQS) regression). RESULTS: Based on the single-element models, significant associations of Zn concentrations in blood (high-level vs. low-level group: aOR = 14.17, 95 % CI: 7.31, 27.50) and FF (first tertile vs. second tertile group: aOR = 0.34, 95 % CI: 0.16, 0.71; third tertile vs. second tertile group: aOR = 2.32, 95 % CI: 1.38, 3.91, respectively) and Co concentrations in blood (first tertile vs. second tertile group, aOR = 0.24, 95 % CI: 0.12, 0.48) and FF (third tertile vs. second tertile group: aOR = 3.87, 95 % CI: 2.19, 6.84) with endometriosis risk were found after adjustment for all confounders. In FF, Cu and Mo levels were significantly greater among the cases than among the controls, with a positive association with endometriosis risk (Cu (first tertile vs. second tertile group: aOR = 0.39, 95 % CI: 0.19, 0.81; third tertile vs. second tertile group: aOR = 2.73, 95 % CI: 1.61, 4.66, respectively) and Mo (high-level vs. low-level group: aOR = 14.93, 95 % CI: 7.16, 31.12)). However, similar associations between blood Cu and Mo levels and endometriosis risk were not found. In addition, the levels of these five essential trace element mixtures in blood and in FF were significantly and positively associated with endometriosis risk according to the BKMR analyses; the levels of Zn and Cu in blood and the levels of Mo in FF were significantly related to the risk of endometriosis, and the posterior inclusion probabilities (PIPs) were 1.00, 0.99 and 1.00 for Zn and Cu levels in blood and Mo levels in FF, respectively. Furthermore, Zn and Mo were the highest weighted elements in blood and FF, respectively, according to WQS analyses. CONCLUSION: The risk of endometriosis was associated with elevated levels of several essential trace elements (Zn, Cu and Co). Elevated levels of these elements may be involved in the pathomechanism of endometriosis. However, further studies with larger sample sizes will be necessary to confirm these associations.

Associations between multiple metal exposure and fertility in women: A nested case-control study.

Metal pollution can cause a decline in female fertility, however, previous studies have focused more on the effect of a single metal on fertility. In this study, we evaluated the effect of metal mixtures on female fertility based on nested case-control samples. The plasma levels of 22 metal elements from 180 women were determined by an inductively coupled plasma mass spectrometer (ICP-MS). Minimum absolute contraction and selection operator (LASSO) penalty regression selected metals with the greatest influence on clinical outcome. Logistic regression was used to analyze the correlation between single metals and fertility while a Bayesian kernel function regression (BKMR) model was used to analyze the effect of mixed metals. Eight metals (Calcium (Ca), Chromium (Cr), Cobalt (Co), Copper (Cu), Zinc (Zn), Rubidium (Rb), Strontium (Sr) and Zirconium (Zr)) were selected by LASSO regression for subsequent analysis. After adjusting for covariates, the logistic model showed that Cu (Odds Ratio(OR):0.33, 95% CI: 0.13 - 0.84) and Co (OR:0.38, 95% CI: 0.15 -0.94) caused a significant reduction in fertility, and identified the protective effect of Zn (OR: 2.96, 95% CI:1.21 -7.50) on fertility. Trend tests showed that increased Cr, Cu, and Rb levels were associated with reduced fertility. The BKMR model showed that Cr, Co, Cu, and Rb had a nonlinear relationship with fertility decline when controlling for the concentrations of other metals and suggested that Cu and Cr might exert an influence on fertility. Analysis showed a negative correlation between Cu, Cr, Co, Rb, and fertility, and a positive correlation between Zn and fertility. Furthermore, we found evidence for the interaction between Cu and Cr. Our findings require further validation and may identify new mechanisms in the future.

Association of co-exposure to organophosphate esters and per- and polyfluoroalkyl substances and mixture with cardiovascular-kidney-liver-metabolic biomarkers among Chinese adults.

BACKGROUND: Organophosphate esters (OPEs) and Per- and polyfluoroalkyl substances (PFAS) are ubiquitous environmental contaminants with common exposure sources, leading to their widespread presence in human body. However, evidence on co-exposure to OPEs and PFAS and its impact on cardiovascular-kidney-liver-metabolic biomarkers remains limited. METHODS: In this cross-sectional study, 467 adults were enrolled from January to May 2022 during physical visits in Shijiazhuang, Hebei province. Eleven types of OPEs and twelves types of PFAS were detected, among which eight OPEs and six PFAS contaminants were detected in more than 60% of plasma samples. Seventeen biomarkers were assessed to comprehensively evaluate the cardiovascular-kidney-liver-metabolic function. Multiple linear regression, multipollutant models with sparse partial least squares, and Bayesian kernel machine regression (BKMR) models were applied to examine the associations of individual OPEs and PFAS and their mixtures with organ function and metabolism, respectively. RESULTS: Of the over 400 exposure-outcome associations tested when modelling, we observed robust results across three models that perfluorohexanoic acid (PFHxS) was significantly positively associated with alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), and indirect bilirubin (IBIL). Perfluorononanoic acid was significantly associated with decreased AST/ALT and increased very-low-density lipoprotein cholesterol levels. Besides, perfluorodecanoic acid was correlated with increased high lipoprotein cholesterol and perfluoroundecanoic acid was consistently associated with lower glucose level. BKMR analysis showed that OPEs and PFAS mixtures were positively associated with IBIL and TBIL, among which PFHxS was the main toxic chemicals. CONCLUSIONS: Our findings suggest that exposure to OPEs and PFAS, especially PFHxS and PFNA, may disrupt organ function and metabolism in the general population, providing insight into the potential pathophysiological mechanisms of OPEs and PFAS co-exposure and chronic diseases.

Association between mixed metal exposure and stroke risk in Shanxi Province: a case-control study.

BACKGROUND: Stroke is the second leading cause of death for all human beings and poses a serious threat to human health. Environmental exposure to a mixture of metals may be associated with the occurrence and development of stroke, but the evidence in the Chinese population is not yet conclusive. OBJECTIVES: This study evaluated the association between stroke risk and 13 metals METHODS: Metal concentrations in whole blood samples from 100 stroke cases and 100 controls were measured by ICP-MS. The cumulative impact of mixed metal on stroke risk was investigated by using three statistical models, BKMR, WQS and QGC. RESULTS: The case group had higher concentrations of Mg, Mn, Zn, Se, Sn, and Pb than the control group (p<0.05). BKMR model indicated a correlation between the risk of stroke and exposure to mixed metals. WQS model showed that Mg (27.2 %), Se (25.1 %) and Sn (14.8 %) were positively correlated with stroke risk (OR=1.53; 95 %Cl: 1.03-2.37, p=0.013). The QGC model showed that Mg (49.2 %) was positively correlated with stroke risk, while Ti (31.7 %) was negatively correlated with stroke risk. CONCLUSIONS: Mg may be the largest contributor to the cumulative effect of mixed metal exposure on stroke risk, and the interaction between metals requires more attention. These findings could provide scientific basis for effectively preventing stroke by managing metals in the environment.

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.

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.

The effect of low-level phthalate mixture on the prevalence of type 2 diabetes mellitus among adults in the US.

Type 2 diabetes mellitus (T2DM) is an important public health issue owing to its rising global prevalence. Phthalates cause various health problems and are currently regulated in developed countries. However, studies on the impacts of low-level phthalate exposure under these regulations on T2DM are limited. This study investigated the impacts of combined and single exposures to phthalates and their alternatives on the prevalence of T2DM in 3,005 adults in the United States. The results indicated a positive joint effect of phthalate mixtures on the prevalence of T2DM. The joint effect was primarily attributed to Di-2-ethylhexyl phthalate (DEHP) metabolites, whereas the contributions of others were limited. This study suggests that, despite the stringent regulations on phthalates, low levels of phthalates, including DEHP, still have joint effects on T2DM. The findings highlight the importance of regulating hazardous phthalates and the need for safer alternatives to reduce public health risks.

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.

Associations of toxic metals and their mixture with hyperuricemia in Chinese rural older adults.

Previous studies have related single toxic metals (TMs) to hyperuricemia (HUA) among the general population, however, the association of the TM mixture with HUA, especially in older adults, remains poorly understood. We aimed to examine the relationships between individual TMs and their mixture and HUA in Chinese rural older adults. This study consisted of 2075 rural older adults aged 60 years or over. Blood concentrations of aluminum (Al), arsenic (As), barium (Ba), cadmium (Cd), cesium (Cs), gallium (Ga), mercury (Hg), lead (Pb), thallium (Tl), and uranium (U) were detected using inductively coupled plasma mass spectrometry. The associations of single TMs with HUA were assessed using logistic regression and restricted cubic spline (RCS) models, and the association of TM mixture with HUA was explored using the elastic net with environmental risk score (ENET-ERS), quantile g-computation (QGC), and Bayesian kernel machine regression (BKMR) models, respectively. Adjusted logistic regression model showed that Cs (OR = 1.65, 95% CI 1.37-1.99) and Pb (OR = 1.46, 95% CI 1.28-1.67) were positively related to HUA, and RCS model exhibited a positive linear association of Cs and Pb with HUA. ENET-ERS and QGC models quantified a positive correlation between the TM mixture and the odds of HUA, with estimated ORs of 1.15 (95% CI 1.11-1.19) and 1.84 (95% CI 1.37-2.47), respectively, and Cs and Pb had the most weight. BKMR model demonstrated a significant linear association between the TM mixture and increased odds of HUA, with the posterior inclusion probabilities (PIPs) of both Cs and Pb being 1.00. Moreover, we observed a positive interaction between Cs and Pb on HUA. The TM mixture is associated with increased odds of HUA in rural older adults, which may mainly be driven by Cs and Pb. Subsequent studies are warranted to confirm these findings and clarify the mechanisms linking multiple TMs with HUA.

Association between Combined Metals and PFAS Exposure with Dietary Patterns: A Preliminary Study.

Background: The global burden of chronic diseases has been increasing, with evidence suggesting that diet and exposure to environmental pollutants, such as per- and polyfluoroalkyl substances (PFAS) and heavy metals, may contribute to their development. The Dietary Inflammatory Index (DII) assesses the inflammatory potential of an individual's diet. However, the complex interplay between PFAS, heavy metals, and DII remains largely unexplored. Objective: The goal of this cross-sectional study was to investigate the associations between diet operationalized as the DII with individual and combined lead, cadmium, mercury, perfluorooctanoic acid (PFOA), and perfluorooctanesulfonic acid (PFOS) exposures using data from the National Health and Nutrition Examination Survey (NHANES) 2017-2018. Methods: Descriptive statistics, a correlational analysis, and linear regression were initially used to assess the relationship between the variables of interest. We subsequently employed Bayesian kernel Machine regression (BKMR) to analyze the data to assess the non-linear, non-additive, exposure-response relationships and interactions between PFAS and metals with the DII. Results: The multi-variable linear regression revealed significant associations between the DII and cadmium and mercury. Our BKMR analysis revealed a complex relationship between PFAS, metal exposures, and the DII. In our univariate exposure-response function plot, cadmium and mercury exhibited a positive and negative linear relationship, respectively, which indicated a positive and negative relationship across the spectrum of exposures with the DII. In addition, the bivariate exposure-response function between two exposures in a mixture revealed that cadmium had a robust positive relationship with the DII for different quantiles of lead, mercury, PFOA, and PFOS, indicating that increasing levels of cadmium are associated with the DII. Mercury's bivariate plot demonstrated a negative relationship across all quantiles for all pollutants. Furthermore, the posterior inclusion probability (PIP) results highlighted the consistent importance of cadmium and mercury with the inflammatory potential of an individual's diet, operationalized as the DII in our study, with both showing a PIP of 1.000. This was followed by PFOS with a PIP of 0.8524, PFOA at 0.5924, and lead, which had the lowest impact among the five environmental pollutants, with a PIP of 0.5596. Conclusion: Our study suggests that exposures to environmental metals and PFAS, particularly mercury and cadmium, are associated with DII. These findings also provide evidence of the intricate relationships between PFAS, heavy metals, and the DII. The findings underscore the importance of considering the cumulative effects of multi-pollutant exposures. Future research should focus on elucidating the mechanistic pathways and dose-response relationships underlying these associations in a study that examines causality, which will enable a deeper understanding of the dietary risks associated with environmental pollutants.

Associations between maternal urinary isoflavone concentrations and anogenital distance of offspring throughout infancy: a prospective cohort study.

STUDY QUESTION: Are maternal urinary isoflavone (ISO) concentrations during pregnancy associated with anogenital distance (AGD) in infants at birth, and at 6 and 12 months of age? SUMMARY ANSWER: Higher maternal urinary ISO concentrations during pregnancy were associated with longer AGD in infants of both sexes, and equol (EQU) and daidzein (DAD) were identified as the important ISO mixture components in the observed associations. WHAT IS KNOWN ALREADY: Evidence of the association of prenatal exposure to ISO with offspring's AGD is mainly derived from animal studies, which used different study designs and had inconsistent results. Only one human study has been reported and it found null associations between maternal ISO exposure during pregnancy and AGD among boys at birth, with a small sample size and a wide range of exposure windows. No human study on girls was found. STUDY DESIGN, SIZE, DURATION: Prospective cohort study (Shanghai-Minhang Birth Cohort Study), with pregnant women recruited at 12-16 weeks of gestation in Shanghai, China between April and December 2012. One thousand two hundred and twenty-five live singletons were left in the cohort at delivery of which 480 mother-infant pairs had data on both maternal urinary ISO concentrations and at least one AGD measurement and were included in the present study. Anopenile distance (AGDAP) and anoscrotal distance (AGDAS) of boys and anoclitoral distance (AGDAC) and anofourchette distance (AGDAF) of girls were measured at birth and at 6 and 12 months of age. PARTICIPANTS/MATERIALS, SETTING, METHODS: Multiple linear regression models were used to examine the associations between maternal ISO concentrations and AGD. Bayesian kernel machine regression (BKMR) was implemented to examine both the overall effects of ISO mixture and the single effect of each ISO and identify important components of ISO mixture. MAIN RESULTS AND THE ROLE OF CHANCE: A general profile of higher concentrations of maternal ISO associated with longer AGD in infants of both sexes was observed, when maternal education, parity, BMI before pregnancy (BMI, categorical variable), passive smoking during early pregnancy, age at delivery, gestational weeks and infant body size were adjusted for. Among boys, EQU was associated with increased AGDAS at birth and at 6 and 12 months, and DAD was associated with increased AGDAP at birth. Among girls, the associations of EQU and DAD with increased AGDAC and AGDAF at birth were found. When gestational weight gain and feeding patterns of infants in the first 6 months were additionally adjusted for, and maternal BMI was adjusted for as a continuous variable, more pronounced associations were observed, especially for associations of genistein (GEN), DAD and glycitein (GLY) with increased AGDAP and AGDAS at 6 months in boys. However, these associations were not always observed in the highest tertile group, and no consistent dose-response relationships were found. Similar results were observed in BKMR models, showing positive correlations of concentration of ISO mixture with increased AGDAS at both 6 and 12 months among boys, and increased AGDAC and AGDAF at birth among girls. Statistically significant increments of 4.96 mm (95% credible interval (CrI): 1.40, 8.52) and 1.07 mm (95% CrI: 0.02, 2.13) in AGDAS at 6 months among boys and AGDAC at birth among girls, respectively, were observed at the 75th percentile of ISO mixture, compared with 25th percentile. EQU and DAD were identified as the important components among ISO-AGD associations. LIMITATIONS, REASONS FOR CAUTION: First, due to the short half-lives of ISO, the accuracy of a single spot urine sample reflecting ISO exposure during pregnancy may be limited, and thus may cause non-differential misclassification. Second, despite the adjustments for several important covariates in the study, unmeasured and residual confounding factors may remain a concern. Third, false discovery due to multiple testing may remain. Finally, the reduced sample sizes attributed to the loss of follow-up and missing data of confounders may limit our ability to detect an association, if any existed. WIDER IMPLICATIONS OF THE FINDINGS: Prenatal ISO exposure may affect the reproductive development of offspring. As ISO can be widely detected in pregnant women, especially in Eastern countries, more studies are warranted to provide evidence of the effects of prenatal ISO exposure on long-term reproductive outcomes. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by grants from the National Key Research and Development Program of China (2021YFC2701003), the National Natural Science Foundation of China (22076123), the Science and Technology Commission of Shanghai Municipality (21ZR1454700 and 20ZR1448000), the Shanghai Municipal Health Commission (20194Y0160) and Innovation-oriented Science and Technology Grant from NHC Key Laboratory of Reproduction Regulation (CX2022-04). The authors have no conflicts of interest to declare. TRIAL REGISTRATION NUMBER: N/A.

Association of dietary mineral mixture with depressive symptoms: A combination of Bayesian approaches.

The relationships between mixtures of multiple minerals and depression have not been explored. Therefore, we analyzed the relationship between the mixture of nine dietary minerals [calcium (Ca), phosphorus, magnesium (Mg), iron (Fe), zinc, copper (Cu), sodium, potassium (K), and selenium (Se)] and depressive symptoms in the general population. We screened 20,342 participants from the National Health and Nutrition Examination Survey (NHANES) 2007-2018. We fitted the general linear regression, Bayesian kernel machine regression (BKMR), and Bayesian semiparametric regression models to explore associations and interactions. We obtained the relative importance of dietary minerals by calculating posterior inclusion probabilities (PIPs). The dietary intakes of minerals were obtained using the 24-h dietary recall interview, and depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9). The linear analysis showed that nine minerals were negatively associated with PHQ-9 scores. The BKMR analysis showed a negative association between the dietary mineral mixture and PHQ-9 scores, with Se having the largest PIP at 1.0000, followed by K (0.7784). We also observed potential interactions between Ca and Fe, Se and Fe, and K and Mg. Among them, the interaction of Ca and Fe had the largest PIP of 0.986. In addition, the overall effect was more pronounced in females than males, and Cu's PIP (0.8376) was higher in females. Two sensitivity analyses showed that our results were robust. Our study provides a basis for formulating nutritional intervention programs for depression in the future.