UNASSIGNED: Pesticides are widely used in agricultural activities. Although pesticide use is known to cause damage to the human body, its relationship with thyroid function remains unclear. Therefore, this study aimed to investigate the association between pesticide exposure and thyroid function.
UNASSIGNED: The Chinese database used included 60 patients with pyrethroid poisoning and 60 participants who underwent health checkups between June 2022 and June 2023. The NHANES database included 1,315 adults enrolled from 2007 to 2012. The assessed pesticide and their metabolites included 2,4-dichlorophenoxyacetic acid (2,4-D), 4-fluoro-3-phenoxybenzoic acid (4F3PB), para-nitrophenol (PN), 3-phenoxybenzoic acid (3P), and trans-dichlorovinyl-dimethylcyclopropane carboxylic acid (TDDC). The evaluated indicators of thyroid function were measured by the blood from the included population. The relationship between pesticide exposure and thyroid function indexes was investigated using linear regression, Bayesian kernel machine regression (BKMR), restricted cubic spline (RCS), and weighted quantile sum (WQS) models.
UNASSIGNED: The Chinese data showed that pesticide exposure was negatively correlated with the thyroid function indicators FT4, TT4, TgAb, and TPOAb (all p < 0.05). The BKMR model analysis of the NHANES data showed that the metabolic mixture of multiple pesticides was negatively associated with FT4, TSH, and Tg, similar to the Chinese database findings. Additionally, linear regression analysis demonstrated positive correlations between 2,4-D and FT3 (p = 0.041) and 4F3PB and FT4 (p = 0.003), whereas negative associations were observed between 4F3PB and Tg (p = 0.001), 4F3PB and TgAb (p = 0.006), 3P and TgAB (p = 0.006), 3P and TPOAb (p = 0.03), PN and TSH (p = 0.003), PN and TT4 (p = 0.031), and TDDC and TPOAb (p < 0.001). RCS curves highlighted that most pesticide metabolites were negatively correlated with thyroid function indicators. Finally, WQS model analysis revealed significant differences in the weights of different pesticide metabolites on the thyroid function indexes.
UNASSIGNED: There is a significant negative correlation between pesticide metabolites and thyroid function indicators, and the influence weights of different pesticide metabolites on thyroid function indicators are significantly different. More research is needed to further validate the association between different pesticide metabolites and thyroid disease.

Liver diseases, including non-alcoholic fatty liver disease (NAFLD), are a growing global health issue. Environmental exposure to toxic metals can harm the liver, increasing the risk of NAFLD. Essential elements are vital for liver health, but imbalances or deficiencies can contribute to the development of NAFLD. Therefore, understanding the interplay between toxic metals and essential elements in liver disease is important. This study aims to assess the individual and combined effects of toxic metals (lead(Pb), cadmium (Cd), mercury (Hg)), and essential elements (manganese and selenium) on the risk of liver disease. Methods: We assessed the individual and combined effects of Pb, Cd, Hg, manganese (Mn), and selenium (Se) on liver disease risk using data from the National Health and Nutrition Examination Survey between 2017 and 2018. We performed descriptive statistics and linear regression analysis and then utilized Bayesian Kernel Machine Regression (BKMR) techniques such as univariate, bivariate, and overall effect analysis. BKMR enabled the assessment of non-linear exposure-response functions and interactions between metals and essential elements. Posterior Inclusion Probabilities (PIPs) were calculated to determine the importance of each metal and essential element in contributing to liver disease. Regarding our study results, the regression analysis of liver injury biomarkers ALT, AST, ALP, GGT, total bilirubin, and the FLI-an indicator of NAFLD-with toxic metals and essential elements, adjusting for covariates such as age, sex, BMI, alcohol consumption, ethnicity, income, and smoking status, demonstrated the differential effects of these contaminants on the markers of interest. Our BKMR analysis provided further insights. For instance, the PIP results underscored Pb\'s consistent importance in contributing to liver disease (PIP = 1.000), followed by Hg (PIP = 0.9512), Cd (PIP = 0.5796), Se (PIP = 0.5572), and Mn (PIP = 0.4248). Our univariate analysis showed a positive trend with Pb, while other exposures were relatively flat. Our analysis of the single-variable effects of toxic metals and essential elements on NAFLD also revealed that Pb significantly affected the risk of NAFLD. Our bivariate analysis found a positive (toxic) trend when Pb was combined with other metals and essential elements. For the overall exposure effect of exposure to all the contaminants together, the estimated risk of NAFLD showed a steady increase from the 60th to the 75th percentile. In conclusion, our study indicates that Pb exposure, when combined with other toxic metals and essential elements, plays a significant role in bringing about adverse liver disease outcomes.

Exposure to certain heavy metals has been demonstrated to be associated with a higher risk of preterm birth (PTB). However, studies focused on the effects of other metal mixtures were limited. A nested case‒control study enrolling 94 PTB cases and 282 controls was conducted. Metallic elements were detected in maternal plasma collected in the first trimester using inductively coupled plasma‒mass spectrometry. The effect of maternal exposure on the risk of PTB was investigated using logistic regression, least absolute shrinkage and selection operator, restricted cubic spline (RCS), quantile g computation (QGC) and Bayesian kernel machine regression (BKMR). Vanadium (V) and arsenic (As) were positively associated with PTB risk in the logistic model, and V remains positively associated in the multi-exposure logistic model. QGC analysis determined V (69.42%) and nickel (Ni) (70.30%) as the maximum positive and negative contributors to the PTB risk, respectively. BKMR models further demonstrated a positive relationship between the exposure levels of the mixtures and PTB risk, and V was identified as the most important independent variable among the elements. RCS analysis showed an inverted U-shape effect of V and gestational age, and plasma V more than 2.18 μg/L was considered a risk factor for shortened gestation length. Exposure to metallic elements mixtures consisting of V, As, cobalt, Ni, chromium and manganese in the first trimester was associated with an increased risk of PTB, and V was considered the most important factor in the mixtures in promoting the incidence of PTB.

The main objective of our study is to explore the associations between combined exposure to urinary heavy metals and high remnant cholesterol (HRC), a known cardiovascular risk factor. Utilizing data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018, we conducted a cross-sectional analysis of 5690 participants, assessing urinary concentrations of ten heavy metals. Ten heavy metals in urine were measured by inductively coupled plasma mass spectrometry (ICP-MS). Fasting residual cholesterol ≥0.8 mmol/L was defined as HRC (using blood samples). Statistical analyses included weighted multivariable logistic regression, weighted quantile sum (WQS) regression, quantile g-computation (qgcomp), and Bayesian kernel machine regression (BKMR) to evaluate the associations of heavy metal exposure with HRC. Stratified analyses based on individual characteristics were also conducted. Multivariable logistic regression found that the four metals (OR Q4 vs. Q1: 1.33, 95% CI: 1.01-1.75 for barium (Ba); OR Q4 vs. Q1: 1.50, 95% CI: 1.16-1.94 for cadmium (Cd); OR Q4 vs. Q1: 1.52, 95% CI: 1.15-2.01 for mercury (Hg); OR Q4 vs. Q1: 1.35, 95% CI: 1.06-1.73 for lead (Pb)) were positively correlated with the elevated risk of HRC after adjusting for covariates. In addition, all three mixed models, including WQS (OR: 1.25; 95% CI: 1.07-1.46), qgcomp (OR: 1.17; 95% CI: 1.03-1.34), and BKMR, consistently showed a significant positive correlation between co-exposure to heavy metal mixtures and HRC, with Ba and Cd being the main contributors within the mixture. These associations were more pronounced in younger adults (20 to 59 years), males, and those with a higher body mass index status (≥25 kg/m2). Our findings reveal a significant relationship between exposure to the mixture of heavy metals and HRC among US adults, with Ba and Cd being the major contributors to the mixture\'s overall effect. Public health efforts aimed at reducing heavy metal exposure can help prevent HRC and, in turn, cardiovascular disease.

OPFRs are emerging environmental pollutants with reproductive and endocrine toxicity. This study aimed to examine the association between environmental exposure to OPFRs during early pregnancy and GDM. This nested case-control study was based on a birth cohort that was constructed at a maternal and child health hospital, including 74 cases of GDM among 512 pregnant women. The OPFRs, including TBP, TBEP, TCEP, TDCPP, TMCP, TOCP, and TPHP during 10-14 weeks of pregnancy were determined using GC-MS. The association between the OPFRs and GDM was assessed using WQS and BKMR models. The levels of OPFRs were significantly elevated in GDM patients (60) compared with the controls (90). The WQS analysis showed that mixtures of the OPFRs were significantly associated with GDM (OR 1.370, 95% CI 1.036-1.810, P = 0.027), and TBP, TPHP, and TMCP were the major contributors to the mixed exposure effect. In the BKMR model, individual exposure to TBP, TPHP, and TMCP, and the interaction of TMCP with TBP and TPHP were significantly associated with GDM. Environmental exposure to OPFRs is positively associated with GDM. These findings provide evidence for the adverse effects of OPFR exposure on the health of pregnant women.

Previous studies have demonstrated that exposure to polycyclic aromatic hydrocarbons (PAHs) can affect maternal and infant health. However, the conclusions regarding the effects of seasonal PAH exposure on maternal and infant health have been inconsistent. To further elucidate this issue, this study included data from 2282 mother-infant pairs in the Zuni birth cohort. The objective was to investigate the association between maternal late-pregnancy urinary PAH metabolite concentrations and neonatal birth outcomes during the heating and non-heating seasons. The results demonstrated that PAH exposure in Zunyi was primarily dominated by 2-OHNAP and 1-OHNAP and that the concentrations of PAH metabolites were significantly higher during the heating season. Furthermore, PAH metabolite exposure was found to affect neonatal birth weight, birth length, and parity index with seasonal differences. Further dose-effect analyses revealed nonlinear relationships and seasonal differences between PAH metabolites and neonatal birth weight, birth length, and parity index. Bayesian kernel mechanism regression modeling demonstrated that the inverted U-shaped relationship between PAH metabolites and neonatal birth weight and parity index was exclusive to the heating season. Consequently, it can be posited that maternal exposure to PAH metabolites during late pregnancy exerts a detrimental influence on neonatal growth and development, which is further compounded by the use of heating fuels. This highlights the necessity to either control or alter the use of heating fuels during pregnancy.

UNASSIGNED: An increasing body of research has demonstrated a correlation between pollutants from the environment and the development of cardiovascular diseases (CVD). However, the impact of volatile organic chemicals (VOC) on CVD remains unknown and needs further investigation.
UNASSIGNED: This study assessed whether exposure to VOC was associated with CVD in the general population.
UNASSIGNED: A cross-sectional analysis was conducted utilizing data from five survey cycles (2005-2006, 2011-2012, 2013-2014, 2015-2016, and 2017-2018) of the National Health and Nutrition Examination Survey (NHANES) program. We analyzed the association between urinary VOC metabolites (VOCs) and participants by multiple logistic regression models, further Bayesian Kernel Machine Regression (BKMR) models and Weighted Quantile Sum (WQS) regression were performed for mixture exposure analysis.
UNASSIGNED: Total VOCs were found to be positively linked with CVD in multivariable-adjusted models (p for trend = 0.025), independent of established CVD risk variables, such as hypertension, diabetes, drinking and smoking, and total cholesterol levels. Compared with the reference quartile of total VOCs levels, the multivariable-adjusted odds ratios in increasing quartiles were 1.01 [95% confidence interval (CI): 0.78-1.31], 1.26 (95% CI: 1.05-1.21) and 1.75 (95% CI: 1.36-1.64) for total CVD. Similar positive associations were found when considering individual VOCs, including AAMA, CEMA, CYMA, 2HPMA, 3HPMA, IPM3 and MHBMA3 (acrolein, acrylamide, acrylonitrile, propylene oxide, isoprene, and 1,3-butadiene). In BKMR analysis, the overall effect of a mixture is significantly related to VOCs when all chemicals reach or exceed the 75th percentile. Moreover, in the WQS models, the most influential VOCs were found to be CEMA (40.30%), DHBMA (21.00%), and AMCC (19.70%).
UNASSIGNED: The results of our study indicated that VOC was all found to have a significant association with CVD when comparing results from different models. These findings hold significant potential for public health implications and offer valuable insights for future research directions.

Metals have been proved to be one of risk factors for chronic kidney disease (CKD) and diabetes, but the effect of mixed metal co-exposure and potential interaction between metals are still unclear. We assessed the urine and whole blood levels of cadmium (Cd), manganese (Mn), lead (Pb), mercury (Hg), and renal function in 3080 adults from National Health and Nutrition Survey (NHANES) (2011-2018) to explore the effect of mixed metal exposure on CKD especially in people with type 2 diabetes mellitus (T2DM). Weighted quantile sum regression model and Bayesian Kernel Machine Regression model were used to evaluate the overall exposure impact of metal mixture and potential interaction between metals. The results showed that the exposure to mixed metals was significantly associated with an increased risk of CKD in blood glucose stratification, with the risk of CKD being 1.58 (1.26,1.99) times in urine and 1.67 (1.19,2.34) times in whole blood higher in individuals exposed to high concentrations of the metal mixture compared to those exposed to low concentrations. The effect of urine metal mixture was elevated magnitude in stratified analysis. There were interactions between urine Pb and Cd, Pb and Mn, Pb and Hg, Cd and Mn, Cd and Hg, and blood Pb and Hg, Mn and Cd, Mn and Pb, Mn and Hg on the risk of CKD in patients with T2DM and no significant interaction between metals was observed in non-diabetics. In summary, mixed metal exposure increased the risk of CKD in patients with T2DM, and there were complex interactions between metals. More in-depth studies are needed to explore the mechanism and demonstrate the causal relationship.

UNASSIGNED: The association between vitamins and eczema has garnered attention, yet few studies have evaluated the effects of co-exposure to multiple vitamins on this condition. This study aims to assess the association of vitamin mixtures with eczema in children.
UNASSIGNED: This cross-sectional study analyzed data from 2,244 children aged 6-17 years from the National Health and Nutrition Examination Surveys. Eczema served as the primary outcome. Six serum vitamins, namely, vitamins A, B6, B12, C, D, and E, were the main variables. Weighted multivariate logistic regression was adopted to analyze the association between each serum vitamin and eczema. Odds ratios (OR) with a 95% confidence interval (CI) were calculated. Bayesian kernel machine regression (BKMR) analysis and the quantile g-computation (qgcomp) model were used to evaluate the association of co-exposure to multiple vitamins with eczema.
UNASSIGNED: In total, 10.83% of children (n = 243) developed eczema. After adjusting for confounding factors, we observed that compared with the reference group (vitamin B12 with second quartile), the OR for eczema was 0.604 (95% CI: 0.373-0.978, P = 0.041) for the first quartile of vitamin B12. Both BKMR analysis and the qgcomp model consistently showed that co-exposure to the six vitamins was positively correlated with the risk of eczema, with vitamin B6 contributing most to the overall effect. In BKMR analyses, we observed an interaction between vitamins B6 and B12 concerning eczema risk.
UNASSIGNED: Co-exposure to vitamins A, C, B6, B12, D, and E was found to be associated with an increased risk of eczema in children, with vitamin B6 as the greatest positive contributor driving the overall effect.

Rare earth elements (REEs) exposure during pregnancy may increase the risk of unexplained spontaneous abortion. However, the association between REEs intrauterine exposure and unexplained spontaneous abortion had yet to be studied. In order to conduct this large case-control study, we thus collected chorionic villus from 641 unexplained spontaneous abortion and 299 control pregnant women and detected the concentrations of 15 REEs by inductively coupled plasma mass spectrometer (ICP-MS). Because the detection rates of 10 REEs were less than 80%, the remaining 5 REEs, which were lanthanum (La), cerium (Ce), praseodymium (Pr), neodymium (Nd) and yttrium (Y), underwent to further analysis. The association between 5 REEs and unexplained spontaneous abortion was assessed by using the logistic regression, bayesian kernel regression (BKMR) and weighted quantile sum regression (WQS) models. In the adjusted logistic regression model, Pr, Nd and Y enhanced the incidence of unexplained spontaneous abortion in a dose-dependent way and Ce increased the risk only at high concentration group. The result of BKMR model demonstrated that the risk of unexplained spontaneous abortion increased as the percentile of five mixed REEs increased. Y and Nd were both significantly associated with an increased incidence of unexplained spontaneous abortion, but La was correlated with a decrease in the risk of unexplained spontaneous abortion. Pr was substantially associated with an increase in the risk of unexplained spontaneous abortion when other REEs concentrations were fixed at the 25th and 50th percentiles. According to WQS regression analysis, the WQS index was significantly associated with unexplained spontaneous abortion (OR = 3.75, 95% CI:2.40-5.86). Y had the highest weight, followed by Nd and Pr, which was consistent with the analysis results of our other two models. In short, intrauterine exposure to REEs was associated with an increased risk of unexplained spontaneous abortion, with Y, Nd and Pr perhaps playing an essential role.