Bayesian Kernel Machine Regression Analysis Research Articles

Associations between specific volatile organic chemical exposures and cardiovascular disease risks: insights from NHANES

IntroductionAn 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.ObjectivesThis study assessed whether exposure to VOC was associated with CVD in the general population.MethodsA 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.ResultsTotal 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%).ConclusionThe 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.

Associations of single and multiple vitamin exposure with childhood eczema: data from the national health and nutrition examination survey.

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. 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. 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. 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.

Association of Blood Copper With the Subclinical Carotid Atherosclerosis: An Observational Study.

Copper exposure is reported to be associated with increased risk of stroke. However, the association of copper exposure with subclinical carotid atherosclerosis remains unclear. This observational study included consecutive participants from Xinqiao Hospital between May 2020 and August 2021. Blood metals were measured using inductively coupled plasma mass spectrometry and carotid atherosclerosis was assessed using ultrasound. Modified Poisson regression was performed to evaluate the associations of copper and other metals with subclinical carotid plaque presence. Blood metals were analyzed as categorical according to the quartiles. Multivariable models were adjusted for age, sex, body mass index, education, smoking, drinking, hypertension, diabetes, dyslipidemia, estimated glomerular filtration rate, and coronary artery disease history. Bayesian Kernel Machine Regression was conducted to evaluate the overall association of metal mixture with subclinical carotid plaque presence. One thousand five hundred eighty-five participants were finally enrolled in our study, and carotid plaque was found in 1091 subjects. After adjusting for potential confounders, metal-progressively-adjusted models showed that blood copper was positively associated with subclinical carotid plaque (relative risk according to comparing quartile 4 to quartile 1 was 1.124 [1.021-1.238], relative risk according to per interquartile increment was 1.039 [1.008-1.071]). Blood cadmium and lead were also significantly associated with subclinical carotid plaque. Bayesian Kernel Machine Regression analyses suggested a synergistic effect of copper-cadmium-lead mixture on subclinical carotid plaque presence. Our findings identify copper as a novel risk factor of subclinical carotid atherosclerosis and show the potential synergistic proatherogenic effect of copper, cadmium, and lead mixture.

Associations between serum perfluoroalkyl and polyfluoroalkyl concentrations and diabetes mellitus in the Korean general population: Insights from the Korean National Environmental Health Survey 2018–2020

AimsRecent epidemiologic research has examined the relationship between perfluoroalkyl and polyfluoroalkyl substances (PFAS) and diabetes mellitus with inconclusive findings. In this cross-sectional study, we aimed to explore the association between serum PFAS concentrations and the prevalence of prediabetes and pre-diagnostic diabetes in the general Korean population as well as the combined effects of exposure to mixed PFAS compounds. MethodsWe analyzed data from participants aged ≥19 years enrolled in the Korean National Environmental Health Survey Cycle 4 (2018–2020). Individuals diagnosed with diabetes were excluded to minimize potential bias. We identified cases of pre-diagnostic diabetes based on the HbA1c level ≥6.5% and prediabetes as HbA1c levels of 5.7–6.49%. Serum concentrations of PFAS, including perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDeA), perfluorohexane sulfonic acid (PFHxS), and perfluorooctane sulfonic acid (PFOS), were quantified using high-performance liquid chromatography-tandem mass spectrometry. Survey-weighted logistic regression models were used to assess the relationships between PFAS levels and diabetes risk, adjusting for covariates. Additionally, Bayesian kernel machine regression (BKMR) was used to investigate the combined effects of exposure to mixed PFAS compounds. ResultsIn the study population excluding participants with diagnosed diabetes (n = 2709), the prevalence of pre-diagnostic diabetes and prediabetes was 4.8% and 30.1%, respectively. Significant positive associations were found between serum PFHxS and PFOS quartiles and pre-diagnostic diabetes risk. Likewise, among those without diagnosed or pre-diagnostic diabetes (n = 2579), the highest quartiles of PFDeA, PFHxS, and PFOS and the overall PFAS level were associated with an increased risk of prediabetes compared with the lowest quartiles. BKMR analysis revealed a significant positive association between overall serum PFAS level and prediabetes risk, which was most marked for PFOS. ConclusionsThese findings highlight the potential health implications of PFAS exposure and prediabetes risk. Further research is needed to validate these associations and identify potential mechanistic pathways.

Exploring Prenatal Exposure to Halogenated Compounds and Its Relationship with Birth Outcomes Using Nontarget Analysis.

Halogenated organic compounds (HOCs) are a class of contaminants showing high toxicity, low biodegradability, and high bioaccumulation potential, especially chlorinated and brominated HOCs (Cl/Br-HOCs). Knowledge gaps exist on whether novel Cl/Br-HOCs could penetrate the placental barrier and cause adverse birth outcomes. Herein, 326 cord blood samples were collected in a hospital in Jinan, Shandong Province from February 2017 to January 2022, and 44 Cl/Br-HOCs were identified with communicating confidence level above 4 based on a nontarget approach, covering veterinary drugs, pesticides, and their transformation products, pharmaceutical and personal care products, disinfection byproducts, and so on. To our knowledge, the presence of closantel, bromoxynil, 4-hydroxy-2,5,6-trichloroisophthalonitrile, 2,6-dibromo-4-nitrophenol, and related components in cord blood samples was reported for the first time. Both multiple linear regression (MLR) and Bayesian kernel machine regression (BKMR) models were applied to evaluate the relationships of newborn birth outcomes (birth weight, length, and ponderal index) with individual Cl/Br-HOC and Cl/Br-HOCs mixture exposure, respectively. A significantly negative association was observed between pentachlorophenol exposure and newborn birth length, but the significance vanished after the false discovery rate correction. The BKMR analysis showed that Cl/Br-HOCs mixture exposure was significantly associated with reduced newborn birth length, indicating higher risks of fetal growth restriction. Our findings offer an overview of Cl/Br-HOCs exposome during the early life stage and enhance the understanding of its exposure risks.

Association of Combined Per- and Polyfluoroalkyl Substances and Metals with Chronic Kidney Disease.

Background: Exposure to environmental pollutants such as metals and Per- and Polyfluoroalkyl Substances (PFAS) has become common and increasingly associated with a decrease in the estimated Glomerular Filtration Rate (eGFR), which is a marker often used to measure chronic kidney disease (CKD). However, there are limited studies involving the use of both eGFR and the urine albumin creatinine ratio (uACR), which are more comprehensive markers to determine the presence of CKD and the complexity of pollutant exposures and response interactions, especially for combined metals and PFAS, which has not been comprehensively elucidated. Objective: This study aims to assess the individual and combined effects of perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), Cadmium (Cd), Mercury (Hg), and Lead (Pb) exposure on CKD using data from the National Health and Nutritional Examination Survey (NHANES) 2017-2018. Methods: We employed the use of bivariate logistic regression and Bayesian Kernel Machine Regression (BKMR) in our analysis of the data. Results: Logistic regression results revealed a positive association between PFOA and CKD. Our BKMR analysis revealed a non-linear and bi-phasic relationship between the metal exposures and CKD. In our univariate exposure-response function plot, Cd and Hg exhibited a U and N-shaped interaction, which indicated a non-linear and non-additive relationship with both low and high exposures associated with CKD. In addition, the bivariate exposure-response function between two exposures in a mixture revealed that Cd had a U-shaped relationship with CKD at different quantiles of Pb, Hg, PFOA, and PFOS, indicating that both low and high levels of Cd is associated with CKD, implying a non-linear and complex biological interaction. Hg's interaction plot demonstrated a N-shaped association across all quantiles of Cd, with the 75th quantile of Pb and the 50th and 75th quantiles of PFOA and PFOS. Furthermore, the PIP results underscored Cd's consistent association with CKD (PIP = 1.000) followed by Hg's (PIP = 0.9984), then PFOA and PFOS with a closely related PIP of 0.7880 and 0.7604, respectively, and finally Pb (PIP = 0.6940), contributing the least among the five environmental pollutants on CKD, though significant. Conclusions: Our findings revealed that exposure to environmental pollutants, particularly Hg and Cd, are associated with CKD. These findings highlight the need for public health interventions and strategies to mitigate the cumulative effect of PFAS and metal exposure and elucidate the significance of utilizing advanced statistical methods and tools to understand the impact of environmental pollutants on human health. Further research is needed to understand the mechanistic pathways of PFAS and metal-induced kidney injury and CKD, and longitudinal studies are required to ascertain the long-term impact of these environmental exposures.

First trimester plasma per- and Polyfluoroalkyl Substances (PFAS) and blood pressure trajectories across the second and third trimesters of pregnancy

BackgroundEvidence suggests that exposure to per- and polyfluoroalkyl substances (PFAS) increases risk of high blood pressure (BP) during pregnancy. Prior studies did not examine associations with BP trajectory parameters (i.e., overall magnitude and velocity) during pregnancy, which is linked to adverse pregnancy outcomes. ObjectivesTo estimate associations of multiple plasma PFAS in early pregnancy with BP trajectory parameters across the second and third trimesters. To assess potential effect modification by maternal age and parity. MethodsIn 1297 individuals, we quantified six PFAS in plasma collected during early pregnancy (median gestational age: 9.4 weeks). We abstracted from medical records systolic BP (SBP) and diastolic BP (DBP) measurements, recorded from 12 weeks gestation until delivery. BP trajectory parameters were estimated via Super Imposition by Translation and Rotation modeling. Subsequently, Bayesian Kernel Machine Regression (BKMR) was employed to estimate individual and joint associations of PFAS concentrations with trajectory parameters – adjusting for maternal age, race/ethnicity, pre-pregnancy body mass index, income, parity, smoking status, and seafood intake. We evaluated effect modification by age at enrollment and parity. ResultsWe collected a median of 13 BP measurements per participant. In BKMR, higher concentration of perfluorooctane sulfonate (PFOS) was independently associated with higher magnitude of overall SBP and DBP trajectories (i.e., upward shift of trajectories) and faster SBP trajectory velocity, holding all other PFAS at their medians. In stratified BKMR analyses, participants with ≥ 1 live birth had more pronounced positive associations between PFOS and SBP velocity, DBP magnitude, and DBP velocity – compared to nulliparous participants. We did not observe significant associations between concentrations of the overall PFAS mixture and either magnitude or velocity of the BP trajectories. ConclusionEarly pregnancy plasma PFOS concentrations were associated with altered BP trajectory in pregnancy, which may impact future cardiovascular health of the mother.

Association of mixed polycyclic aromatic hydrocarbons exposure with oxidative stress in Korean adults

Polycyclic aromatic hydrocarbons (PAHs) are widespread pollutants associated with several adverse health effects and PAH-induced oxidative stress has been proposed as a potential mechanism. This study evaluated the associations of single and multiple PAHs exposure with oxidative stress within the Korean adult population, using serum gamma glutamyltransferase (GGT) as an oxidative stress marker. Data from the Second Korean National Environmental Health Survey (2012–2014) were analyzed. For analysis, 5225 individuals were included. PAH exposure was assessed with four urinary PAH metabolites: 1-hydroxyphenanthrene, 1-hydroxypyrene, 2-hydroxyfluorene, and 2-naphthol. After adjusting for age, sex, body mass index, drinking, passive smoking, and current smoking (model 1), as well as the presence of diabetes and hepatobiliary diseases (model 2), complex samples general linear model regression analyses for each metabolite revealed a significant positive association between Ln(1-hydroxyphenanthrene) and Ln(GGT) (model 1: β = 0.040, p < 0.01 and model 2: β = 0.044, p < 0.05). For the complete dataset (n = 4378), a significant positive association was observed between mixture of four urinary PAH metabolites and serum GGT in both the quantile g-computation and the Bayesian kernel machine regression analysis. Our study provides evidence for the association between mixed PAH exposure and oxidative stress.

Analysis of relationship between mixed heavy metal exposure and early renal damage based on a weighted quantile sum regression and Bayesian kernel machine regression model

BackgroundOccupation, environmental heavy metal exposure, and renal function impairment are closely related. The relationship between mixed metal exposure and chronic renal injury is inadequately described, and the interaction between each metal is poorly explored. ObjectiveThis cross-sectional study assessed mixed heavy metal exposure in the general population and their relationship with early renal impairment, as well as possible interactions between metals. MethodsThe study was conducted in two communities in Taiyuan City in northern China. Multiple linear regression, weighted quantile sum (WQS) and bayesian kernel machine regression (BKMR) regression were used to explore the relationship of mixed heavy metal exposure with indicators of early kidney injury (N-acetyl-β-D- glucosidase (UNAG), urinary albumin (UALB)). Meanwhile, BKMR was used to explore the possible interactions between mixed heavy metal and indicators of early kidney injury. ResultsBased on the WQS regression results, we observed adjusted WQS coefficient β (β-WQS) of 0.711 (95% CI: 0.543, 0.879). Notably, this change was primarily driven by As (35.6%) and Cd (22.5%). In the UALB model, the adjusted β-WQS was 0.657 (95% CI: 0.567, 0.747), with Ni (30.5%), Mn (22.1%), Cd (21.2%), and As (18.6%) exhibiting higher weights in the overall effect. The BKMR results showed a negative interaction between As and other metals in the UNAG and UALB models, a positive interaction between Mn and Ni and other metals. No significant pairwise interaction was observed in the association of metals with indicators of early kidney injury. ConclusionThrough multiple linear regression, WQS regression, and BKMR analyses, we found that exposure to mixed heavy metals such as Cd, Cr, Pb, Mn, As, Co and Ni was positively correlated with UNAG and UALB. Moreover, there are complex interactions between two or more heavy metals in more than one direction.

Associations of pyrethroid exposure with bone mineral density and osteopenia in adults.

This study was to investigate the correlations between pyrethroid exposure and bone mineral density (BMD) and osteopenia. This cross-sectional study included 1389 participants over 50years of age drawn from the 2007-2010 and 2013-2014 National Health and Nutrition Examination Survey (NHANES). Three pyrethroid metabolites, 3-phenoxybenzoic acid (3-PBA), trans-3-(2,2-dichlorovinyl)-2,2-dimethyl-cyclopropane-1-carboxylic acid (trans-DCCA), and 4-fluoro-3-phenoxybenzoic acid (4-F-3PBA) were used as indicators of pyrethroid exposure. Low BMD was defined as T-score < -1.0, including osteopenia. Weighted multivariable linear regression analysis or logistic regression analysis was utilized to evaluate the correlation between pyrethroid exposure and BMD and low BMD. Bayesian kernel machine regression (BKMR) model was utilized to analyze the correlation between pyrethroids mixed exposure and low BMD. There were 648 (48.41%) patients with low BMD. In individual pyrethroid metabolite analysis, both tertile 2 and tertile 3 of trans-DCCA were negatively related to total femur, femur neck, and total spine BMD [coefficient (β) = -0.041 to -0.028; all P < 0.05]. Both tertile 2 and tertile 3 of 4-F-3PBA were negatively related to total femur BMD (P < 0.05). Only tertile 2 [odds ratio (OR) = 1.63; 95% CI = 1.07, 2.48] and tertile 3 (OR = 1.65; 95% CI = 1.10, 2.50) of trans-DCCA was correlated with an increased risk of low BMD. The BKMR analysis indicated that there was a positive tendency between mixed pyrethroids exposure and low BMD. In conclusion, pyrethroids exposure was negatively correlated with BMD levels, and the associations of pyrethroids with BMD and low BMD varied by specific pyrethroids, pyrethroid concentrations, and bone sites.

The association between brominated flame retardants exposure with bone mineral density in US adults: A cross-sectional study of the national health and nutrition examination survey (NHANES) 2005–2014

Background and aimsExposure to brominated flame retardants (BFRs) has been widely confirmed to impair the normal functioning of the human body system. However, there is a paucity of study on the effects of serum BFRs on bone mineral density (BMD). This study aims to investigate the relationship between exposure to BFRs and BMD in a nationally representative sample of U.S. adults. Methods3079 participants aged between 20 and 80 years with complete data were included in the study. Serum levels of BFRs were measured using automated liquid-liquid extraction and subsequent sample clean-up. The BMD of all participants were assessed by DXA examinations. Generalize linear model, Restricted cubic spline (RCS), subgroup, weighted quantile sum (WQS) and bayesian kernel machine regression (BKMR) were used to estimate the association between serum BFRs and BMD. ResultsMultivariate linear regression analyses revealed that, after adjusting for covariates, PBB153 was significantly associated with TF-BMD (β = 0.0177, 95%CI: 0.0103–0.0252), FN-BMD (β = 0.009, 95%CI: 0.0036–0.0145), TS-BMD (β = 0.0081, 95%CI: 0.0013–0.015) and L1-BMD (β = 0.0144, 95%CI: 0.0075–0.0213). However, the associations lose their statistical significance after further adjustment for sex. BFRs exhibited S-shaped or line-plateau dose-response curves with BMD. In subgroup analyses, BFRs were significantly associated with BMD in participants who were younger than 55 years, female, overweight (BMI >25 kg/m2), and less alcohol consumption. In WQS and BKMR analyses, the effects of BFRs mixtures on BMD differed by sex, and PBDE153, PBDE209 and PBB153 had the highest weights in the WQS regression model. ConclusionThis study showed that serum BFRs negatively predicted BMD in men, but not in women or the general population. PBDE153, PBDE209, and PBB153 were significant BMD factors, especially in younger, overweight, and less alcohol consumption individuals.

Urinary phenols and parabens exposure in relation to urinary incontinence in the US population.

Our study aimed to investigate the impact of urinary concentrations of personal care products (PCPs)-related phenols (PNs) and parabens (PBs), including Triclosan (TCS), Bisphenol A (BPA), Benzophenone-3 (BP-3), Butylparaben (BPB), Ethylparaben (EPB), Methylparaben (MPB), and Propylparaben (PPB), on urinary incontinence (UI) occurrence. We conducted a cross-sectional analysis using data from the National Health and Nutrition Examination Survey (NHANES) spanning the years 2007 to 2016. Regression analysis was employed to investigate the relationship between exposure to PCPs-related substances, various levels of exposure, and UI within both the general population and the female demographic. Additionally, the Bayesian Kernel Machine Regression (BKMR) model was used to assess the effects of mixtures on UI. Our analysis comprised 7,690 participants who self-reported their diagnosis. Among them, 12.80% experienced stress urinary incontinence (SUI), 11.80% reported urge urinary incontinence (UUI), and 10.22% exhibited mixed urinary incontinence (MUI). In our fully adjusted multivariable models, BP-3 exposure exhibited a positive association with SUI (OR 1.07, 95% CI 1.02-1.14, p = 0.045). BPA exposure correlated with an increased risk of UUI (OR 1.21, 95% CI 1.01-1.44, p = 0.046) and MUI (OR 1.26, 95% CI 1.02-1.54, p = 0.029). TCS exposure displayed a negative correlation with the incidence of MUI (OR 0.87, 95% CI 0.79-0.97, p = 0.009). No significant links were observed between parabens and urinary incontinence. Notably, among the female population, our investigation revealed that BPA exposure heightened the risk of MUI (OR 1.28, 95% CI 1.01-1.63, p = 0.043). Participants in the highest tertile of BP-3 exposure demonstrated elevated likelihoods of SUI and MUI compared to those in the lowest tertile. In the BKMR analysis, negative trends were observed between the mixture and the risks of UUI and MUI when the mixture ranged from the 25th to the 40th and 35th to the 40th percentiles or above, respectively. Additionally, a positive trend was identified between the mixture and MUI when it was in the 40th to 55th percentile. In conclusion, our findings suggest that exposure to BPA, TCS, and BP-3 may contribute to the development of urinary incontinence.

The single and mixed impacts of cadmium, cobalt, lead, and PAHs on systemic immunity inflammation index in male and female.

Studies on the association between mixed exposure to common pollutants such as cadmium (Cd), cobalt (Co), lead (Pb), and polycyclic aromatic hydrocarbons (PAHs) with Systemic Immune Inflammatory Index (SII), a novel hemocyte-based inflammatory marker, have not been reported. This study explored the relationship between co-exposure to Cd, Co, Pb, PAHs, and SII. In this study, we used data from the National Health and Nutrition Examination Survey and enrolled adults with complete information on Cd, Co, Pb, PAHs, and SII. The linear regression was used to analyze the association of single pollutants with SII. Furthermore, a Bayesian Kernel Machine Regression analysis and a generalized weighted quantile sum regression analysis were used to analyze the association between mixed exposure to Cd, Co, Pb, and six PAHs and SII. We also separated males and females and analyzed the different effects of pollutants on SII, respectively. 5,176 participants were included in the study. After adjusting for age, gender, race, education, smoking, drinking, physical activity, and sedentary, Cd, Co, 1-OHN, 2-OHN and 2-OHF were positive with SII in the total population. Compared with the 50th percentile, the joint effect of pollutants on SII was positive. In the total population, males, and females, the top contaminant with the highest effect weights on SII were Co, Cd, and 1-OHN, respectively. The result of interaction analysis showed that the low concentrations of Cd had an elevation effect on SII in males. This study found a positive association of mixed exposure to Cd, Co, Pb, and six PAHs with SII, which occurred mainly in females.

Association of non‐essential metals with Chinese schizophrenia: A case‐control study

AbstractBackgroundThe potential link between environmental pollutants, including metals, and schizophrenia development remains debated. This study aimed to explore the association between plasma levels of three non‐essential metals—barium (Ba), tungsten (W), and uranium (U)—and schizophrenia risk among Chinese individuals.MethodWe recruited a total of 221 patients and 219 healthy controls. Plasma levels of three non‐essential metals were measured using inductively coupled plasma mass spectrometry. We employed unconditional logistic regression and Bayesian kernel machine regression (BKMR) to explore the relationship between exposure to multiple metals and the risk of schizophrenia.ResultsLogistic regression analysis revealed that the highest quartile (Q4) of W had an odds ratio (OR) of 1.87 (95% CI: 1.08–3.21) compared to the lowest quartile (Q1), with a significant P‐trend of 0.017. For U, the ORs (95% CI) for Q2, Q3, and Q4 were 2.06 (1.19–3.56), 1.99 (1.15–3.44), and 1.74 (1.00–3.00), respectively. BKMR analyses revealed a progressive increase in the risk of schizophrenia with increasing cumulative levels of the three metals at concentrations below 35%, with U playing a major role in this association. U showed a non‐linear positive correlation with schizophrenia, particularly at the 75th percentile level. Moreover, potential interactions were observed between W and Ba, as well as between W and U.ConclusionHigher plasma W and U concentrations were positively associated with the risk of schizophrenia, which was potentially related to the severity of symptoms in schizophrenic patients.

Using Bayesian and weighted regression to evaluate the association of idiopathic oligoastenoteratozoospermia with seminal plasma metal mixtures

Idiopathic oligoastenoteratozoospermia (iOAT) affects 30% of infertile men of reproductive age. However, the associations between Cr, Fe, Cu, Se or Co levels and iOAT risk have not been determined. This research aimed to assess the associations between Cr, Fe, Cu, Se and Co levels as well as their mixtures in seminal plasma and the risk of iOAT and severe iOAT. Therefore, a case‒control study including 823 participants (416 iOAT patients and 407 controls) recruited from October 2021 to August 2022 at the reproductive medicine center of the First Affiliated Hospital of Anhui Medical University was conducted in Anhui, China. The concentrations of Cr, Fe, Cu, Se and Co in seminal plasma were detected via inductively coupled plasma‒mass spectrometry. Binary logistic regression models were used to assess the associations between the levels of Cr, Fe, Cu, Se and Co and the risk of iOAT and severe iOAT; additionally, Bayesian kernel machine regression (BKMR) and weighted quantile sum (WQS) regressions were performed to evaluate the joint effect of seminal plasma levels of Cr, Fe, Cu, Se and Co on the risk of iOAT and explore which elements contributed most to the relationship. We found significant associations between the concentrations of Fe, Cu and Se in seminal plasma and iOAT risk after adjusting for covariates (Fe, lowest tertile vs. second tertile: aOR = 1.86, 95% CI = 1.31, 2.64; Cu, lowest tertile vs. second tertile: aOR = 1.95, 95% CI = 1.37, 2.76; Se, lowest tertile vs. second tertile: aOR = 1.65, 95% CI = 1.17, 2.35). A lower Se concentration in seminal plasma (lowest tertile vs. second tertile: aOR = 1.84, 95% CI = 1.10, 3.10) was positively associated with the risk of severe iOAT. Additionally, we also observed an association between the concentration of Cr in seminal plasma and the risk of iOAT before adjusting for covariates (Cr, third tertile vs. lowest tertile: OR=1.44, 95% CI: 1.03, 2.02). According to the BKMR analyses, the risk of iOAT increased when the overall concentrations were less than the 25th percentile. The results from the WQS regression indicated that a negative WQS index was significantly associated with the iOAT risk, while a positive WQS index was not. Se and Fe had significant weights in the negative direction. In conclusion, lower Cu, Fe and Se levels in seminal plasma were positively associated with iOAT risk, while higher Cr levels in seminal plasma were positively associated with iOAT risk according to the single element model, and lower levels of Se were related to a greater risk of severe iOAT; when comprehensively considering all the results from BKMR and WQS regression, Fe, Se and Cr levels contributed most to this relationship.

Elevated levels of Zn, Cu and Co are associated with an increased risk of endometriosis: Results from a case[sbnd]control study

BackgroundEndometriosis 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. ObjectiveThis 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. MethodsA 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). ResultsBased 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. ConclusionThe 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.

Inverse association between maternal serum concentrations of trace elements and risk of spontaneous preterm birth: a nested case-control study in China.

Few studies have evaluated the joint effect of trace elements on spontaneous preterm birth (SPTB). This study aimed to examine the relationships between the individual or mixed maternal serum concentrations of Fe, Cu, Zn, Se, Sr and Mo during pregnancy, and risk of SPTB. Inductively coupled plasma MS was employed to determine maternal serum concentrations of the six trace elements in 192 cases with SPTB and 282 controls with full-term delivery. Multivariate logistic regression, weighted quantile sum regression (WQSR) and Bayesian kernel machine regression (BKMR) were used to evaluate the individual and joint effects of trace elements on SPTB. The median concentrations of Sr and Mo were significantly higher in controls than in SPTB group (P < 0·05). In multivariate logistic regression analysis, compared with the lowest quartile levels of individual trace elements, the third- and fourth-quartile Sr or Mo concentrations were significantly associated with reduced risk of SPTB with adjusted OR (aOR) of 0·432 (95 CI < 0·05). In multivariate logistic regression analysis, compared with the lowest quartile levels of individual trace elements, the third- and fourth-quartile Sr or Mo concentrations were significantly associated with reduced risk of SPTB with adjusted aOR of 0·432 (95 % CI 0·247, 0·756), 0·386 (95 % CI 0·213, 0·701), 0·512 (95 % CI 0·297, 0·883) and 0·559 (95 % CI 0·321, 0·972), respectively. WQSR revealed the inverse combined effect of the trace elements mixture on SPTB (aOR = 0·368, 95 % CI 0·228, 0·593). BKMR analysis confirmed the overall mixture of the trace elements was inversely associated with the risk of SPTB, and the independent effect of Sr and Mo was significant. Our findings suggest that the risk of SPTB decreased with concentrations of the six trace elements, with Sr and Mo being the major contributors.

Telomere length as a modifier in the relationship between phthalate metabolites exposure and glucose homeostasis

Given the rising concern over the potential impact of environmental factors on metabolic heath, we conducted a cross-sectional analysis among 645 adults aged 20 and older in the National Health and Nutrition Examination Survey (NHANES), examining the association between nine phthalate metabolites (Mono-n-butyl phthalate (MBP), Mono-ethyl phthalate (MEP), Mono-(2-ethyl)-hexyl phthalate (MEHP), Mono-benzyl phthalate (MBzP), Mono-n-methyl phthalate (MnMP), Mono-(3-carboxy propyl) phthalate (MCPP), Mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), Mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), Mono-isobutyl phthalate (MiBP)) and six glucose homeostasis indices (fasting glucose, fasting insulin, hemoglobin A1C (HbA1C), homeostatic model assessment of insulin resistance (HOMA-IR), single Point Insulin Sensitivity Estimator (SPISE), and HOMA-β). Latent Class Analysis identified three phthalate metabolites exposure patterns: high MEP-low MEOHP (n = 282), high MBzP-low MEHHP (n = 214), and high MEHHP, MEOHP (n = 149). The high MBzP-low MEHHP and high MEHHP, MEOHP, versus the high MEP-low MEOHP, exposure groups showed significantly higher levels of fasting insulin (β = 0.126, 95% CI: 0.023–0.228), SPISE (β = 0.091, 95% CI: 0.018–0.164), and HOMA-IR (β = 0.091, 95% CI: 0.018–0.164). In the shorter telomere length group, high MEHHP, MEOHP exposure showed an increase in SPISE levels (β = 0.153, 95% CI: 0.037–0.269), while in the overweight/obese subgroup, high MEHHP, MEOHP exposure was significantly positively associated with HOMA-IR (β = 0.392, 95% CI: 0.150–0.735). Bayesian kernel machine regression analyses showed positive associations between higher combined phthalate exposure and increased glucose homeostasis indices (fasting glucose, HbA1C, fasting insulin, SPISE, and HOMA-IR). The quantile of g-calculation analysis also supported the positive associations with HbA1C, HOMA-IR, and fasting insulin. Our findings indicate that phthalate exposure was positively associated with glucose homeostasis indices, which strengthen the call for proactive measures to reduce phthalate exposure and mitigate potential risks to glucose metabolism.

Effect of trace element mixtures on the outcome of patients with esophageal squamous cell carcinoma: a prospective cohort study in Fujian, China

BackgroundThe evidence about the effects of trace elements on overall survival(OS) of patients with esophageal squamous cell carcinoma(ESCC) is limited. This study aims to evaluate mixed effects of plasma trace elements on OS of ESCC.MethodsThis prospective cohort analysis included 497 ESCC patients with a median follow-up of 52.3 months. The concentrations of 17 trace elements were measured. We fitted Cox’s proportional hazards regression, factor analysis and Bayesian kernel machine regression (BKMR) models to estimate the association between trace elements and OS.ResultsOur analysis found that in the single-element model, Co, Ni, and Cd were associated with an increased risk of death, while Ga, Rb, and Ba were associated with a decreased risk. Cd had the strongest risk effect among all elements. As many elements were found to be mutually correlated, we conducted a factor analysis to identify common factors and investigate their associations with survival time. The factor analysis indicated that the factor with high factor loadings in Ga, Ba and B was linked to a decreased risk of death, while the factor with high factor loadings in Co, Ti, Cd and Pb was associated with a borderline significantly increased risk. Using BKMR analysis to disentangle the interaction between elements in significant factors, we discovered that Ga interacted with Ba and both elements had U-shaped effects with OS. Cd, on the other hand, had no interaction with other elements and independently increased the risk of death.ConclusionsOur analysis revealed that Ga, Ba and Cd were associated with ESCC outcome, with Ga and Ba demonstrating an interaction. These findings provide new insights into the impact of trace elements on the survival of patients with ESCC.

Role of alanine aminotransferase in the effects of urinary caffeine concentration and its primary metabolite concentration on cognitive function in older adults: Bayesian Kernel Machine regression analysis and mediation analysis.

This study aimed to explore the role of alanine aminotransferase (ALT) in the effects of urinary caffeine and its primary metabolites on cognitive function in elderly people. In this investigation, we meticulously curated a cohort from the 2011-2014 National Health and Nutrition Examination Survey (NHANES) database. Animal fluency emerged as the pivotal metric for assessing cognitive function within our study population. In order to navigate the intricacies of mixture analysis and circumvent potential complexities, we harnessed the power of Bayesian kernel machine regression (BKMR) models. This method allowed us to dissect the nuanced impacts of caffeine and its primary urinary metabolites on cognitive function. While accounting for caffeine and its metabolites, we analyzed the relationship between ALT and cognitive function through non-linear dynamics. Lastly, employing structural equation modeling, we probed the intriguing question of whether ALT mediates the influence of 3,7-dimethylxanthine on cognitive function. This comprehensive approach has unveiled a deeper understanding of the multifaceted interplay among these variables, offering invaluable insights into the determinants of cognitive function within our cohort. After meticulous adjustment for various covariates, our linear regression analysis unveiled a noteworthy finding: 3,7-dimethylxanthine demonstrated a significant positive correlation with cognitive function (p < 0.05). Importantly, within the BKMR model employed, 3,7-dimethylxanthine emerged as the most influential factor within the compound, with posterior inclusion probabilities of 0.995 and 0.939. Furthermore, our single-exposure effect model confirmed its presence at the 25th, 50th, and 75th percentile concentrations of other components within the compound. Interestingly, bivariate concentration curves indicated no interaction within the compound, underscoring the prominent impact of 3,7-dimethylxanthine on cognitive function. Subsequently, through a test of Restricted Cubic Splines (RCS), we revealed a non-linear relationship between ALT and cognitive function at the 10th, 50th, and 90th percentiles (p < 0.05), indicating a heightened risk of diminished cognitive function in the low ALT group. Employing structural equation modeling, we meticulously examined the mediating role of ALT in relation to 3,7-dimethylxanthine and cognitive function. However, our study results did not yield significant evidence of a mediating effect. This comprehensive analysis elucidates the intricate interplay between these variables, unveiling the subtle mechanisms governing cognitive function. In this study, a noteworthy positive correlation was observed between 3,7-dimethylxanthine and cognitive function. Additionally, a non-linear relationship was identified between ALT and cognitive function, with lower levels of ALT associated with a decline in cognitive function. The RCS trend suggested that higher levels of ALT may similarly lead to diminished cognitive performance. However, in our pursuit to ascertain potential mediation, we regrettably found no significant evidence supporting mediation among these factors involving ALT. This underscores the need for more comprehensive investigations and expanded clinical explorations into the intricate associations among these three pivotal elements.