Bayesian Kernel Machine Regression Models Research Articles

Associations between single and multiple dietary vitamins and the risk of periodontitis: results from NHANES 2009–2014

BackgroundPeriodontitis is a prevalent inflammatory periodontal disease that has an impact on the overall quality of life. Although several studies have indicated an association between individual vitamin intake and periodontitis risk, the associations of the multivitamins with periodontitis risk remain unclear.AimThis study aimed to explore the joint effect of multivitamins (including vitamin A, vitamin B1, vitamin B2, vitamin B6, vitamin B12, vitamin C, vitamin D, vitamin E, and vitamin K) on periodontitis.MethodsFor this cross-sectional study, data were collected from participants aged ≥ 30 years in the National Health and Nutrition Examination Surveys 2009–2014 (n = 9,820). We employed weighted multivariate logistic regression models to evaluate the single association between individual vitamin intakes and periodontitis, and Bayesian kernel machine regression (BKMR), weighted quantile sum (WQS) regression, and quantile g-computation (qgcomp) models to assess the joint effect of nine vitamins on periodontitis.ResultsThe overall prevalence of periodontitis was approximately 35.97%. After adjustment of covariates, vitamin B6 [odds ratio (OR) = 0.82, 95% confidence interval (CI): 0.72–0.94] and vitamin E (OR = 0.79, 95%CI: 0.69–0.92) were negatively related to the likelihood of developing periodontitis, respectively. The result of three models indicated that, mixture of vitamin A, vitamin B1, vitamin B2, vitamin B6, vitamin B12, vitamin C, vitamin D, vitamin E, and vitamin K had a significant negative combined effect on the risk of periodontitis. In the BKMR model, when all remaining vitamins were at their median levels, the periodontitis risk decreased with increased concentration levels of vitamin E and vitamin B2. WQS analysis indicated the highest weighted chemical was vitamin E, followed by vitamin B12 and vitamin D. In the qgcomp model, vitamin E received the highest negative weights for the periodontitis risk, followed by vitamin B2 and vitamin D, respectively.ConclusionBoth dietary vitamin B6 and vitamin E were associated with decreased odds of periodontitis. Additionally, the mixture-exposed analyses consistently showed the negative correlations between nine dietary vitamins mixtures and periodontitis.

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

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

Association between Per- and poly-fluoroalkyl substances and nonalcoholic fatty liver disease: a nested case-control study in northwest China

Per- and poly-fluoroalkyl substances (PFAS) have been reported to have hepatotoxic effects. However, it is unclear whether they are linked to non-alcoholic fatty liver disease (NAFLD). This nested case-control study focused on the epidemiological links between PFAS and the prevalence of NAFLD. We selected 476 new cases of NAFLD and 952 age- and sex-matched controls from the Jinchang cohort population between 2014 and 2019. Serum concentrations of PFAS were measured using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Only PFAS with a detection rate of ≥ 90 % were included for analysis, which included PFPeA, PFOA, PFNA, PFHxS, PFOS, and 9Cl-PF3ONS. The relationship between single and co-exposure to PFAS and the occurrence of NAFLD was evaluated using conditional logistic regression, Quantile g-computation (QgC), and Bayesian kernel machine regression (BKMR) model. Logistic regression indicated that PFPeA, PFOA, and 9Cl-PF3ONS were positive correlation with the incidence of NAFLD after adjusting for confounders, with odds ratios (OR) and 95 % confidence interval (CI) of 3.13 (95 % CI: 2.53, 3.86), 1.39 (95 % CI: 1.12, 1.73), and 1.41 (95 % CI: 1.20, 1.66), respectively. PFNA, PFHxS, and PFOS were nonlinearly and negatively associated with the incidence of NAFLD, with OR (95 % CI) of 0.53 (0.46, 0.62), 0.83 (0.73, 0.95), and 0.52 (0.44, 0.61), respectively. QgC showed a significant joint effect of PFAS on NAFLD onset (OR: 1.52, 95 % CI: 1.24, 1.88). BKMR showed a weak positive trend between PFAS mixtures and NAFLD incidence. Positive correlations were primarily driven by PFPeA and 9Cl-PF3ONS, while negative correlations were mainly influenced by PFNA and PFOS. The BKMR model also suggested that there was an interaction between PFOS and PFNA and other four PFAS compounds. In conclusion, our findings suggest that individual and co-exposure to PFAS is associated with a risk of NAFLD onset.

Associations of multiple metals exposure with immunoglobulin levels in pregnant women: Hangzhou Birth Cohort Study

Metal may affect maternal immune function, but few epidemiological studies have reported the associations between multiple-metal exposure and maternal immunoglobulin (Ig) levels. Based on the Hangzhou Birth Cohort Study, 1059 participants were included, and eleven metals in whole blood samples and serum IgA, IgG, IgE and IgM levels were measured. Linear regression, quantile-based g-computation (QGC), and Bayesian kernel machine regression (BKMR) models were used to evaluate the associations. Compared with the first tertile of metal levels, arsenic (As) was negatively associated with IgE (β = -0.25, 95% confidence interval (CI) = -0.48 to -0.02). Moreover, significant associations of manganese (Mn) with IgA, IgG and IgM were demonstrated (β = 0.10, 95% CI = 0.04 to 0.18; β = 0.07, 95% CI = 0.03 to 0.12; β = 0.10, 95% CI = 0.03 to 0.18, respectively). Cadmium (Cd) were associated with higher levels of IgM. QGC models showed the positive association of the metal mixtures with IgA and IgG, with Mn playing a major role. Mn and Cd had positive contributions to IgM, while As had negative contributions to IgE. In the BKMR models, the latent continuous outcomes of IgA and IgG showed a significant increase when all the metals were at their 60th percentile or above compared to those at their 50th percentile. Therefore, exposure to metals was associated with maternal Igs, and mainly showed that Mn was associated with increased levels of IgA, IgG and IgM, and As was associated with low IgE levels.

Association between multipollutant exposure and thyroid hormones in elderly people: A cross-sectional study in China

Environmental chemicals have been indicated to cause disruption of thyroid homeostasis in human populations. However, previous studies mostly focused on single group of chemicals. Herein, we investigate the independent and combined effects of multiple pollutants on thyroid homeostasis, including thyroid-stimulating hormone (TSH), total and free thyroxine (tT4 and fT4) and total and free triiodothyronine (tT3 and fT3) in elderly people. These environmental pollutants (n = 144) are from ten categories, including phenols, parabens, perfluoroalkyl substances (PFASs), polychlorinated biphenyls (PCBs), phthalate esters (PAEs), polycyclic aromatic hydrocarbons (PAHs), organochlorine pesticides (OCPs), organophosphate pesticides (OPPs), synthetic pyrethroids (SPs), herbicides, and metals. Few studies have evaluated the health risks of these 144 chemicals, especially their joint effects. In single-pollutant evaluations, multiple linear regression (MLR) models were used to estimate the independent associations between multiple exposures and thyroid biomarkers. In multi-pollutant evaluations, elastic net regression and Bayesian kernel machine regression (BKMR) models were used to estimate the combined associations. The MLR models showed that 41 chemicals were significantly related to THs levels. BKMR models revealed the most important chemical groups: metals for TSH, PAHs, SPs and PCBs for tT4, herbicides and SPs for tT3. This study will contribute to the understanding of multipollutant exposure and help prioritize specific chemical groups related to thyroid hormone disruption.

Single and mixed effects of multiple volatile organic compounds exposure on hematological parameters in the U.S. adult population

BackgroundMost research exploring the correlation between volatile organic compounds (VOCs) and hematological parameters have focused on single VOCs. Our study aimed to explore the single and combined effects of VOCs on hematological parameters through three statistical models. MethodsData from 4 cycles of the National Health and Nutrition Examination Survey (NHANES) were used in this study. The correlations between single exposure to 16 VOCs and hematological parameters in the general population were assessed by weighted multiple linear regression. Weighted quantile sum (WQS) and Bayesian kernel machine regression (BKMR) models were used to explore the relationship between the combined important VOCs selected by the least absolute shrinkage and selection operator (LASSO) and hematological parameters, as well as the effects of smoking status on them. ResultsA total of 4089 adults were included in the study. We found that a variety of VOCs were significantly associated with hematological parameters. Among them, N-acetyl-S-(benzyl)-l-cysteine (BMA) was significantly negatively correlated with white blood cell (WBC), red blood cell (RBC), lymphocyte, and neutrophil counts. N-acetyl-S-(3-hydroxypropyl-1-methyl)-l-cysteine (HPMMA) was significantly positively correlated with WBC, monocyte, lymphocyte, and neutrophil counts. In the WQS analysis, the WQS index of the VOCs mixtures was positively correlated with WBC (β: 0.031; P < 0.001), monocyte (0.023; P = 0.021), and neutrophil (0.040; P = 0.001) counts, while negatively associated with RBC (−0.013; P < 0.001) counts. The BKMR model revealed that combined exposure to VOCs levels ≥70th percentile was significantly associated with lower RBC counts, and BMA was identified as the dominant contributor. Smoking significantly influenced the relationship between VOCs and hematological parameters. ConclusionsOur study indicated the effects of single and overall VOCs exposure on hematological parameters and suggested the hematotoxicity as well as pro-inflammatory effects of VOCs, which had strong public health implications for reducing the potential health hazards of VOCs exposure to the hematologic system.

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.

Analyzing the impact of phthalate and DINCH exposure on fetal growth in a cohort with repeated urine collection

BackgroundMost previous studies investigating the associations between prenatal exposure to phthalates and fetal growth relied on measurements of phthalate metabolites at a single time point. They also focused on weight at birth without assessing growth over pregnancy, preventing the identification of potential periods of fetal vulnerability. We examined the associations between pregnancy urinary phthalate metabolites and fetal growth outcomes measured twice during pregnancy and at birth. MethodsFor 484 pregnant women, we assessed 13 phthalate and two 1,2-cyclohexane dicarboxylic acid, diisononyl ester (DINCH) metabolite concentrations from two within-subject weekly pools of up to 21 urine samples (median of 18 and 34 gestational weeks, respectively). Fetal biparietal diameter, femur length, head and abdominal circumferences were measured during two routine pregnancy follow-up ultrasonographies (median 22 and 32 gestational weeks, respectively) and estimated fetal weight (EFW) was calculated. Newborn weight, length, and head circumference were measured at birth. Associations between phthalate/DINCH metabolite and growth parameters were investigated using adjusted linear regression and Bayesian kernel machine regression models. ResultsDetection rates were above 99 % for all phthalate/DINCH metabolites. While no association was observed with birth measurements, mono-iso-butyl phthalate (MiBP) and mono-n-butyl phthalate (MnBP) were positively associated with most fetal growth parameters measured at the second trimester. Specifically, MiBP was positively associated with biparietal diameter, head and abdominal circumferences, while MnBP was positively associated with EFW, head and abdominal circumferences, with stronger associations among males. Pregnancy MnBP was positively associated with biparietal diameter and femur length at third trimester. Mixture of phthalate/DINCH metabolites was positively associated with EFW at second trimester. ConclusionsIn this pregnancy cohort using repeated urine samples to assess exposure, MiBP and MnBP were associated with increased fetal growth parameters. Further investigation on the effects of phthalates on child health would be relevant for expanding current knowledge on their long-term effects.

Association between polycyclic aromatic hydrocarbons and infertility in U.S. women: National Health and Nutrition Examination Survey 2013–2016

Although there is a body of research indicating the potential impact of polycyclic aromatic hydrocarbons (PAHs) exposure on male infertility, the understanding of how PAH might affect female infertility is still limited. This study aimed to evaluate associations of PAHs, both individually and as a mixture, with female infertility using multiple logistic regression, Bayesian kernel machine regression (BKMR), and quantile g-computation (QGC) models based on data from the National Health and Nutrition Examination Survey (NHANES) 2013–2016. The study included 729 female participants. Multiple logistic regression results indicated that there was a significant association between the third tertile of 2-hydroxy fluorene (2-OHFLU) and female infertility, and the OR was 2.84 (95% CI: 1.24–6.53, P value = 0.015) compared with the first tertile after adjusting for the potential covariates. The BKMR model revealed a positive overall trend between mixed PAH exposure and female infertility, particularly when the mixture was at or above the 55th percentile, where 2-hydroxynaphthalene (2-OHNAP) and 1-hydroxypyrene (1-OHPYR) were the primary influences of the mixture. The univariate exposure-response function indicated positive associations between individual PAH exposure, specifically 2-OHNAP, 2-OHFLU, and 1-OHPYR, and female infertility. The QGC model also indicated a positive trend between exposure to a mixture of PAHs and female infertility, although it did not reach statistical significance (OR = 1.33, 95%CI: 0.86–2.07), with 1-OHPYR having the greatest positive effect on the outcome. This study suggested that exposure to PAHs may be associated with female infertility and further research is needed to consolidate and confirm these findings.

Joint and interactive effects of metal mixtures on liver damage: Epidemiological evidence from repeated-measures study

BackgroundThe impact of heavy metals on liver function has been examined in numerous epidemiological studies. However, these findings lack consistency and longitudinal validation. MethodsIn this study, we conducted three follow-up surveys with 426 participants from Northeast China. Blood and urine samples were collected, along with questionnaire information. Urine samples were analyzed for concentrations of four metals (chromium [Cr], cadmium [Cd], lead [Pb], and manganese [Mn]), while blood samples were used to measure five liver function indicators (alanine aminotransferase [ALT], aspartate aminotransferase [AST], albumin [ALB], globulin [GLB], and total protein [TP]). We utilized a linear mixed-effects model (LME) to explore the association between individual heavy metal exposure and liver function. Joint effects of metal mixtures were investigated using quantile g-computation and Bayesian kernel machine regression (BKMR). Furthermore, we employed BKMR and Marginal Effect models to examine the interaction effects between metals on liver function. ResultsThe LME results demonstrated a significant association between urinary heavy metals (Cr, Cd, Pb, and Mn) and liver function markers. BKMR results indicated positive associations between heavy metal mixtures and ALT, AST, and GLB, and negative associations with ALB and TP, which were consistent with the g-comp results. Synergistic effects were observed between Cd-Cr on ALT, Mn-Cr and Cr-Pb on ALB, while an antagonistic effect was found between Mn-Pb and Mn-Cd on ALB. Additionally, synergistic effects were observed between Mn-Cr on GLB and Cd-Cr on TP. Furthermore, a three-way antagonistic effect of Mn-Pb-Cr on ALB was identified. ConclusionExposure to heavy metals (Cr, Cd, Mn, Pb) is associated with liver function markers, potentially leading to liver damage. Moreover, there are joint and interaction effects among these metals, which warrant further investigation at both the population and mechanistic levels.

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

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

The Relationship Between Plasma Nickel Concentrations and Type 2 Diabetes Mellitus Risk: A Protective Effect Within a Specific Range

BackgroundNickel is considered an essential nutrient for certain microbial, plant, and animal species, but its role in human health remains controversial. Some studies have reported the relationship between nickel and type 2 diabetes mellitus (T2DM), but the results are not consistent and the mechanism is not clear, which needs further exploration. AimTo investigate the possible correlation between nickel and T2DM. MethodsWe conducted a case-control study of 192 patients with T2DM and 189 healthy controls at a hospital in central China. Plasma concentrations of nickel and six other trace elements were measured with inductively coupled plasma mass spectrometry. Logistic regression models, restricted cubic spline models (RCS), and Bayesian kernel machine regression (BKMR) were used to evaluate the relationship between plasma nickel and T2DM and its metabolic risk factors, as well as the presence or absence of interactions between nickel and other elements. ResultsThe T2DM group exhibited considerably lower plasma nickel levels than the control group (P < 0.001). Whether using a crude or adjusted model, logistic regression analysis finds a negative correlation between nickel levels and the risk of T2DM (P trend < 0.001). According to the RCS, the risk of T2DM reduces with rising nickel levels when the value is below 6.1 μg/L; nickel has a negative linear correlation with fasting plasma glucose (FPG), an inverse U-shaped connection with superoxide dismutase (SOD), and a positive linear correlation with malondialdehyde (MDA) (all P overall < 0.05). The plasma nickel concentration was positively correlated with zinc, vanadium, and chromium (r = 0.23, 0.11, and 0.19, respectively; all P < 0.05) and negatively correlated with copper (r = − 0.11, P < 0.05). In the BKMR model, interactions of nickel with zinc on T2DM and SOD, nickel with chromium on T2DM and homeostasis model assessment of β cell (HOMA-β), and nickel with copper on FPG, homeostasis model assessment of insulin (HOMA-IR), and MDA were observed. ConclusionNickel may have a dual effect on the risk of T2DM, with a protective range of less than 6.1 μg/L. Potential interactions between nickel, copper, zinc, and chromium existed in their associations with T2DM and its metabolic risk factors.

Combined association of urinary volatile organic compounds with chronic bronchitis and emphysema among adults in NHANES 2011–2014: The mediating role of inflammation

Evidence on the association of volatile organic compounds (VOCs) with chronic bronchitis (CB) and emphysema is spare and defective. To evaluate the relationship between urinary metabolites of VOCs (mVOCs) with CB and emphysema, and to identify the potential mVOC of paramount importance, data from NHANES 2011–2014 waves were utilized. Logistic regression was conducted to estimate the independent association of mVOCs with respiratory outcomes. Least absolute shrinkage and selection operator (LASSO) regression was performed to screen a parsimonious set of CB- and emphysema-relevant mVOCs that were used for further co-exposure analyses of weight quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR). Mediation analysis was employed to detect the mediating role of inflammatory makers in such associations. In single exposure analytic model, nine mVOCs were individually and positively associated with CB, while four mVOCs were with emphysema. In WQS regression, positive association between LASSO selected mVOCs and CB was identified (OR = 1.82, 95% CI: 1.25 to 2.69), and N-acetyl-S-(4-hydroxy-2-butenyl)-l-cysteine (MHBMA3) weighted the highest. Results from BKMR further validated such combined association and the significance of MHBMA3. As for emphysema, significantly positive overall trend of mVOCs was only observed in BKMR model and N-acetyl-S-(N-methylcarbamoyl)-l-cysteine (AMCC) contributed most to the mixed effect. White blood cell count (WBC) and lymphocyte number (LYM) were mediators in the positive pattern of mVOCs mixture with CB, while association between mVOCs mixture and emphysema was significantly mediated by LYM and segmented neutrophils num (NEO). This study demonstrated that exposure to VOCs was associated with CB and emphysema independently and combinedly, which might be partly speculated that VOCs were linked to activated inflammations. Our findings shed novel light on VOCs related respiratory illness, and provide a new basis for the contribution of certain VOCs to the risk of CB and emphysema, which has potential public health implications.

Environmental exposure to per- and polyfluoroalkyl substances mixture and asthma in adolescents.

Previous epidemiological studies about the relationship between per- and polyfluoroalkyl substances (PFAS) concentrations and adolescent asthma have typically examined single PFAS, without considering the mixtures effects of PFAS. Using data from the 2013-2018 National Health and Nutrition Examination Survey (NHANES), 886 adolescents aged 12-19years were included in this study. We explored the association between PFAS mixture concentrations and adolescent asthma using weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) models, respectively. After adjusting for confounders, the results of the WQS regression and BKMR models were consistent, with mixed exposure to the five PFAS not significantly associated with asthma in all adolescents. The association remained nonsignificant in the subgroup analysis by sex. Our study demonstrated no significant association between mixed exposure to PFAS and adolescent asthma, and more large cohort studies are needed to confirm this in the future.

Associations between serum per- and polyfluoroalkyl substances as mixtures and lipid levels: A cross-sectional study in Jinan

Per- and polyfluoroalkyl substances (PFASs) are known to be linked with dyslipidemia. Between March and June 2022, we collected 575 fasting serum samples from individuals without occupational exposure in Jinan, China. Eighteen PFASs were analyzed using UHPLC-Orbitrap MS. Multiple linear regression (MLR), Bayesian kernel machine regression (BKMR), and Quantile g-computation (QGC) models were utilized to assess the effects of both individual PFAS and PFAS mixtures on serum lipid levels, including triglycerides (TG), cholesterol (CHO), high-density lipoprotein (HDL), and low-density lipoprotein (LDL). The PFAS mixture, composed of perfluoroheptanoic acid (PFHpA), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), perfluoroundecanoic acid (PFUnDA), perfluorododecanoic acid (PFDoDA), perfluorotridecanoic acid (PFTrDA), perfluorohexane sulfonate (PFHxS), perfluoroheptane sulfonic acid (PFHpS), perfluorooctane sulfonate (PFOS), and 6:2 chlorinated polyfluoroalkyl ether sulfonate (6:2 Cl-PFESA), showed a positive association with CHO and LDL levels, while no distinct trend was noted in HDL and TG levels about changes in PFAS mixtures levels in BKMR and QGC models, adjusted for gender, age, BMI, occupation, and educational level. The effects of individual PFASs on lipid levels were in general consistent across MLR, BKMR and QGC models. PFUnDA and PFTrDA demonstrated greater impacts on blood lipid levels compared to other PFAS, albeit with varied directional effects. Age-stratified analysis revealed PFAS mixture effect was more pronounced in participants aged higher than 40. No obvious trend in lipid levels with changes in PFAS mixture levels in participants with age ranged from 18 to 40, while positive association between PFAS mixture and CHO and LDL was detected in participants aged higher than 40.

The Correlation between Metal Mixed Exposure and Lung Function in Different Ages of the Population.

Herein, we explored the overall association between metal mixtures and lung functions in populations of varying ages and the relationship among the associated components. The 2007-2012 National Health and Nutrition Examination Survey data of 4382 American participants was analyzed, and generalized linear, elastic net, quantile g-computation, and Bayesian kernel machine regression models were used to evaluate the relationship between exposure to the metal mixture and lung function at various ages. The results of barium exposure at distinct stages revealed that children and adolescents exhibited greater lung function changes than those in adults and the elderly. Additionally, compared with children and adolescents, cadmium- and arsenic-containing metabolites contributed to nonconductive lung function changes in adults and the elderly exposed to metal mixtures. The results showed that the effects of exposure to metal mixtures on lung function in children and adolescents were predominantly caused by lead and barium. Altogether, children and adolescents were found to be more susceptible to metal-exposure-mediated lung function changes than adults and the elderly.

Association between prenatal exposure to per- and polyfluoroalkyl substances and infant anthropometry: A prospective cohort study

BackgroundPer- and polyfluoroalkyl substances (PFAS) are a group of synthetic organic chemicals with potential endocrine-disrupting effects, and have been found to impair the physical growth of offspring in both experimental and epidemiological studies. We aimed to investigate the effects of prenatal PFAS exposure on repeated measurements of multiple anthropometric indicators in infants. MethodPFAS were measured in serum samples collected from pregnant women at 12–16 gestational weeks. We calculated z-scores for the weight-for-age (WAZ), weight-for-length (WLZ), head circumference-for-age (HCZ), arm circumference-for-age (ACZ), triceps skinfold-for-age (TSZ), and subscapular skinfold-for-age (SSZ) at birth, 6 months, and 12 months of age according to the child growth standards of the World Health Organization (WHO) for anthropometric indicators. A total of 964 mother–infant pairs were included. A multivariate linear regression was performed to examine the associations between prenatal PFAS concentrations and anthropometric indicators at each time point. A generalized estimating equation (GEE) model was used to examine the longitudinal effects of PFAS exposure on repeated measurements of anthropometric indicators. Ultimately, a Bayesian kernel machine regression (BKMR) model was used to assess the joint effects of the PFAS mixture on anthropometric indicators. ResultsIn GEE models, perfluorododecanoic acid (PFDoA) in the high tertile group was associated with increased WAZ/WLZ, with β values (95% confidence intervals (CI)) of 0.12 (0.00, 0.23) and 0.18 (0.03, 0.32), respectively. Perfluorononanoic acid (PFNA) was associated with increased ACZ in the middle and high tertile groups. The BKMR models also presented the associations of the PFAS mixture with increased WAZ/WLZ throughout infancy, with more profound effects in females. Meanwhile, a pattern of inverse associations was observed between the perfluorooctanoic acid (PFOA) concentrations in the high tertile group and decreased WAZ, WLZ, and HCZ in males. In addition, the associations between PFAS and increased TSZ/SSZ at birth were identified by both linear regression and BKMR models. ConclusionPrenatal PFAS exposure (PFNA and PFDoA) was associated with increased infant anthropometry, especially in female infants, while prenatal PFOA exposure was associated with decreased weight, and head and arm circumference in male infants. The findings indicate that prenatal PFAS exposure may impair the growth trajectory of offspring.

Association between Heavy Metals and Trace Elements in Cancerous and Non-cancerous Tissues with the Risk of Colorectal Cancer Progression in Northwest China.

Alterations in heavy metals and trace element levels may be associated with various cancers. However, the role of this interaction in colorectal cancer (CRC) progression is unclear. In recent years, Principal Component Analysis (PCA) and Bayesian Kernel Machine Regression (BKMR) models have provided new ideas for analyzing the effects of metal mixtures on CRC progression. Herein, we assessed the differences in the levels of arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), nickel (Ni), selenium (Se), and zinc (Zn) in tumors and adjacent healthy tissues, to investigate the relationship between heavy metals/trace elements and CRC progression. Surgical samples of CRC and noncancerous tissues were collected, and trace metal levels were analyzed using inductively coupled plasma mass spectrometry (ICP-MS). Logistic regression, PCA, and BKMR models were used to investigate the relationship between heavy metals and trace elements and the degree of tumor differentiation and lymph node metastasis in CRC. Cancer tissues showed lower As, Cd, Co, and Cr concentrations, and higher Se concentrations than healthy tissues (P < 0.05). In addition, CRC patients with poorly differentiated tumors and/or positive lymph node metastases had lower levels of Cd, Zn, Cu, and Se (P < 0.05). Logistic regression showed that single metal concentration was negatively correlated with CRC progression. PCA and BKMR models also showed that the metal mixture concentration was negatively correlated with CRC progression, with Cd contributing the most. Overall, changes in heavy metal and trace element levels may be related to the development of CRC; however, further mechanistic studies are required.

Association of per- and polyfluoroalkyl substances (PFAS) with periodontitis: the mediating role of sex hormones

ObjectivesTo investigate the association between serum per- and polyfluoroalkyl substances (PFAS) and periodontitis, and further explore the possible mediating role of sex hormones in this association.MethodsWe extracted data from National Health and Nutrition Examination Survey (NHANES) 2009–2014. Univariable and multivariable logistic regression models were performed to investigate the association between serum levels of seven PFASs and periodontitis. Bayesian kernel machine regression (BKMR) was conducted to assess the joint effect of PFASs in mixtures. Mediation analyses were used to explore the potential mediating role of sex hormones.ResultsParticipants with periodontitis had higher concentrations of serum perfluorooctane sulfonate (PFOS) and perfluorononanoic acid (PFNA) than those without periodontitis (both P < 0.05). In fully adjusted models, high serum concentrations of PFOS and PFNA were positively associated with periodontitis (tertile 3 vs. tertile 1: prevalence ratio (PR) = 1.19 for PFOS, 95% CI: 1.01–1.39; PR = 1.17 for PFNA, 95% CI: 1.02–1.34). The results from the BKMR models consistently showed a positive association between PFAS mixtures and periodontitis. Of note, testosterone and the ratio of testosterone to estradiol significantly mediated the relationship between high level of PFOS and periodontitis, accounting for 16.5% and 31.7% of the total effect, respectively. Sensitivity analyses yielded similar results when using periodontal clinical indices (mean loss of attachment, mean periodontal probing depth, and the number of teeth) as dependent variables.ConclusionsThese findings provide evidence to support a positive association between certain PFASs and periodontitis, which might be partially mediated by sex hormones.

Association between urinary organophosphate ester metabolite exposure and thyroid disease risk among US adults: National Health and Nutrition Examination Survey 2011-2014.

Organophosphate esters (OPEs) may interfere with thyroid function, but the relationship between OPEs and thyroid disease remains unclear. This study aims to elucidate the relationship between OPEs exposure and thyroid disease risk in the general population in the United States. Data were obtained from the 2011-2014 National Health and Nutrition Examination Survey cycle. All participants were tested for seven OPE metabolites in their urine and answered questions about whether they had thyroid disease through questionnaires. Logistic regression was employed to analyze the association between exposure to individual OPE metabolites and thyroid disease. Weighted Quantile Sum (WQS) regression modeling was utilized to assess exposure to mixed OPE metabolites and risk of thyroid disease. Bayesian kernel machine regression(BKMR) models to analyze the overall mixed effect of OPE metabolites. A total of 2,449 participants were included in the study, 228 of whom had a history of thyroid disease. Bis(1,3-dichloro-2-propyl) phos (BDCPP), Diphenyl phosphate (DPHP) and Bis(2-chloroethyl) phosphate (BCEP) were the top three metabolites with the highest detection rates of 91.75%, 90.77% and 86.57%, respectively. In multivariate logistic regression models, after adjustment for confounding variables, individuals with the highest tertile level of BCEP were significantly and positively associated with increased risk of thyroid disease (OR=1.57, 95% CI=1.04-2.36), using the lowest tertile level as reference. In the positive WQS regression model, after correcting for confounding variables, mixed exposure to OPE metabolites was significantly positively associated with increased risk of thyroid disease (OR=1.03, 95% CI=1.01-1.06), with BCEP and DPHP having high weights. In the BKMR model, the overall effect of mixed exposure to OPE metabolites was not statistically significant, but univariate exposure response trends showed that the risk of thyroid disease decreased and then increased as BCEP exposure levels increased. The study revealed a significant association between exposure to OPE metabolites and an increased risk of thyroid disease, with BCEP emerging as the primary contributor. The risk of thyroid disease exhibits a J-shaped pattern, whereby the risk initially decreases and subsequently increases with rising levels of BCEP exposure. Additional studies are required to validate the association between OPEs and thyroid diseases.