Bayesian Kernel Machine Regression Models Research Articles

Associations between exposure to phthalates and liver function among women undergoing assisted reproductive technology

Phthalates can induce hepatotoxicity in animal studies. We aimed to assess the associations of individual and mixture of urinary phthalate metabolites with serum liver function indicators among 764 women undergoing assisted reproductive technology (ART). In linear models, we observed inverse correlations between urinary mono-benzyl phthalate and serum total protein (TP) as well as globulin (β=–0.27 and –0.23, respectively, P<0.05). Additionally, negative associations were identified between mono-isobutyl phthalate and mono-butyl phthalate (MBP) and aspartate aminotransferase-to-alanine transaminase ratio (AST/ALT) (P<0.05). MBP and the sum of all phthalate metabolites (∑all.phth.m) were positively associated with bilirubin, with β ranging from 0.14 to 0.47. Most phthalate metabolites were also positively related to gamma-glutamyl transferase (GGT) (all P<0.05). In Bayesian kernel machine regression models, phthalate mixture was positively associated with bilirubin and GGT, whereas inversely associated with AST/ALT and TP. Our results suggest that phthalate exposure may impair liver function among women undergoing ART.

Phthalate exposure and subfecundity in preconception couples: A nested case-control study

BackgroundPhthalates (PAEs) are endocrine-disrupting chemicals ubiquitously found in the environment. This study aimed to examine the association between exposure of PAEs and subfecundity in preconception couples. MethodsThis is a nested case-control study based on preconception cohort. Preconception couples with intention to conceive were enrolled and followed up until a clinically confirmed pregnancy or 12 menstrual cycles of preparation for conception. A total of 107 couples with subfecundity- time to pregnancy (TTP) more than 12 menstrual cycles, and 144 couples ≤12 cycles were included in the analysis. The levels of PAE metabolites in one spot urine samples were detected and compared between the groups. The weighted quantile sum (WQS) regression model and Bayesian kernel machine regression (BKMR) model were used to examine the joint effects of couples’ exposure to PAEs on subfecundity. ResultsUsing the multivariate binary logistic regression model, compared to the lowest quartile of urinary ∑PAEs concentration group, both preconception females (aOR=2.42, 95% CI: 1.10–5.30, p=0.027) and males (aOR=2.99, 95% CI: 1.36–6.58, p=0.006) in the highest quartile group had an increased risk of subfecundity, and a dose-response relationship was observed between PAEs and the risk of subfecundity. The WQS analyses found that co-exposure to PAE mixture was a risk factor for subfecundity in preconception female (aOR=1.76, 95% CI: 1.38–2.26, p<0.001), male (aOR=1.58, 95% CI: 1.20–2.08, p=0.001), and couple (aOR=2.39, 95% CI: 1.61–3.52, p<0.001). The BKMR model found a positive combined effect of mixed exposure to PAEs on the risk of subfecundity. ConclusionsPAEs increase the risk of subfecundity in preconception couples. Our research reinforced the need of monitoring PAE exposure for the purpose of improving human reproductive health.

Complex interplay of heavy metals and renal injury: New perspectives from longitudinal epidemiological evidence

BackgroundEpidemiological studies have reported associations between heavy metals and renal function. However, longitudinal studies are required to further validate these associations and explore the interactive effects of heavy metals on renal function and their directional influence. MethodThis study, conducted in Northeast China from 2016 to 2021, included a four-time repeated measures design involving 384 participants (1536 observations). Urinary concentrations of chromium (Cr), cadmium (Cd), manganese (Mn), and lead (Pb) were measured, along with renal biomarkers including urinary microalbumin (umAlb), urinary albumin-to-creatinine ratio (UACR), N-acetyl-β-D-glucosaminidase (NAG), and β2-microglobulin (β2-MG) levels. Estimated glomerular filtration rate (eGFR) was calculated. A Linear Mixed Effects Model (LME) examined the association between individual metal exposure and renal biomarkers. Subsequently, Quantile g-computation and Bayesian Kernel Machine Regression (BKMR) models assessed the overall effects of heavy metal mixtures. Marginal Effect models examined the directional impact of metal interactions in the BKMR on renal function. ResultResults indicate significant impacts of individual and combined exposures of Cr, Cd, Pb, and Mn on renal biomarkers. Metal interactions in the BKMR model were observed, with synergistic effects of Cd-Cr on NAG, umAlb, UACR; Cd-Pb on NAG, UACR; Pb-Cr on umAlb, UACR, eGFR-MDRD, eGFR-EPI; and an antagonistic effect of Mn-Pb-Cr on UACR. ConclusionBoth individual and combined exposures to heavy metals are associated with renal biomarkers, with significant synergistic interactions leading to renal damage. Our findings elucidate potential interactions among these metals, offering valuable insights into the mechanisms linking multiple metal exposures to renal injury.

Environmental perchlorate, thiocyanate, and nitrate exposures and bone mineral density: a national cross-sectional study in the US adults.

Associations of perchlorate, thiocyanate, and nitrate exposures with bone mineral density (BMD) in adults have not previously been studied. This study aimed to estimate the associations of individual and concurrent exposure of the three chemicals with adult BMD. Based on National Health and Nutrition Examination Survey (NHANES, 2011-2018), 1618 non-pregnant adults (age ≥ 20years and 47.0% female) were included in this study. Survey-weighted linear regression models were used to estimate individual urinary perchlorate, thiocyanate, and nitrate concentrations with lumbar spine BMD and total BMD in adults. Then, weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) models were conducted to evaluate associations of co-occurrence of the three chemicals with adult BMD. In all participants, nitrate exposure was inversely associated with lumbar spine BMD (β = - 0.054, 95%CI: - 0.097, - 0.010). In stratification analyses, significant inverse associations were observed in female and participants older than 40years old. In WQS regressions, significant negative associations of the weighted sum of the three chemicals with total and lumbar spine BMD (β = - 0.014, 95%CI: - 0.021, - 0.007; β = - 0.011, 95%CI: - 0.019, - 0.004, respectively) were found, and the dominant contributor was nitrate. In the BKMR models, non-linear dose-response associations of nitrate exposure with lumbar spine and total BMD were observed. These findings suggested that environmental perchlorate, thiocyanate, and nitrate exposure may reduce adult BMD and nitrate is the main contributor.

Urinary volatile organic compound metabolites and COPD among US adults: mixture, interaction and mediation analysis

BackgroundVolatile organic compounds (VOCs) encompass hundreds of high production volume chemicals and have been reported to be associated with adverse respiratory outcomes such as chronic obstructive pulmonary disease (COPD). However, research on the combined toxic effects of exposure to various VOCs on COPD is lacking. We aimed to assess the effect of VOC metabolite mixture on COPD risk in a large population sample.MethodsWe assessed the effect of VOC metabolite mixture on COPD risk in 5997 adults from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2020 (pre-pandemic) using multivariate logistic regression, Bayesian weighted quantile sum regression (BWQS), quantile-based g-Computation method (Qgcomp), and Bayesian kernel machine regression (BKMR). We explored whether these associations were mediated by white blood cell (WBC) count and total bilirubin.ResultsIn the logistic regression model, we observed a significantly increased risk of COPD associated with 9 VOC metabolites. Conversely, N-acetyl-S-(benzyl)-L-cysteine (BMA) and N-acetyl-S-(n-propyl)-L-cysteine (BPMA) showed insignificant negative correlations with COPD risk. The overall mixture exposure demonstrated a significant positive relationship with COPD in both the BWQS model (adjusted odds ratio (OR) = 1.30, 95% confidence interval (CI): 1.06, 1.58) and BKMR model, and with marginal significance in the Qgcomp model (adjusted OR = 1.22, 95% CI: 0.98, 1.52). All three models indicated a significant effect of the VOC metabolite mixture on COPD in non-current smokers. WBC count mediated 7.1% of the VOC mixture associated-COPD in non-current smokers.ConclusionsOur findings provide novel evidence suggesting that VOCs may have adverse associations with COPD in the general population, with N, N- Dimethylformamide and 1,3-Butadiene contributing most. These findings underscore the significance of understanding the potential health risks associated with VOC mixture and emphasize the need for targeted interventions to mitigate the adverse effects on COPD risk.

Fetal and Infancy Exposure to Phenols, Parabens, and Phthalates and Anthropometric Measurements up to 36 Months, in the Longitudinal SEPAGES Cohort.

Endocrine-disrupting chemicals may play a role in adiposity development during childhood. Until now literature in this scope suffers from methodologic limitations in exposure assessment using one or few urine samples and missing assessment during the infancy period. We investigated the associations between early-life exposure to quickly metabolized chemicals and post-natal growth, relying on repeated within-subject urine collections over pregnancy and infancy. We studied the associations of four phenols, four parabens, seven phthalates, and one nonphthalate plasticizer from weekly pooled urine samples collected from the mother during second and third trimesters (median 18 and 34 gestational weeks, respectively) and infant at 2 and 12 months of age, and child growth until 36 months. We relied on repeated measures of height, weight and head circumference from study visits and the child health booklet to predict growth outcomes at 3 and 36 months using the Jenss-Bayley nonlinear mixed model. We assessed associations with individual chemicals using adjusted linear regression and mixtures of chemicals using a Bayesian kernel machine regression model. The unipollutant analysis revealed few associations. Bisphenol S (BPS) at second trimester was positively associated with all infant growth parameters at 3 and 36 months, with similar patterns between exposure at third trimester and all infant growth parameters at 3 months. Mono-n-butyl phthalate (MnBP) at 12 months was positively associated with body mass index (BMI), weight, and head circumference at 36 months. Mixture analysis revealed positive associations between exposure at 12 months and BMI and weight at 36 months, with MnBP showing the highest effect size within the mixture. This study suggests that exposure in early infancy may be associated with increased weight and BMI in early childhood, which are risk factors of obesity in later life. Furthermore, this study highlighted the impact of BPS, a compound replacing bisphenol A, which has never been studied in this context. https://doi.org/10.1289/EHP13644.

Human exposure characteristics of pharmaceutical and personal care product chemicals and associations with dietary habits

Considering the widespread presence of pharmaceutical and personal care products (PPCPs) in the environment and their adverse health effects, human exposure to PPCPs has caused worldwide concern. However, there remains insufficient information on the exposure assessment of the Chinese population. Based on this, the exposure levels of 13 PPCPs in the urine samples of 986 Chinese adults were measured, aiming to provide information on the prevalence of PPCP occurrence and investigate potential correlations between PPCP exposure and obesity. Results showed that the detection rates of these compounds in urine ranged from 28.12 % to 98.58 %, with median concentrations ranging below the limit of detection to 10.58 ng mL−1. Methyl-paraben (MeP) was the most dominant paraben and had the highest urinary concentration (median = 10.12 ng mL−1), while 4-hydroxy-benzophenone (4-OH-BP) was the dominant benzophenone derivative (median = 0.22 ng mL−1). In antibacterials, the urinary concentration of triclosan (mean = 42.00 ng mL−1) was much higher than that of triclocarban (mean = 0.63 ng mL−1). PPCP concentrations were significantly associated with sex, age, body mass index, education level, and annual household income (p < 0.050). Regression analysis of dietary habits showed that seafood and tea consumption may be significant exposure sources of PPCP exposure (p < 0.050). Furthermore, individual exposure to MeP (odds ratio (OR) < 1, p = 0.002) and 4-OH-BP (OR < 1, p = 0.009) exhibited a significantly negative association with obesity in females. Also, analysis results from quantile g-computation and Bayesian kernel machine regression models demonstrated that an inverse correlation between PPCP mixture exposure and obesity was significant in females. This study reports the extensive prevalence of PPCP exposure among adults from China, and may provide crucial insights into PPCP exposure dynamics. More epidemiological studies are need in the future, with a thorough knowledge of PPCP exposure.

Cholesterol mediates the effects of single and multiple environmental phenols in urine on obesity

BackgroundOverweight and obesity are among the leading chronic diseases worldwide. Environmental phenols have been renowned as endocrine disruptors that contribute to weight changes; however, the effects of exposure to mixed phenols on obesity are not well established.MethodsUsing data from adults in National Health and Nutrition Examination Survey, this study examined the individual and combined effects of four phenols on obesity. A combination of traditional logistic regression and two mixed models (weighted quantile sum (WQS) regression and Bayesian kernel-machine regression (BKMR)) were used together to assess the role of phenols in the development of obesity. The potential mediation of cholesterol on these effects was analyzed through a parallel mediation model.ResultsThe results demonstrated that solitary phenols except triclosan were inversely associated with obesity (P-value < 0.05). The WQS index was also negatively correlated with general obesity (β: 0.770, 95% CI: 0.644–0.919, P-value = 0.004) and abdominal obesity (β: 0.781, 95% CI: 0.658–0.928, P-value = 0.004). Consistently, the BKMR model demonstrated the significant joint negative effects of phenols on obesity. The parallel mediation analysis revealed that high-density lipoprotein mediated the effects of all four single phenols on obesity, whereas low-density lipoprotein only mediated the association between benzophenol-3 and obesity. Moreover, Cholesterol acts as a mediator of the association between mixed phenols and obesity. Exposure to single and mixed phenols significantly and negatively correlated with obesity. Cholesterol mediated the association of single and mixed environmental phenols with obesity.ConclusionsAssessing the potential public health risks of mixed phenols helps to incorporate this information into practical health advice and guidance.

Multiple xenoestrogen air pollutants and breast cancer risk: Statistical approaches to investigate combined exposures effect

Studies suggested that exposure to air pollutants, with endocrine disrupting (ED) properties, have a key role in breast cancer (BC) development. Although the population is exposed simultaneously to a mixture of multiple pollutants and ED pollutants may act via common biological mechanisms leading to synergic effects, epidemiological studies generally evaluate the effect of each pollutant separately. We aimed to assess the complex effect of exposure to a mixture of four xenoestrogen air pollutants (benzo-[a]-pyrene (BaP), cadmium, dioxin (2,3,7,8-Tétrachlorodibenzo-p-dioxin TCDD)), and polychlorinated biphenyl 153 (PCB153)) on the risk of BC, using three recent statistical methods, namely weighted quantile sum (WQS), quantile g-computation (QGC) and Bayesian kernel machine regression (BKMR). The study was conducted on 5222 cases and 5222 matched controls nested within the French prospective E3N cohort initiated in 1990. Annual average exposure estimates to the pollutants were assessed using a chemistry transport model, at the participants’ residence address between 1990 and 2011. We found a positive association between the WQS index of the joint effect and the risk of overall BC (adjusted odds ratio (OR) = 1.10, 95% confidence intervals (CI): 1.03–1.19). Similar results were found for QGC (OR = 1.11, 95%CI: 1.03–1.19). Despite the association did not reach statistical significance in the BKMR model, we observed an increasing trend between the joint effect of the four pollutants and the risk of BC, when fixing other chemicals at their median concentrations. BaP, cadmium and PCB153 also showed positive trends in the multi-pollutant mixture, while dioxin showed a modest inverse trend. Despite we found a clear evidence of a positive association between the joint exposure to pollutants and BC risk only from WQS and QGC regression, we observed a similar suggestive trend using BKMR. This study makes a major contribution to the understanding of the joint effects of air pollution.

Association of plasma trans fatty acid concentrations with blood pressure and hypertension in U.S. adults.

The present study aimed to evaluate the association of plasma trans fatty acids (TFAs) biomarkers with the risk of hypertension. Using data from the National Health and Nutrition Examination Surveys (NHANES 2009-2010), we conducted a thorough analysis using both the traditional regression model and the Bayesian Kernel Machine Regression (BKMR) model to investigate the associations of individual TFAs and their mixtures with systolic blood pressure (SBP), diastolic blood pressure (DBP), and the risk of hypertension in a sample of 1,970 American adults. The concentrations of TFAs were natural logarithms (ln) transformed to approximate a normal distribution. Multivariate linear regression models showed that each 1-unit increase in ln-transformed plasma concentrations of palmitelaidic, elaidic, vaccenic, and linolelaidic acids was associated with separate 2.94-, 3.60-, 2.46- and 4.78-mm Hg and 2.77-, 2.35-, 2.03-, and 3.70- mm Hg increase in SBP and DBP, respectively (P < 0.05). The BKMR model showed positive associations between the four TFAs mixtures and SBP and DBP. In addition, linolelaidic acid contributed the most to an increased blood pressure. Similar results were observed with the threshold of hypertension (≥130/80 mm Hg). Our findings provide preliminary evidence that plasma TFA concentrations are associated with increased blood pressure and the risk of hypertension in US adults. This study also suggests that linolelaidic acid might exhibit more deleterious effects on hypertension than other TFAs. Further studies should be conducted to validate these results.

Associations of prenatal exposure to bisphenols with infant anthropometry: A prospective cohort study

BackgroundBisphenols (BPs) have been shown to exhibit developmental toxicities. Epidemiological evidence on prenatal BPs exposure and infant growth primarily confined scopes to specific BPs and birth outcomes, with few studies focusing on infant growth and reporting inconsistent findings. The joint effect of prenatal exposure to BPs mixture on infant growth was rarely studied. ObjectiveThis study examined associations of prenatal exposure to individual bisphenol A (BPA) and its analogues (bisphenol F [BPF], bisphenol S [BPS], bisphenol AF [BPAF], and tetrachlorobisphenol A [TCBPA]) and their mixture with infant growth. MethodsUrinary concentrations of BPs in pregnant women were quantified. Weight, body mass index, skinfold thickness, and circumference measurements of infants were collected at birth, 6 and 12 months of age, rapid growth and overweight were further defined. Multiple linear regression models and Bayesian kernel machine regression models (BKMR) were used to analyze associations of exposure to individual BPs and BPs mixture with infants' anthropometric measurements, and to identify the important components among mixture. The risks for rapid growth and overweight of each BP were determined using modified Poisson regression models. ResultsA general profile of higher prenatal BPs exposure (mainly BPA, BPF, and BPS) associated with higher anthropometric measurements and higher risks of overweight during infancy was found. We also observed higher risks of rapid growth in infants following prenatal BPs exposure, with risk ratios ranging from 1.46 to 1.91. The joint effect of BPs mixture and single effect of each BP from the BKMR models were consistent with findings from the linear regression models, further suggesting that associations in girls were generally driven by BPA, BPF, or BPS, while in boys mainly by BPF. ConclusionPrenatal exposure to BPs and their mixture could increase anthropometric measurements of offspring during infancy, with implications of altered growth trajectory in future.

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 mixture 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 between single and multiple dietary vitamins and the risk of periodontitis: results from NHANES 2009-2014.

Periodontitis 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. This 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. For 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. The 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. Both 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.

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 of exposure to multiple perfluoroalkyl and polyfluoroalkyl substances and glucose metabolism in National Health and Nutrition Examination Survey 2017-2018.

To investigate the relationships between perfluoroalkyl and polyfluoroalkyl substances (PFASs) exposure and glucose metabolism indices. Data from the National Health and Nutrition Examination Survey (NHANES) 2017-2018 waves were used. A total of 611 participants with information on serum PFASs (perfluorononanoic acid (PFNA); perfluorooctanoic acid (PFOA); perfluoroundecanoic acid (PFUA); perfluorohexane sulfonic acid (PFHxS); perfluorooctane sulfonates acid (PFOS); perfluorodecanoic acid (PFDeA)), glucose metabolism indices (fasting plasma glucose (FPG), homeostasis model assessment for insulin resistance (HOMA-IR) and insulin) as well as selected covariates were included. We used cluster analysis to categorize the participants into three exposure subgroups and compared glucose metabolism index levels between the subgroups. Least absolute shrinkage and selection operator (LASSO), multiple linear regression analysis and Bayesian kernel machine regression (BKMR) were used to assess the effects of single and mixed PFASs exposures and glucose metabolism. The cluster analysis results revealed overlapping exposure types among people with higher PFASs exposure. As the level of PFAS exposure increased, FPG level showed an upward linear trend (p < 0.001), whereas insulin levels demonstrated a downward linear trend (p = 0.012). LASSO and multiple linear regression analysis showed that PFNA and FPG had a positive relationship (>50 years-old group: β = 0.059, p < 0.001). PFOA, PFUA, and PFHxS (≤50 years-old group: insulin β = -0.194, p < 0.001, HOMA-IR β = -0.132, p = 0.020) showed negative correlation with HOMA-IR/insulin. PFNA (>50 years-old group: insulin β = 0.191, p = 0.018, HOMA-IR β = 0.220, p = 0.013) showed positive correlation with HOMA-IR/insulin, which was essentially the same as results that obtained for the univariate exposure-response map in the BKMR model. Association of exposure to PFASs on glucose metabolism indices showed positive interactions between PFOS and PFHxS and negative interactions between PFOA and PFNA/PFOS/PFHxS. Our study provides evidence that positive and negative correlations between PFASs and FPG and HOMA-IR/insulin levels are observed, respectively. Combined effects and interactions between PFASs. Given the higher risk of glucose metabolism associated with elevated levels of PFAS, future studies are needed to explore the potential underlying mechanisms.

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.