Search Results (68)

Background: Human lead exposure is a multi-pathway phenomenon that integrates internal biological burden with persistent residential environmental reservoirs. Although individual lead metrics have been linked to cardiometabolic dysfunction, current research often fails to capture the ‘exposome’ reality of joint, nonlinear, and interaction-dependent effects on metabolic outcomes like BMI. Objectives: To evaluate associations between biological (blood and urinary) and residential dust (window and floor) lead measures and BMI, and to characterize nonlinear and interaction-dependent mixture effects using Bayesian Kernel Machine Regression (BKMR). Methods: We analyzed data from NHANES 2001–2002, a nationally representative survey of the U.S. noninstitutionalized civilian population. Window and floor dust lead (µg/ft²) were obtained from the NHANES household dust component, and blood lead (µg/dL) and urinary lead (µg/L) were measured using standardized NHANES laboratory protocols. BMI was calculated from measured height and weight. Missing data were addressed using multivariate imputation by chained equations. Descriptive statistics and multivariable linear regression were used to estimate adjusted associations between individual lead metrics and BMI, controlling for age, gender, income, race/ethnicity, and education. BKMR was then applied to evaluate joint mixture effects, estimate univariate and bivariate exposure–response functions, and quantify relative exposure importance using posterior inclusion probabilities (PIPs). Results: In covariate-adjusted linear regression, blood lead (β = −0.485; 95% CI: −0.566, −0.405; p < 0.001) and window dust lead (β = −0.00047; 95% CI: −0.00067, −0.00026; p < 0.001) were inversely associated with BMI, whereas floor dust lead was positively associated (β = 0.258; 95% CI: 0.209, 0.306; p < 0.001). Urinary lead was inversely but not significantly associated with BMI (β = −0.111; 95% CI: −0.235, 0.013; p = 0.079). In BKMR, blood lead was the dominant contributor, with a posterior inclusion probability (PIP; proportion of iterations in which an exposure is selected) of 1.00. Window dust lead showed modest inclusion (PIP = 0.26), whereas urinary and floor dust lead were not selected (PIP = 0.00). Exposure–response functions indicated modest nonlinearity for blood lead and greater divergence for the blood lead–window dust lead pairing at higher exposure levels. The overall mixture effect declined across increasing joint exposure quantiles, crossing the null near the median and becoming increasingly negative at higher mixture levels. Conclusions: In our study, lead metrics showed heterogeneous associations with BMI, and BKMR indicated that internal lead burden (blood lead) primarily drove mixture-related BMI patterns, with evidence that window dust lead may modify mixture effects at higher co-exposure levels. These findings support evaluating multiple lead exposure pathways jointly and using flexible mixture models to capture nonlinear and interaction-dependent relationships with BMI. Full article

Phthalates (PAEs) are ubiquitous endocrine-disrupting chemicals (EDCs), but their association with early pregnancy loss (gestational age ≤ 12 weeks) remains controversial. This study enrolled pregnant women aged 20–45 years in Zunyi City, China, and included 107 cases and 349 controls following propensity score matching. Logistic regression, restricted cubic spline (RCS) analysis, Bayesian kernel machine regression (BKMR), and weighted quantile sum (WQS) regression were employed to investigate associations between urinary phthalate metabolites and early pregnancy loss. We found that monoethyl phthalate (MEP), mono(2-ethylhexyl) phthalate (MEHP), monooctyl phthalate (MOP), mono(2-ethyl-5-oxohexyl) phthalate (MEOHP), and mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) were associated with spontaneous abortion in early pregnancy, with corresponding odds ratios (ORs; 95% confidence intervals [CIs]) of 1.62 (1.26–2.09), 1.49 (1.07–2.09), 1.64 (1.26–2.12), 1.78 (1.27–2.50), 2.63 (1.90–3.64), 1.41 (1.11–1.79), and 5.39 (3.53–8.25). Non-linear dose–response relationships were observed between exposure to MMP, MEP, MEHP, MOP, monobenzyl phthalate (MBZP), MEOHP, MEHHP, and mono-(3-carboxypropyl) phthalate (MECPP) and early pregnancy loss (non-linear p < 0.05; overall p < 0.05). Co-exposure to multiple phthalate metabolites was also linked to a significantly non-linear elevation in the risk of early pregnancy loss (OR; 95% confidence interval [CI]) of 1.92 (1.76–2.15). Among these metabolites, MMP, MOP, MEOHP, and MECPP make the largest contribution to the correlation. In summary, our findings indicate that exposure to phthalate esters during early pregnancy is associated with early pregnancy loss, with MMP, MOP, MEOHP, and MECPP as the primary contributors. However, these results are based on a single urine sample, and caution is warranted when interpreting the findings. Full article

Parabens, a prevalent class of endocrine-disrupting chemicals (EDCs), are ubiquitous in consumer products; however, their role in linking pediatric allergic phenotypes remains poorly understood. This case-control study analyzed paraben levels in urine and indoor dust as proxies for internal and external exposures and investigated their associations with allergic rhinitis only (AR Only), asthma only (AS Only), and comorbidities (AR&AS) among children in Shanghai. The concentrations for each of four paraben compounds were quantitatively measured, and multi-pollutant frameworks—including Bayesian Kernel Machine Regression (BKMR) and Weighted Quantile Sum (WQS) regression—were employed to characterize the mixture exposure and risk. Propylparaben (PrP) was detectable in 100% of urine samples and over 90% of dust samples, and the concentrations ranked the highest out of the four compounds in both samples. Benzylparaben (BzP) was detected in >70% of urine samples and over 50% of dust samples at relatively lower levels. Urinary PrP exhibited significantly positive associations with all phenotypes (OR in 2.18–2.92) and BzP with the AR&AS Comorbidity (OR = 3.55, 95% CI: 1.32–9.55). Dust-borne PrP was associated with AR Only (OR = 2.26, 95% CI: 1.16–4.43), indicating a potential “Portal of Entry” effect via direct nasal deposition. According to BKMR and WQS analyses, urinary PrP and BzP emerged as two primary risk drivers. Using interaction analysis, an additive synergistic effect was observed between urinary PrP and BzP with parental history of allergy, suggesting heightened vulnerability to paraben exposure in genetically predisposed subgroups. In conclusion, children with respiratory allergies were associated with higher exposure to PrP and BzP and exhibited higher susceptibility in those with a parental history of allergy. Full article

(1) Background: Few studies have examined gestational paraben exposure and early childhood neurodevelopment. We evaluated associations between gestational exposure to methyl, ethyl and propyl paraben and neurodevelopment via the Child Behavior Checklist (CBCL) administered at ages 2, 3, and 4 years. (2) Methods: Gestational exposures were assessed using pooled prenatal urine samples from five time points across pregnancy. CBCL outcomes included internalizing, externalizing, and sub-scale scores. Covariate-adjusted generalized linear regression was employed to assess individual paraben exposures. Mixture analysis was performed using Bayesian Kernel Machine Regression and Quantile g-computation. (3) Results: In individual paraben analyses, each paraben was associated with increased externalizing behaviors, particularly ethylparaben (age 2: β = 0.40, 95% CI = −0.02, 0.83; age 3: β = 0.42, 95% CI = −0.19, 0.01; age 4: β = 0.18, 95% CI = −0.34, 0.70), ADHD problems at age 2 (β = 0.21, 95% CI = 0.05, 0.37), and both aggressive behavior (β = 0.38, 95% CI = 0.01, 0.74) and oppositional defiant problems (β = 0.25, 95% CI = 0.09, 0.41) at age 3. All three parabens were also associated with a reduction in withdrawn symptoms for males, especially at age 2 (ethylparaben: β = −0.09, 95% CI = −0.01, 0.85; methylparaben: β = −0.20, 95% CI = −0.34, −0.05; propylparaben: β = −0.13, 95% CI = −0.24, −0.03). The parabens mixture was associated with elevated scores in multiple CBCL subscales, though only association with oppositional defiant scores at age 3 reached significance in both BKMR (change in score when all components are at 50th percentile values compared with their 75th percentile values = 0.15; 95% CI = 0.01, 0.29) and quantile g-computation (β = 0.33, 95% CI = 0.02, 0.65), driven primarily by ethylparaben. (4) Conclusions: Individual parabens and the paraben mixture showed significant association with domains of childhood neurodevelopment, with possible detriments especially evident (a) at earlier time points, (b) in male children, and (c) in terms of externalizing behaviors. Full article

Depression is a major public health concern, and evidence continues to show that environmental toxicants may contribute to its development. This study evaluated the association between depressive symptoms and per- and polyfluoroalkyl substances (PFAS), heavy metals, phthalates, and organophosphate metabolites using data from NHANES 2017–2018. Depressive symptoms were measured with the Patient Health Questionnaire-9 (PHQ-9). Environmental exposure variables were analyzed using multivariable linear regression and Bayesian Kernel Machine Regression (BKMR). All models adjusted for demographic, socioeconomic, behavioral, and clinical covariates. In multivariable linear regression models adjusted for demographic, socioeconomic, behavioral, and clinical covariates, higher urinary dimethylphosphate concentrations were significantly associated with increased depressive symptom scores (β = 0.15; 95% CI: 0.04, 0.27; p = 0.0098). Mono-(2-ethylhexyl) phthalate (MEHP) was also positively associated with PHQ-9 scores (β = 0.001; 95% CI: 0.0003, 0.0019; p = 0.0043). Because environmental mixtures tend to follow non-linear patterns, BKMR analysis was run. BKMR analyses indicated that organophosphate metabolites exhibited the greatest overall contribution to depressive symptoms (group posterior inclusion probability = 0.7875), with diethylphosphate emerging as the most influential individual exposure within the group (conditional PIP = 0.7211). Exposure–response functions suggested non-linear and threshold relationships for several metabolites. These findings identify specific organophosphate and phthalate metabolites as potential contributors to depressive symptoms and support the importance of evaluating chemical mixtures rather than single exposures. Additional longitudinal studies are needed to clarify temporal relationships and to inform public health efforts aimed at reducing exposure to organophosphate pesticides and endocrine-disrupting chemicals. Full article

Associations between prenatal exposure to phthalates, bisphenols and their mixtures and early childhood allergic conditions and asthma were examined. Five hundred and fifty-six mother–child pairs from the Alberta Pregnancy Outcomes and Nutrition (APrON) cohort participated. Urine samples collected from mothers during the second trimester of pregnancy were analyzed for phthalates and bisphenols. A child health questionnaire, completed by mothers when children were 12, 24, and 36 months, asked whether children had experienced allergic conditions (i.e., food allergies, eczema, rash) or asthma. In single-chemical models, associations varied with child age. Higher prenatal concentrations of mono-benzyl phthalate (MBzP) were associated with lower odds of eczema at 12 months. At 36 months, higher mono-methyl phthalate (MMP) was associated with increased odds of eczema, whereas higher mono-carboxy-octyl phthalate (MCOP) was associated with reduced odds. Higher prenatal MCOP was also associated with higher odds of rash at 12 months, and higher MMP was associated with higher odds of rash at 36 months. Higher bisphenol S (BPS) was associated with increased odds of asthma at 12 months but decreased odds of eczema and rash at 36 months. Sex-specific effects were also noted. In multi-chemical exposure least absolute shrinkage and selection operator (LASSO) models, several phthalate metabolites and BPS were selected as the best predictors of eczema and rash at 36 months of age. Bayesian kernel machine regression (BKMR) mixture models suggested that BPS was the most important chemical in predicting eczema in children at 36 months, while MMP and BPS were the most important chemicals in predicting rash at 36 months. Prenatal exposure to certain phthalate metabolites and BPS predicted allergic conditions and asthma in young children, with patterns varying by age and sex. Prenatal exposure to these chemicals may differentially influence immune development and contribute to the development of early-life allergic conditions, with potentially sex-specific susceptibility. Full article

Exposure to environmental pollutants, including toxic metals, volatile organic compounds (VOCs), and per- and polyfluoroalkyl substances (PFAS), has been increasingly linked to impaired kidney function. However, the combined effects of these exposures, along with essential elements, on kidney health remain poorly understood. This study aimed to evaluate the independent and cumulative or mixture effects of toxic metals (cadmium, lead, and mercury), essential elements (iron, manganese, and selenium), PFAS (PFOA and PFOS), and VOCs (m-/p-xylene and o-xylene) on kidney function as measured by estimated glomerular filtration rate (eGFR). Using data from the National Health and Nutrition Examination Survey (NHANES), we applied multiple imputation to address missing data and implemented statistical techniques, including Bayesian Kernel Machine Regression (BKMR), quantile g-computation, and Weighted Quantile Sum Regression (WQSR) to assess complex exposure–response relationships, including non-linear, potential synergistic, and antagonistic effects. The results indicated that several exposures were correlated, particularly o-xylene with m-/p-xylene (r = 0.77), Cd with Pb (r = 0.46), and PFOS with PFOA (r = 0.61). eGFR was negatively associated with Pb, PFOS, PFOA, and Hg. In the BKMR analysis, overall posterior inclusion probabilities (PIPs) highlighted PFOS, Cd, Se, Mn, and Fe as the most influential exposures. Quantile g-computation highlighted Cd and Mn as major contributors, while WQSR modeling confirmed Mn as a key contributor. The findings underscore the importance of considering complex interactions in environmental exposure assessments. While essential elements may offer protective effects, toxic metals, PFAS, and VOCs remain critical contributors to kidney dysfunction. These insights highlight the need for integrative risk assessment approaches and public health strategies aimed at mitigating harmful exposures while promoting optimal nutrient balance. Full article

People are exposed to mixtures of metals, per- and polyfluoroalkyl substances (PFAS), phthalates, and polycyclic aromatic hydrocarbons (PAH) rather than single chemicals, yet mixture inference is hampered by high dimensionality, correlation, missingness, and left-censoring below limits of detection (LOD). We analyzed 2013–2014 National Health and Nutrition Examination Survey (NHANES) biomarkers (n = 4367) to (i) recover latent, interpretable co-exposure structures and (ii) quantify how these mixtures relate to liver health. To denoise and handle censoring, we applied Principal Component Pursuit with LOD adjustment (PCP-LOD), decomposing the exposure matrix into a non-negative low-rank component (population co-exposure profiles) and a sparse component (individual spikes), and then used Bayesian Kernel Machine Regression (BKMR) to estimate nonlinear and interactive associations with AST, ALT, GGT, ALP, total bilirubin, and the Fatty Liver Index (FLI), retaining analytes with ≥50% detection. PCP-LOD revealed coherent clusters (e.g., long-chain PFAS grouping; shared metal loadings), while the sparse layer highlighted episodic phthalate elevations. BKMR indicated outcome-specific mixture effects: PAHs and selected phthalates showed consistently positive associations with ALP, GGT, and FLI; PFAS (PFOS, PFNA, PFOA) exhibited modest associations with ALP and bilirubin; metals displayed mixed directions. A joint increase in the overall mixture from the 25th to 75th percentile corresponded to an upward shift in FLI and a smaller rise in ALT. This censoring-aware low-rank-plus-sparse framework coupled with flexible mixture modeling recovers actionable exposure architecture and reveals clinically relevant links to liver injury and steatosis, motivating longitudinal and mechanistic studies to strengthen causal interpretation. Full article

Background: Liver disease is a growing global health burden. While individual environmental exposures like heavy metals (lead, cadmium, mercury) and behavioral factors such as smoking and alcohol use are known risk factors, their combined impact and the underlying physiological pathways are poorly understood. Allostatic load (AL), a measure of cumulative physiological stress, is a potential mediator or modifier in the relationship between these chronic exposures and liver disease. This study aimed to investigate the joint effects of heavy metals and behavioral exposures on liver health and to examine the mediating role of AL. Methods: This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES) 2017–2018 cycle. We assessed blood concentrations of the environmental and lifestyle variables in relation to liver biomarkers and the Fatty Liver Index (FLI). Descriptive statistics were used to summarize participant characteristics. Multivariable linear regression and Bayesian Kernel Machine Regression–Causal Mediation Analysis (BKMR-CMA) were used to model combined, nonlinear effects of the exposure–outcome mixture and to evaluate the mediating role of AL. Results: Lead exposure was positively associated with higher AST (β = 0.65, p = 0.04) and GGT (β = 1.99, p = 0.05), while smoking increased GGT (β = 0.79, p = 0.03) and ALP (β = 0.78, p < 0.01). AL independently predicted higher FLI (β = 3.66, p < 0.001). Conclusions: This study highlights that liver health is influenced by the combined effects of environmental pollutants, behaviors, and cumulative biological stress. While lead exposure and smoking were independently linked to liver enzyme elevations, and AL to FLI, mediation by AL was limited, though trends suggest AL may still amplify chronic metabolic pathways leading to liver disease. Full article

Perfluoroalkyl substances (PFASs) possess immunosuppressive properties. However, their association with rheumatoid arthritis (RA) risk remains inconclusive across epidemiological studies. This study integrates population-based and mechanistic evidence to clarify the relationship between PFAS exposure and RA. We analyzed 8743 U.S. adults from the NHANES (2005–2018), assessing individual and mixed exposures to PFOA, PFOS, PFNA, and PFHxS using multivariable logistic regression, Bayesian kernel machine regression, quantile g-computation, and weighted quantile sum models. Network toxicology and molecular docking were utilized to identify core targets mediating immune disruption. The results showed that elevated PFOA (OR = 1.63, 95% CI: 1.41–1.89), PFOS (OR = 1.41, 1.25–1.58), and PFNA (OR = 1.40, 1.20–1.63) levels significantly increased RA risk. Mixture analyses indicated a positive joint effect (WQS OR = 1.06, 1.02–1.10; qgcomp OR = 1.26, 1.16–1.38), with PFOA as the primary contributor. Stratified analyses revealed stronger effects in females (PFOA Q4 OR = 3.75, 2.36–5.97) and older adults (≥60 years). Core targets included EGFR, SRC, TP53, and CTNNB1. PFAS mixtures increase RA risk, dominated by PFOA and modulated by sex/age. These findings help reconcile prior contradictions by identifying key molecular targets and vulnerable subpopulations, supporting regulatory attention to PFAS mixture exposure. Full article

Background: Environmental exposures, such as per- and polyfluoroalkyl substances (PFAS), in conjunction with social and behavioral factors, can significantly impact liver health. This research investigates the combined effects of PFAS (perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS), alcohol consumption, smoking, income, and education on liver function among the U.S. population, utilizing data from the 2017–2018 National Health and Nutrition Examination Survey (NHANES). Methods: PFAS concentrations in blood samples were analyzed using online solid-phase extraction combined with liquid chromatography–tandem mass spectrometry (LC-MS/MS), a highly sensitive and specific method for detecting levels of PFAS. Liver function was evaluated using biomarkers such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), gamma-glutamyltransferase (GGT), total bilirubin, and the fatty liver index (FLI). Descriptive statistics and multivariable linear regression analyses were employed to assess the associations between exposures and liver outcomes. Bayesian Kernel Machine Regression (BKMR) was utilized to explore the nonlinear and interactive effects of these exposures. To determine the relative influence of each factor on liver health, Posterior Inclusion Probabilities (PIPs) were calculated. Results: Linear regression analyses indicated that income and education were inversely associated with several liver injury biomarkers, while alcohol use and smoking demonstrated stronger and more consistent associations. Bayesian Kernel Machine Regression (BKMR) further highlighted alcohol and smoking as the most influential predictors, particularly for GGT and total bilirubin, with posterior inclusion probabilities (PIPs) close to 1.0. In contrast, PFAS showed weaker associations. Regression coefficients were small and largely non-significant, and PIPs were comparatively lower across most liver outcomes. Notably, education had a higher PIP for ALT and GGT than PFAS, suggesting a more protective role in liver health. People with higher education levels tend to live healthier lifestyles, have better access to healthcare, and are generally more aware of health risks. These factors can all help reduce the risk of liver problems. Overall mixture effects demonstrated nonlinear trends, including U-shaped relationships for ALT and GGT, and inverse associations for AST, FLI, and ALP. Conclusion: These findings underscore the importance of considering both environmental and social–behavioral determinants in liver health. While PFAS exposures remain a long-term concern, modifiable lifestyle and structural factors, particularly alcohol, smoking, income, and education, exert more immediate and pronounced effects on hepatic biomarkers in the general population. Full article

Environmental exposures to heavy metals, polychlorinated biphenyls (PCBs), dioxins, and furans have been associated with adverse cardiovascular outcomes, yet their combined effects remain underexplored. This study examined the joint influence of these contaminants on cardiovascular risk indicators in a representative sample of U.S. adults from the 2003–2004 National Health and Nutrition Examination Survey (NHANES). Biomarkers of exposure included lead, cadmium, mercury, twelve PCB congeners, seven dioxins, and ten furans. Cardiovascular outcomes were assessed using blood pressure, Framingham Risk Score (FRS), and lipid profiles. Associations were analyzed using multivariable linear regression and Bayesian Kernel Machine Regression (BKMR), adjusting for age, sex, ethnicity, body mass index, smoking, alcohol consumption, and income. The results demonstrated that metals, particularly mercury, were strongly associated with increased blood pressure and altered HDL cholesterol. PCBs were predominantly linked to elevated systolic blood pressure and FRS, with PCB156 and PCB126 identified as principal contributors. Furans exhibited the strongest associations with dyslipidemia, including elevated LDL cholesterol, total cholesterol, and triglycerides. Combined exposure analysis revealed a complex pattern, with increasing pollutant burdens associated with rising blood pressure and risk scores but declining lipid levels. These findings underscore the outcome-specific effects of pollutant mixtures and suggest that chronic low-level exposure to multiple environmental contaminants may contribute to cardiovascular dysfunction in the general population. Further longitudinal research is needed to confirm these associations and guide risk reduction strategies. Full article

Per- and polyfluoroalkyl substances (PFASs) are ubiquitous environmental contaminants with potential endocrine-disrupting properties. This study examines the association between exposure to multiple PFASs and pan-cancers associated with sex hormones (PCSH) while accounting for potential non-linear relationships and interactions. We analyzed data from the National Health and Nutrition Examination Survey (NHANES), spanning two-year cycles from 1999 to 2012 and including 14,373 participants. Serum concentrations of six PFAS—perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), perfluorohexanesulfonic acid (PFHxS), perfluorodecanoic acid (PFDE), perfluorononanoic acid (PFNA), and perfluoroundecanoic acid (PFUA)—were assessed for their relationship with PCSH. The statistical analyses included descriptive statistics, Spearman and Pearson correlation analyses, and both linear and logistic regression models. Additionally, Bayesian kernel machine regression (BKMR) was applied to capture potential nonlinear relationships and interactions. The initial t-tests showed a statistically significant difference in PFOS levels between individuals with and without PCSH (p = 0.0022), with higher mean PFOS levels in the PCSH group. Chi-square tests revealed a significant association between ethnicity and PCSH (p < 0.001). Linear and logistic regression analyses revealed significant associations for PFOS. BKMR analysis identified PFOA as having the highest posterior inclusion probability, indicating its importance in explaining PCSH risk. Univariate exposure-response analysis revealed limited individual PFAS effects. However, bivariate analysis indicated a complex U-shaped interaction pattern among many joint PFAS assessments. The overall exposure effect analysis suggested that the combined impact of all PFASs was more strongly associated with PCSH at exposure levels below the 0.5 quantile compared to higher levels. Single-variable interaction analyses highlighted PFOA and PFOS as the most interactive PFASs when evaluating their interaction with combined exposure to all other PFASs. In summary, while the initial findings suggested a positive association between PFOS and PCSH, the BKMR analysis revealed complex non-linear relationships and interactions among PFAS. These findings highlight the importance of evaluating PFASs as a mixture rather than as individual chemicals and using techniques that can capture non-linear relationships and interactions. Full article

This study assessed the relationship between environmental chemical mixtures—including metals, per- and polyfluoroalkyl substances (PFAS), phthalates, and plasticizers—and key cardiovascular health markers using data from the 2013–2014 National Health and Nutrition Examination Survey (NHANES). The combined effects of these pollutants on cardiovascular markers were evaluated using Bayesian Kernel Machine Regression (BKMR), a flexible, non-parametric modeling approach that accommodates nonlinear and interactive relationships among exposures. BKMR was applied to assess both the joint and individual associations of the chemical mixture with systolic blood pressure (SBP), high-density lipoprotein (HDL), low-density lipoprotein (LDL), diastolic blood pressure (DBP), total cholesterol, and triglycerides. As part of the BKMR analysis, posterior inclusion probabilities (PIPs) were estimated to identify the relative importance of each exposure within the mixture. These results highlighted phthalates as major contributors to LDL, SBP, total cholesterol, HDL, and triglycerides while plasticizers were associated with LDL, SBP, HDL, and triglycerides. Metals and PFAS were most strongly linked to LDL, DBP, total cholesterol, and SBP. The overall mixture effect indicated that cumulative exposures were associated with lower LDL and SBP and elevated DBP, suggesting an increased cardiovascular risk. Triglycerides exhibited a complex quantile-dependent trend, with higher exposures associated with reduced levels. These findings underscore the importance of mixture-based risk assessments that reflect real-world exposure scenarios. Full article

Background: Cardiovascular disease (CVD) is a major global health burden influenced by genetic, behavioral, and environmental factors. Among these, exposure to per- and poly-fluoroalkyl substances (PFASs) and toxic metals has been increasingly implicated in adverse cardiovascular outcomes. However, the mediating role of dietary inflammation in these associations remains unclear. Objective: This study investigates the relationship between PFAS and metal exposures and CVD risk, focusing on the potential mediating role of diet, operationalized through the Dietary Inflammatory Index (DII). Additionally, this study examines age as an effect modifier in these associations. Methods: Utilizing data from the National Health and Nutrition Examination Survey (NHANES) 2017–2018 cycle (n = 660), we assessed environmental exposures (lead, cadmium, mercury, perfluorooctanoic acid-PFOA, perfluorooctane sulfonate-PFOS), dietary inflammatory potential (DII), and cardiovascular markers (blood pressure, lipid profile, C-reactive protein). Statistical analyses included linear regression and Bayesian Kernel Machine Regression-Causal Mediation Analysis (BKMR-CMA) to estimate the direct, indirect (through DII), and total effects of exposure on CVD risk biomarkers. Results: Linear regression revealed significant associations between mercury and reduced systolic blood pressure (SBP) (p = 0.017) and cadmium with increased C-reactive protein (CRP) (p = 0.006). Mediation analysis suggested dietary inflammation may play a role, though estimates were imprecise. Conclusions: PFAS and metals may influence CVD risk through inflammatory pathways, with potential age-related differences. Future longitudinal studies are needed to clarify these complex interactions, reduce measurement error, and guide age-specific exposure regulations. Full article