Integrating population epidemiology and bioinformatics to decipher the hypertensive effects of per- and polyfluoroalkyl substances mixtures

Parabens exposure, depression, and cardiovascular metabolic health in the elderly: Findings from a cross-sectional study in China.

PFNA dominates the association between PFAS mixture exposure and hypertension risk: The mediating role of estradiol in the U.S. adults.

Cardiovascular disease (CVD) remains a leading cause of mortality in China. The triglyceride-glucose (TyG) index and body roundness index (BRI)-have separately shown associations with CVD risk, but their interaction, as well as their combined effects and interplay with inflammatory markers remain unclear. We conducted a prospective cohort study using data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020. A total of 7,853 participants without pre-existing CVD were included. We examined mediation, cross-lagged path, interaction and joint association analysis to explore the interrelationships between TyG and BRI on CVD. Cox proportional hazards models and restricted cubic spline analysis, receiver operating characteristic (ROC), and weighted quantile sum (WQS) were performed to further investigate the associations between TyG, BRI, and CVD. During a median follow-up of 9.0years, 1,922 participants (24.48%) developed CVD. In fully adjusted models, baseline BRI mediated 40.14% of the association between baseline TyG and CVD risk, with an indirect effect HR of 1.053 (95% CI: 1.035-1.073). Follow-up BRI mediated 51.46% of the association between baseline TyG and CVD risk, with an indirect effect HR of 1.046 (95% CI: 1.028-1.068). Per standard deviation increase in baseline BRI led to an average increase of 0.12 standard deviation in follow-up TyG levels. A significant antagonistic interaction was observed, aligned with the finding that the combination of low TyG and high BRI presents the highest CVD risk. Additionally, WQS analysis highlights waist circumference (WC) as the most substantial contributor (weight = 0.523). Joint elevation of composite indexes (TyG-BRI and TyG + BRI) with hs-CRP further stratified CVD risk, with participants having elevated levels of all markers showing the highest risk. Composite indexes, particularly TyG + BRI, showed the highest CVD risk (HR: 1.773, 95% CI: 1.499-2.097), along with the limited discriminatory ability on CVD (AUC < 0.65). In conclusion, our study highlights the critical role of BRI as a mediator in the relationship between TyG and CVD risk. The findings indicate that both baseline and follow-up BRI significantly contribute to the pathway linking TyG to CVD, suggesting that individuals with higher BRI are at an increased risk. The antagonistic interaction underscores the complexity of metabolic risk factors in CVD development and emphasizes the need for a multifaceted approach in risk assessment and management. Future research should focus on elucidating the biological mechanisms underlying this interaction and exploring potential interventions that target body composition and metabolic health to mitigate CVD risk in high-risk populations.

Clustered health risk behaviors association with mental health problems among adolescents: A cross-sectional study from China.

Cardiovascular diseases are the leading cause of death, and reducing them requires identifying risk factors, among which exposure to environmental pollutants is well documented. Metal(loid) exposure is related to oxidative stress (OxS), in which oxygen radicals react with biomolecules, thus altering the cardiovascular system. This study aimed to identify cardiovascular risk factors and their relationship with OxS biomarkers. A cross-sectional study (CINVESTAV-063-2020/HIM-2019-025) was conducted in an apparently healthy pediatric population (N = 359). Metal(loid)s were measured by ICP-MS, and enzymatic and colorimetric techniques were applied for OxS determination. Descriptive and bivariate analyses were performed. A weighted quantile sum (WQS) approach was used to examine the mixture effect and identify the components associated with a health outcome. Finally, spatial autocorrelation was estimated for metal(loid)s and environmental sources. The median age of the participants was 14years, 30% were overweight or obese, and cardiovascular risk was 32.6%. Median metal(loid) concentrations (ng/mL) were 34.5 for arsenic, 27.2 for copper, 0.837 for manganese, and 7.45 for vanadium. There was an association between the multi-OxS biomarkers and cardiovascular risk (OR: 0.4291, 95% CI: 0.281-0.577). However, there was no relationship between the multi-metal(loid)s and cardiovascular risk, but there were significant correlations between the OxS biomarkers and urinary metal(loid)s. Spatial autocorrelation was observed for vanadium and arsenic. OxS biomarkers were associated with cardiovascular risk and some related factors. Furthermore, the presence of metal(loid)s is involved in redox imbalance, which appears to increase cardiovascular risk, and the spatial autocorrelation observed suggests exposure to vanadium and arsenic.

Background: Long-term PM2.5 exposure is a major health risk, yet the heterogeneity of its chemical components and sources is often overlooked in risk assessments. Methods: Using county-level census data for 1990, 2000, and 2010 in China, we employed a difference-in-differences (DID) study design to associate all-cause mortality with long-term exposure to PM2.5 from five sources and by five components. We applied log-linear models and several mixed exposure models (weighted quantile sum (WQS), ridge regression, random forest, XGBoost, and an ensemble model) to capture effect heterogeneity with cross-validation for evaluating the prediction performance and Shapley additive explanations (SHAP) values for interpretability. Results: Each 10 μg/m3 increment in PM2.5 was associated with a 3.16% increase in all-cause mortality (95% confidence interval [95% CI]: 2.13-4.20%). Industry (3.46%, for each interquartile range increment), power (2.32%), and residential usage (1.46%) were the most hazardous sources; ammonium (6.46%), nitrate (4.23%), and black carbon (3.93%) were the most potent components. Random forest and the ensemble model showed superior predictive performance, identifying industrial-sourced black carbon as the leading contributor to PM2.5-associated mortality. Conclusion: The health effects of PM2.5 differ considerably by the source sector and chemical component. Industrial black carbon exhibits higher toxicity and should be given priority when designing the air-pollution-control strategies.

Organophosphorus pesticide (OPP) exposure is a public health concern, yet the link between chronic low-level exposure and chronic kidney disease (CKD) in the general population remains unclear. This study investigated the association between urinary dialkyl phosphate (DAP) metabolites and CKD prevalence among U.S. adults. Data from 5751 participants aged ≥ 20years across five NHANES cycles (2003-2008, 2011-2016) were analyzed. Urinary DAP metabolites served as biomarkers of recent OPP or environmental DAP exposure. CKD associations were assessed using survey-weighted regression models. Secondary mixture analyses, including weighted quantile sum (WQS), Bayesian kernel machine regression (BKMR), and quantile g-computation (QGC), were conducted on metabolites with adequate detection frequency. Overall, 18.7% of participants met CKD criteria. Higher concentrations of diethylphosphate (DEP) and diethylthiophosphate (DETP) were consistently associated with increased CKD prevalence across models. Mixture analyses identified DEP and DETP as primary contributors to the overall association. This cross-sectional study indicates a potential link between exposure to specific DAPs (DEP and DETP) andan increased risk of CKD, supported by multiple statistical models. Longitudinal research to establish causality and clinical screening for OPPs exposure in unexplained CKD cases is warranted.

Long-term exposure to fine particulate matter (PM2.5) increases atherosclerotic cardiovascular disease (ASCVD) risk, but evidence on its components' effects and the potential benefits achievable through PM2.5 interventions remains limited. We used data from participants in the China Health and Retirement Longitudinal Study (CHARLS) with low ASCVD risk at baseline. The associations between PM2.5, its components (black carbon, ammonium, nitrate, sulfate, organic matter), and 10-year ASCVD risk were evaluated using the generalized linear regression. Co-exposure effects of PM2.5 components were estimated using weighted quantile sum (WQS) regression and quantile g-computation. Effects of hypothetical PM2.5 interventions (reducing annual averages to 35, 25, and 15 μg/m3) on ASCVD risk were assessed using the parametric g-formula. Each 10 μg/m3 increase in PM2.5 raised 10-year ASCVD risk by 18.3% (RR = 1.183, 95% CI: 1.099-1.267). Each 0.1 μg/m3 increase in black carbon and 1 μg/m3 increase in ammonium, nitrate, sulfate, and organic matter increased risks by 18.4%, 10.7%, 6.8%, 9.0%, and 6.7%, respectively. Nitrate contributed most (46.3%). Parametric g-formula estimated that reducing PM2.5 to 35, 25, and 15 μg/m3 lowered ASCVD risk by 2.78%, 3.15%, and 3.43%, respectively. Psychological conditions (e.g. depression) mediated 10-year ASCVD risk. Interaction analysis showed females were more susceptible to PM2.5 and its components. Long-term exposure to PM2.5 and its components elevates ASCVD risk in Chinese adults, with greater susceptibility in females. Reducing PM2.5 concentrations significantly mitigates ASCVD risk.

This study aimed to assess the associations between particulate matter (PM) exposures and depressive symptom trajectories, as well as the potential contributing role of loneliness in these associations. The analysis included 11,758 participants (≥45 years), with depressive symptoms and covariate data from the China Health and Retirement Longitudinal Study (2011-2020) and PM data from the ChinaHighAirPollutants dataset. Depressive symptom trajectories were identified using group-based trajectory modeling. Individual and combined effects of PM on depressive symptom trajectories were assessed using multivariable logistic regression and weighted quantile sum (WQS) regression, with results reported as odds ratio (OR) and 95% confidence interval (CI). A serial multiple mediator model was used to evaluate the contributing role of loneliness. Five depressive symptom trajectories were identified: stable-low, stable-moderate, stable-high, decreasing, and increasing. PM exposures were positively associated with more severe depressive symptom trajectory groups (stable-high [PM10: OR = 1.10, 95% CI 1.04-1.16; WQS: OR = 1.41, 95% CI 1.09-1.82] and increasing [PM1.0: OR = 1.44, 95% CI 1.06-1.98; PM2.5: OR = 1.10, 95% CI 1.02-1.19; PM10: OR = 1.10, 95% CI 1.06-1.13; WQS: OR = 1.21, 95% CI 1.01-1.45]) compared to the stable-low symptoms trajectory. Loneliness contributed to 26.73%-29.73% of the associations between PM exposure and depressive symptom trajectories. Exposures to individual and mixed PM pollutants increase the risk of severe depressive symptom trajectory groups, and reducing loneliness alleviates these effects. The findings underscore the need for further coordinated control of PM pollutants and alleviating loneliness to prevent depressive symptoms.

Childhood dyslexia risk elevated by heavy metal mixtures from e-waste: A machine learning-driven mixture modeling study.

Oligohydramnios is a clinically relevant but understudied pregnancy complication. This study evaluated the association between maternal exposure to mixed ambient air pollutants and the risk of oligohydramnios, focusing on identifying critical exposure windows and pollutant-specific concentration thresholds. We conducted a retrospective cohort study of 7,608 singleton live births from a tertiary hospital in northwestern China (2015-2019). Individual-level air pollution exposure was estimated by inverse distance weighting. Weighted quantile sum (WQS) and lagged WQS (lWQS) models were used to assess mixture effects and time-specific susceptibility. Restricted cubic spline models were applied to estimate concentration-response relationships and preventive thresholds of representative weeks and corresponding key pollutants. The WQS index showed a significant joint effect for daily average exposure during whole pregnancy (odds ratio = 1.204, 95% confidene interval 1.049, 1.285), mainly driven by NO2 and O3. The lWQS model identified the early and late pregnancy as critical exposure windows. As representative time points for early, mid, and late pregnancy, estimated O3 thresholds were 49.28 μg/m3 (week 4), 36.28 μg/m3 (week 16), and 37.40 μg/m3 (week 32); the NO2 threshold at week 32 was 37.41 μg/m3. Maternal exposure to mixed air pollutants, particularly O3 and NO2, increases the risk of oligohydramnios. Findings highlight gestational timing and pollutant-specific targets for prenatal environmental protection.

Prenatal exposure to multiple insecticides and reduced birth weight: a possible mediating role of plasma metabolomic alterations.

A study on the association between early-pregnancy hair metal levels and gestational diabetes mellitus.

Binational association between polyunsaturated fatty acid intake and depression in Korea and the US: A cross-national cross-sectional study.

Associations and mechanistic insights of multiple metal exposure and hypothyroidism: Evidence from population data and network toxicology.

The dose-response relationship between seminal plasma metal mixtures and oligo-astheno-teratozoospermia: a hospital-based case-control study.

Association of inflammation mediated blood heavy metals with plasma atherogenic index: NHANES analysis 2015-2020.

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.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading chronic liver disease worldwide. While total saturated fatty acid (SFA) intake has been linked to MASLD, the contribution of specific SFAs and the mechanism underlying the SFA-MASLD association remain unclear. This study evaluated the associations of individual SFAs with MASLD and the mediating roles of insulin resistance and serum albumin.We used data from seven NHANES cycles (2005-2018) in a cross-sectional analysis. Associations between individual SFAs and MASLD were estimated via logistic regression with restricted cubic splines (RCS). Weighted quantile sum (WQS) and quantile g-computation (QGC) models assessed the mixture associations. Mediation analysis evaluated the proportions of these associations accounted for by serum albumin and insulin resistance.Compared with the reference group, the highest tertile of intake was associated with increased odds of MASLD for C4:0 (OR=1.12, 95% CI: 1.01-1.25), C6:0 (OR=1.15, 95% CI: 1.04-1.28), C14:0 (OR=1.20, 95% CI: 1.08-1.33), C16:0 (OR=1.24, 95% CI: 1.12-1.38), and C18:0 (OR=1.25, 95% CI: 1.12-1.39). RCS models revealed largely linear dose-response relationships. Both WQS and QGC indicated a positive joint association of SFAs with MASLD, with C16:0 identified as a major contributor. Among SFAs significantly associated with MASLD, insulin resistance accounted for 30.0%-47.4% of the associations, while serum albumin accounted for 5.9%-8.0%.Higher intakes of short- and long-chain SFAs, both individually and collectively, are associated with higher odds of MASLD. Insulin resistance and serum albumin may partially explain these associations. These findings support the development of precision dietary strategies targeting specific SFAs for MASLD prevention.