The association between environmental toxin exposure and frailty: A full exposure group approach using NHANES 2013-2016.

Calibration of Cystatin C in the National Health and Nutrition Examination Surveys (NHANES)

Allergic sensitization is a key risk factor for but not synonymous with allergic disease

Exposure to brominated flame retardants (BFRs) may negatively impact human health. The association of BFRs with nonalcoholic fatty liver disease (NAFLD) in the general population is unclear. Meanwhile, limited studies have investigated the potential role of oxidative stress and inflammation in this link. We included 4110 adults from the 2009-2014 National Health and Nutrition Examination Survey (NHANES). NAFLD was diagnosed by serum alanine aminotransferase (ALT), hepatic steatosis index (HSI), and United States fatty liver index (USFLI). The link between a single BFR exposure and NAFLD was estimated using weighted logistic regression and restricted cubic splines (RCS). The quantile-based g-computation (QGC), weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) were applied to evaluate the overall correlation of BFRs mixtures with NAFLD and identify significant compounds. Furthermore, we investigated the potential mediation function of oxidative stress and inflammation. Our study demonstrated that specific concentrations of BFRs are related to an increased risk of NAFLD, both individually and when combined. PBB153, PBDE28, PBDE209, and PBDE153 exhibited the highest importance for NAFLD and were potential risk factors worthy of concern. Additionally, mediation analysis showed that absolute neutrophil cell count (ANC) and lymphocyte count (LC) (inflammation markers) have significantly mediated influences on the correlations of PBB153, PBDE85, and PBDE28 with N AFLD risk. Albumin (ALB) (oxidative stress marker) has notably mediated influences on the correlations of PBDE99, PBDE154, and PBDE85 with NAFLD risk. Men had higher serum BFRs concentrations than women, and the association between BFRs and NAFLD was also more prominent in men, which may be related to physiological differences between the sexes. Our findings offer evidence for single and mixed associations of BFRs and NAFLD in ordinary US adults. Furthermore, oxidative stress and chronic inflammation may mediate the effects of BFR exposure on NAFLD development.

Associations among blood heavy metals, neurofilament light chains and cognition function in US adults: NHANES 2013-2014.

Impact of polyfluoroalkyl chemicals and volatile organic compounds exposure on lung function of American adults

Perchlorates, nitrates, and thiocyanates are prevalent environmental chemicals. Their potential association with arthritis remains unexplored. This study aimed to investigate the link between perchlorate, nitrate, and thiocyanate exposure and arthritis, as well as the potential role of inflammation in this context. Utilizing the National Health and Nutrition Examination Survey (NHANES) data spanning from 2005 to 2016, the study enrolled 6597 participants aged 20-59 (young and middle-aged), of which 1045 had arthritis. Employing multivariate logistic regression modeling, multiple linear regression models, restricted cubic spline analysis, Bayesian kernel machine regression (BKMR) modeling, and mediation analysis, we assessed these relationships. There was a significant positive association between elevated urinary thiocyanate levels and arthritis risk [1.19 (1.11, 1.28)]. This association held true across subgroups of osteoarthritis (OA) [1.24 (1.10, 1.40)] and rheumatoid arthritis (RA) [1.33 (1.15, 1.55)]. Thiocyanate levels displayed a dose-dependent relationship with arthritis risk, showing a linear trend (nonlinear P > 0.05). Conversely, perchlorate and nitrate did not exhibit associations with arthritis risk. BKMR outcomes highlighted a positive correlation between a mixture of perchlorate, nitrate, and thiocyanate and arthritis risk, with thiocyanate being the predominant predictors. Moreover, BKMR and generalized linear model analyses unveiled no significant synergistic effect of urinary perchlorate, nitrate, and thiocyanate on arthritis risk. Furthermore, thiocyanate exposure has been linked to elevated levels of inflammatory indicators (white blood cell, neutrophils, lymphocytes, and systemic immune-inflammatory index (SII)). Heightened thiocyanate exposure may be linked to elevated arthritis risk, either single or in combined effects. Additionally, thiocyanate exposure is associated with heightened inflammation levels.

The main objective of our study is to explore the associations between combined exposure to urinary heavy metals and high remnant cholesterol (HRC), a known cardiovascular risk factor. Utilizing data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018, we conducted a cross-sectional analysis of 5690 participants, assessing urinary concentrations of ten heavy metals. Ten heavy metals in urine were measured by inductively coupled plasma mass spectrometry (ICP-MS). Fasting residual cholesterol ≥0.8 mmol/L was defined as HRC (using blood samples). Statistical analyses included weighted multivariable logistic regression, weighted quantile sum (WQS) regression, quantile g-computation (qgcomp), and Bayesian kernel machine regression (BKMR) to evaluate the associations of heavy metal exposure with HRC. Stratified analyses based on individual characteristics were also conducted. Multivariable logistic regression found that the four metals (OR Q4 vs. Q1: 1.33, 95% CI: 1.01–1.75 for barium (Ba); OR Q4 vs. Q1: 1.50, 95% CI: 1.16–1.94 for cadmium (Cd); OR Q4 vs. Q1: 1.52, 95% CI: 1.15–2.01 for mercury (Hg); OR Q4 vs. Q1: 1.35, 95% CI: 1.06–1.73 for lead (Pb)) were positively correlated with the elevated risk of HRC after adjusting for covariates. In addition, all three mixed models, including WQS (OR: 1.25; 95% CI: 1.07–1.46), qgcomp (OR: 1.17; 95% CI: 1.03–1.34), and BKMR, consistently showed a significant positive correlation between co-exposure to heavy metal mixtures and HRC, with Ba and Cd being the main contributors within the mixture. These associations were more pronounced in younger adults (20 to 59 years), males, and those with a higher body mass index status (≥25 kg/m2). Our findings reveal a significant relationship between exposure to the mixture of heavy metals and HRC among US adults, with Ba and Cd being the major contributors to the mixture’s overall effect. Public health efforts aimed at reducing heavy metal exposure can help prevent HRC and, in turn, cardiovascular disease.

Associations between urinary heavy metals and anxiety among adults in the National Health and Nutrition Examination Survey (NHANES), 2007–2012

The association of mixed multi-metal exposure with sleep duration and self-reported sleep disorder: A subgroup analysis from the National Health and Nutrition Examination Survey (NHANES)

BackgroundVolatile organic compounds (VOCs) are ubiquitous environmental pollutants which have been suggested to have adverse effects on human health. While the influence of environmental pollutant exposures on periodontitis has attracted elevating attention in recent years, the epidemiological evidence on the association between VOCs exposure and periodontitis was scarce. This study aimed to investigate the potential mediating role of systemic inflammation factors in the complex association between VOCs exposure and periodontitis.MethodsUtilizing data from the National Health and Nutrition Examination Survey (NHANES) 2011–2014, we examined the impacts of VOCs exposure on periodontitis. Concentrations of urinary metabolites of VOCs (mVOCs) were measured using electrospray tandem mass spectrometry to evaluate internal VOCs exposure. Multivariable logistic regression, restricted cubic spline regression (RCS), Bayesian kernel machine regression (BKMR) and Quantile g-computation (QGC) models were performed to investigate the impacts of VOCs exposure on periodontitis. Mediation models were applied to assess the mediated effects of systemic inflammation on the association between mixed VOCs exposure and periodontitis. Besides, we analyzed the association between mixed VOCs exposure and periodontitis in stratified age, gender, and smoking status subgroups.Results1,551 participants were ultimately included for further analyses, of whom 45.20% suffering from periodontitis. Multivariable logistic regression and RCS identified positive associations between single urinary mVOCs and periodontitis (P < 0.05). Notably, BKMR and QGC models suggested that mixed VOCs exposure was significantly associated with periodontitis, with 2-Aminothiazoline-4-carboxylic acid (ATCA) contributing the most (conditional posterior inclusion probability = 0.997). Moreover, systemic inflammation markers (leukocyte and lymphocyte counts) were found to partly mediate the association between VOCs exposure and periodontitis (P < 0.05). No interaction effect was identified between mixed VOCs exposure and periodontitis in age, gender and smoking status subgroups (P > 0.05).ConclusionThis study demonstrated a positive association between VOCs exposure and periodontitis, which was potentially mediated by systemic inflammation factors. Further longitudinal researches are demanded to clarify the underlying mechanisms.

BackgroundCardiovascular disease (CVD) is the leading cause of death worldwide. Few studies have investigated the effects of mixed polycyclic aromatic hydrocarbon (PAH) exposure on CVD prevalence. We aimed to evaluate the association between mixed PAHs exposure and CVD and determine the extent to which these links are mediated by inflammatory indices.MethodsWe used National Health and Nutrition Examination Survey (NHANES) data from 2003 to 2016. Adults with a diagnosis of CVD and seven monohydroxylated PAH metabolites (OH-PAHs) in their urine samples were included. Multivariate logistic regression and Bayesian kernel machine regression (BKMR) models were used to estimate the association between single and mixed PAHs exposure and CVD. Mediation analysis was used to evaluate the mediating effect of inflammatory indices on the association between PAHs mixtures and CVD.ResultsHere, 9136 individuals were included and 10.5% had CVD. Multivariate logistic regression analysis with all the OH-PAHs included that 2-hydroxyfluorene was found positively associated with increased odds of CVD. The BKMR analysis revealed that the overall effect of the seven PAH mixtures was positively associated with CVD. The univariate exposure-response function showed that 2-hydroxyfluorene was positively associated with CVD. Moreover, mediation analysis demonstrated that neutrophil-to-lymphocyte ratio and systemic immune inflammation index mediated the association between PAHs and CVD.ConclusionsOur findings highlight the complexity of the association between mixed PAHs exposure and CVD. At the same time, our study provides insight into the potential mechanisms of inflammation as a mediator between exposure to PAH mixtures and CVD.Supplementary informationThe online version contains supplementary material available at https://doi.org/10.1265/ehpm.24-00091.

Association between endocrine disrupting chemicals exposure and diabetic kidney disease in adults: A national cross-sectional NHANES study.

Background: There is limited research on the associations between serum nutritional biomarkers and mortality risk in patients with metabolic syndrome (MetS). Existing studies merely investigated the single-biomarker effect. Thus, this study aimed to investigate the combined effect of nutritional biomarker mixtures and mortality risk using the Bayesian kernel machine regression (BKMR) model in patients with MetS. Methods: We included the MetS patients, defined according to the 2018 Guideline on the Management of Blood Cholesterol from the National Health and Nutrition Examination Survey (NHANES) 2001–2006. A total of 20 serum nutritional biomarkers were measured and evaluated in this study. The Cox proportional hazard model and restricted cubic spline models were used to evaluate the individual linear and non-linear association of 20 nutritional biomarkers with mortality risk. Bayesian kernel machine regression (BKMR) was used to assess the associations between mixture of nutritional biomarkers and mortality risk. Results: A total of 1455 MetS patients had a median age of 50 years (range: 20–85). During a median of 17.1-year follow-up, 453 (24.72%) died: 146 (7.20%) caused by CVD and 87 (5.26%) by cancer. Non-linear and linear analyses indicated that, in total, eight individual biomarkers (α-carotene, β-carotene, bicarbonate, lutein/zeaxanthin, lycopene, potassium, protein, and vitamin A) were significantly associated with all-cause mortality (all p-values < 0.05). Results from BKMR showed an association between the low levels of the mixture of nutritional biomarkers and high risk of all-cause mortality with the estimated effects ranging from 0.04 to 0.14 (referent: medians). α-Carotene (PIP = 0.971) and potassium (PIP = 0.796) were the primary contributors to the combined effect of the biomarker mixture. The nutritional mixture levels were found to be negatively associated with the risk of cardiovascular disease (CVD) mortality and positively associated with the risk of cancer mortality. After it was stratified by nutrients, the mixture of vitamins showed a negative association with all-cause and CVD mortality, whereas the mixture of mineral-related biomarkers was positively associated with all-cause and cancer mortality. Conclusion: Our findings support the evidence that nutritional status was associated with long-term health outcomes in MetS patients. It is necessary for MetS patients to be concerned with certain nutritional status (i.e., vitamins and mineral elements).

This study investigates the combined effects of environmental pollutants (lead, cadmium, total mercury) and behavioral factors (alcohol consumption, smoking) on depressive symptoms in women. Data from the National Health and Nutrition Examination Survey (NHANES) 2017-2018 cycle, specifically exposure levels of heavy metals in blood samples, were used in this study. The analysis of these data included the application of descriptive statistics, linear regression, and Bayesian Kernel Machine Regression (BKMR) to explore associations between environmental exposures, behavioral factors, and depression. The PHQ-9, a well-validated tool that assesses nine items for depressive symptoms, was used to evaluate depression severity over the prior two weeks on a 0-3 scale, with total scores ranging from 0 to 27. Exposure levels of heavy metals were measured in blood samples. BKMR was used to estimate the exposure-response relationship, while posterior inclusion probability (PIP) in BKMR was used to quantify the likelihood that a given exposure was included in the model, reflecting its relative importance in explaining the outcome (depression) within the context of other predictors in the mixture. A descriptive analysis showed mean total levels of lead, cadmium, and total mercury at 1.21 µg/dL, 1.47 µg/L, and 0.80 µg/L, respectively, with a mean PHQ-9 score of 5.94, which corresponds to mild depressive symptoms based on the PHQ-9 scoring. Linear regression indicated positive associations between depression and lead as well as cadmium, while total mercury had a negative association. Alcohol and smoking were also positively associated with depression. These findings were not significant, but limitations in linear regression prompted a BKMR analysis. BKMR posterior inclusion probability (PIP) analysis revealed alcohol and cadmium as significant contributors to depressive symptoms, with cadmium (PIP = 0.447) and alcohol (PIP = 0.565) showing notable effects. Univariate and bivariate analyses revealed lead and total mercury's strong relationship with depression, with cadmium showing a complex pattern in the bivariate analysis. A cumulative exposure analysis of all metals and behavioral factors concurrently demonstrated that higher quantile levels of combined exposures were associated with an increased risk of depression. Finally, a single variable-effects analysis in BKMR revealed lead, cadmium, and alcohol had a stronger impact on depression. Overall, the study findings suggest that from exposure to lead, cadmium, mercury, alcohol, and smoking, cadmium and alcohol consumption emerge as key contributors to depressive symptoms. These results highlight the need to address both environmental and lifestyle choices in efforts to mitigate depression.

The causes of visual impairment are complex and may be influenced by exposure to environmental pollutants. Using data from the 2003–2004 National Health and Nutrition Examination Survey (NHANES), we examined the association between exposure to ten polycyclic aromatic hydrocarbons (PAHs) and vision problems in 1149 U.S. adults. We employed various supervised learning methods, including variable selection techniques such as Lasso and elastic net, weighted quantile sum regression (WQS), and Bayesian kernel machine regression (BKMR), to assess the association between PAHs and the occurrence of visual impairments. The mediation effects between urinary 2-fluorene and inflammation were evaluated using mediation analysis. Both the lasso and elastic net models consistently identified two specific PAH congeners, 2-fluorene and 1-phenanthrene, as significant predictors. The WQS regression revealed a positive relationship between the PAH mixture and visual impairment, with notable contributions from urinary 2-fluorene (weight = 0.39) and 9-fluorene (weight = 0.21). BKMR analysis indicated that the likelihood of visual impairment increases with higher PAH exposure, showing a general upward trend. This trend also revealed a positive association between visual impairment and exposure to four specific PAH metabolites, including 2-fluorene. A significant mediation effect was observed for alkaline phosphatase (p = 0.03), with a proportion mediated of 10.48%. Our findings suggest a significant association between PAHs and visual impairment, with multiple statistical models consistently emphasizing the crucial role of 2-fluorene exposure. This study highlights the importance of considering environmental pollutants as significant contributors to visual health outcomes, providing insights for preventing visual impairment.