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Background: The global burden of chronic diseases has been increasing, with evidence suggesting that diet and exposure to environmental pollutants, such as per- and polyfluoroalkyl substances (PFAS) and heavy metals, may contribute to their development. The Dietary Inflammatory Index (DII) assesses the inflammatory potential of an individual's diet. However, the complex interplay between PFAS, heavy metals, and DII remains largely unexplored. Objective: The goal of this cross-sectional study was to investigate the associations between diet operationalized as the DII with individual and combined lead, cadmium, mercury, perfluorooctanoic acid (PFOA), and perfluorooctanesulfonic acid (PFOS) exposures using data from the National Health and Nutrition Examination Survey (NHANES) 2017-2018. Methods: Descriptive statistics, a correlational analysis, and linear regression were initially used to assess the relationship between the variables of interest. We subsequently employed Bayesian kernel Machine regression (BKMR) to analyze the data to assess the non-linear, non-additive, exposure-response relationships and interactions between PFAS and metals with the DII. Results: The multi-variable linear regression revealed significant associations between the DII and cadmium and mercury. Our BKMR analysis revealed a complex relationship between PFAS, metal exposures, and the DII. In our univariate exposure-response function plot, cadmium and mercury exhibited a positive and negative linear relationship, respectively, which indicated a positive and negative relationship across the spectrum of exposures with the DII. In addition, the bivariate exposure-response function between two exposures in a mixture revealed that cadmium had a robust positive relationship with the DII for different quantiles of lead, mercury, PFOA, and PFOS, indicating that increasing levels of cadmium are associated with the DII. Mercury's bivariate plot demonstrated a negative relationship across all quantiles for all pollutants. Furthermore, the posterior inclusion probability (PIP) results highlighted the consistent importance of cadmium and mercury with the inflammatory potential of an individual's diet, operationalized as the DII in our study, with both showing a PIP of 1.000. This was followed by PFOS with a PIP of 0.8524, PFOA at 0.5924, and lead, which had the lowest impact among the five environmental pollutants, with a PIP of 0.5596. Conclusion: Our study suggests that exposures to environmental metals and PFAS, particularly mercury and cadmium, are associated with DII. These findings also provide evidence of the intricate relationships between PFAS, heavy metals, and the DII. The findings underscore the importance of considering the cumulative effects of multi-pollutant exposures. Future research should focus on elucidating the mechanistic pathways and dose-response relationships underlying these associations in a study that examines causality, which will enable a deeper understanding of the dietary risks associated with environmental pollutants.
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The combined effects of lead exposure and the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and how they cause cardiovascular dysfunction are examined in this viewpoint manuscript. Lead was picked as a representative environmental contaminant because it has been studied extensively for more than 40 years, while SARS-CoV-2 illustrates the unpredictability of a new infectious agent that can quickly increase the environmental burden on communities. Given that this interaction represents a plausible combined exposure for many people, it is crucial to discuss how it might happen at a mechanistic level. SARS-CoV-2 causes the coronavirus disease 2019 (COVID-19), which can spread by contact and respiratory droplets. One may be exposed to lead and SARS-CoV-2 simultaneously depending on their living situation. Uncertainty exists regarding the consequences of this exposure on cardiovascular disease and its underlying processes. This paper aims to investigate these mechanisms and provide potential causes behind them. The interaction of lead with SARS-CoV-2 and its effects on the cardiovascular system are likely caused by direct damage, the promotion of reactive oxygen species (ROS) production, oxidative stress, and inflammation. In particular, the stimulation of nuclear factor kappa B (NF-B), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF) were all identified as potentially important pathways. Blood clotting, cytokine storm cycle development, and increased hypoxia may also be the results of this. In summary, the effects on the immune system, coagulation, the renin-angiotensin-aldosterone system, and cardiac contractility were the four primary areas identified.
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This exploratory narrative review paper delves into the intricate interplay between per- and polyfluoroalkyl substances (PFAS) exposure, sociodemographic factors, and the influence of stressors in the context of endometrial cancer. PFAS, ubiquitous environmental contaminants notorious for their persistence in the ecosystem, have garnered attention for their potential to disrupt endocrine systems and provoke immune responses. We comprehensively examine the various sources of PFAS exposure, encompassing household items, water, air, and soil, thus shedding light on the multifaceted routes through which individuals encounter these compounds. Furthermore, we explore the influence of sociodemographic factors, such as income, education, occupation, ethnicity/race, and geographical location and their relationship to endometrial cancer risk. We also investigated the role of stress on PFAS exposure and endometrial cancer risk. The results revealed a significant impact of sociodemographic factors on both PFAS levels and endometrial cancer risk. Stress emerged as a notable contributing factor influencing PFAS exposure and the development of endometrial cancer, further emphasizing the importance of stress management practices for overall well-being. By synthesizing evidence from diverse fields, this review underscores the need for interdisciplinary research and targeted interventions to comprehensively address the complex relationship between PFAS, sociodemographic factors, stressors, and endometrial cancer.
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This study utilizes the National Health and Nutrition Examination Survey (NHANES) 2017-2018 data to explore the relationship between exposure to perfluoroalkyl substances (specifically perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS), metals lead (Pb), mercury (Hg), and cadmium (Cd), allostatic load, and hepatic disease markers, including the fatty liver index a measure of the likelihood of non-alcoholic fatty liver disease, aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), and total bilirubin. The paper identified significant associations and interaction effects by employing descriptive statistics, Spearman's correlation analysis, linear regression, and Bayesian kernel machine regression (BKMR). Descriptive statistics highlight sex-specific differences in contaminant levels. Spearman's analysis underscores strong correlations among metals and per- and polyfluoroalkyl substances (PFAS). Linear regression reveals significant impacts of specific contaminants on AST, ALT, ALP, and bilirubin levels, adjusting for age and alcohol consumption. BKMR results further elucidate the complex, potentially synergistic relationships between these environmental exposures and the likelihood of non-alcoholic fatty liver disease, offering nuanced insights into their combined effects on liver health. The findings emphasize the intricate dynamics of environmental exposures on hepatic function, advocating for targeted public health interventions.
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Liver diseases, including non-alcoholic fatty liver disease (NAFLD), are a growing global health issue. Environmental exposure to toxic metals can harm the liver, increasing the risk of NAFLD. Essential elements are vital for liver health, but imbalances or deficiencies can contribute to the development of NAFLD. Therefore, understanding the interplay between toxic metals and essential elements in liver disease is important. This study aims to assess the individual and combined effects of toxic metals (lead(Pb), cadmium (Cd), mercury (Hg)), and essential elements (manganese and selenium) on the risk of liver disease. Methods: We assessed the individual and combined effects of Pb, Cd, Hg, manganese (Mn), and selenium (Se) on liver disease risk using data from the National Health and Nutrition Examination Survey between 2017 and 2018. We performed descriptive statistics and linear regression analysis and then utilized Bayesian Kernel Machine Regression (BKMR) techniques such as univariate, bivariate, and overall effect analysis. BKMR enabled the assessment of non-linear exposure-response functions and interactions between metals and essential elements. Posterior Inclusion Probabilities (PIPs) were calculated to determine the importance of each metal and essential element in contributing to liver disease. Regarding our study results, the regression analysis of liver injury biomarkers ALT, AST, ALP, GGT, total bilirubin, and the FLI-an indicator of NAFLD-with toxic metals and essential elements, adjusting for covariates such as age, sex, BMI, alcohol consumption, ethnicity, income, and smoking status, demonstrated the differential effects of these contaminants on the markers of interest. Our BKMR analysis provided further insights. For instance, the PIP results underscored Pb's consistent importance in contributing to liver disease (PIP = 1.000), followed by Hg (PIP = 0.9512), Cd (PIP = 0.5796), Se (PIP = 0.5572), and Mn (PIP = 0.4248). Our univariate analysis showed a positive trend with Pb, while other exposures were relatively flat. Our analysis of the single-variable effects of toxic metals and essential elements on NAFLD also revealed that Pb significantly affected the risk of NAFLD. Our bivariate analysis found a positive (toxic) trend when Pb was combined with other metals and essential elements. For the overall exposure effect of exposure to all the contaminants together, the estimated risk of NAFLD showed a steady increase from the 60th to the 75th percentile. In conclusion, our study indicates that Pb exposure, when combined with other toxic metals and essential elements, plays a significant role in bringing about adverse liver disease outcomes.
Subject(s)
Nutrition Surveys , Humans , Female , Male , Adult , Middle Aged , Liver Diseases/epidemiology , Liver Diseases/etiology , Environmental Exposure/adverse effects , Environmental Pollutants/toxicity , Metals, Heavy/toxicity , Selenium , Cadmium/toxicity , Non-alcoholic Fatty Liver Disease/chemically induced , Non-alcoholic Fatty Liver Disease/epidemiology , Aged , Young Adult , Trace Elements , Mercury/toxicity , Bayes Theorem , Manganese/toxicity , Lead/toxicity , United States/epidemiologyABSTRACT
Background: Exposure to environmental pollutants such as metals and Per- and Polyfluoroalkyl Substances (PFAS) has become common and increasingly associated with a decrease in the estimated Glomerular Filtration Rate (eGFR), which is a marker often used to measure chronic kidney disease (CKD). However, there are limited studies involving the use of both eGFR and the urine albumin creatinine ratio (uACR), which are more comprehensive markers to determine the presence of CKD and the complexity of pollutant exposures and response interactions, especially for combined metals and PFAS, which has not been comprehensively elucidated. Objective: This study aims to assess the individual and combined effects of perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), Cadmium (Cd), Mercury (Hg), and Lead (Pb) exposure on CKD using data from the National Health and Nutritional Examination Survey (NHANES) 2017-2018. Methods: We employed the use of bivariate logistic regression and Bayesian Kernel Machine Regression (BKMR) in our analysis of the data. Results: Logistic regression results revealed a positive association between PFOA and CKD. Our BKMR analysis revealed a non-linear and bi-phasic relationship between the metal exposures and CKD. In our univariate exposure-response function plot, Cd and Hg exhibited a U and N-shaped interaction, which indicated a non-linear and non-additive relationship with both low and high exposures associated with CKD. In addition, the bivariate exposure-response function between two exposures in a mixture revealed that Cd had a U-shaped relationship with CKD at different quantiles of Pb, Hg, PFOA, and PFOS, indicating that both low and high levels of Cd is associated with CKD, implying a non-linear and complex biological interaction. Hg's interaction plot demonstrated a N-shaped association across all quantiles of Cd, with the 75th quantile of Pb and the 50th and 75th quantiles of PFOA and PFOS. Furthermore, the PIP results underscored Cd's consistent association with CKD (PIP = 1.000) followed by Hg's (PIP = 0.9984), then PFOA and PFOS with a closely related PIP of 0.7880 and 0.7604, respectively, and finally Pb (PIP = 0.6940), contributing the least among the five environmental pollutants on CKD, though significant. Conclusions: Our findings revealed that exposure to environmental pollutants, particularly Hg and Cd, are associated with CKD. These findings highlight the need for public health interventions and strategies to mitigate the cumulative effect of PFAS and metal exposure and elucidate the significance of utilizing advanced statistical methods and tools to understand the impact of environmental pollutants on human health. Further research is needed to understand the mechanistic pathways of PFAS and metal-induced kidney injury and CKD, and longitudinal studies are required to ascertain the long-term impact of these environmental exposures.
Subject(s)
Alkanesulfonic Acids , Cadmium , Caprylates , Environmental Exposure , Environmental Pollutants , Fluorocarbons , Lead , Renal Insufficiency, Chronic , Renal Insufficiency, Chronic/chemically induced , Renal Insufficiency, Chronic/epidemiology , Renal Insufficiency, Chronic/urine , Humans , Fluorocarbons/toxicity , Fluorocarbons/urine , Fluorocarbons/adverse effects , Environmental Pollutants/urine , Environmental Pollutants/toxicity , Female , Alkanesulfonic Acids/urine , Alkanesulfonic Acids/toxicity , Caprylates/toxicity , Caprylates/urine , Caprylates/adverse effects , Male , Cadmium/urine , Cadmium/toxicity , Middle Aged , Adult , Lead/urine , Lead/toxicity , Environmental Exposure/adverse effects , Nutrition Surveys , Mercury/urine , Mercury/toxicity , Aged , Bayes Theorem , Glomerular Filtration Rate/drug effectsABSTRACT
Extensive research has highlighted the strong association between chronic stress and negative health outcomes. This relationship is influenced by various factors, including sociobehavioral, environmental, and genetic and epigenomic forces. To comprehensively assess an individual's stress levels, we propose the development of the Chronic Stress Indicator (CSI), a novel comprehensive multifaceted tool that incorporates key biological, anthropometric, behavioral, and socioeconomic factors. The objective of this study is to assess the effectiveness of the CSI compared to Allostatic Load (AL), a type of chronic stress, in identifying health issues related to stress. The objective of this research is to evaluate the performance of the Chronic Stress Indicator (CSI) versus Allostatic Load (AL) in detecting adverse health outcomes within the U.S. demographic aged 20-49. The information used for this study was sourced from the National Health and Nutrition Examination Survey (NHANES), carried out from 2001 to 2004. Logistic regression modeling was employed to calculate odds ratios and confidence intervals. The Wilcoxon rank-sum test was employed to assess differences in means, whereas the chi-square test, accompanied by Cramer's V statistic, was used to examine the association among categorical variables. Additionally, the relationship between continuous variables was analyzed using Pearson's correlation coefficient. Our association tests show that the length of occupation activity and health status were among the strongest associations to CSI risk. Based on our logistic regression models, age and sex were found to be significant factors in determining AL. We also found that age, smoking, and longest occupation activity were significant factors of CSI risk. These findings suggest a need for individuals to limit smoking as it may lead to higher overall stress despite its common use as a coping mechanism for stress. We should also review the level of occupational activity a job has before continuously working on it as this may also lead to higher cumulative stress.
Subject(s)
Smoking , Stress, Psychological , Humans , Nutrition Surveys , Socioeconomic Factors , Smoking/epidemiologyABSTRACT
Background: Heavy metals, pesticides and a host of contaminants found in dust and soil pose a health risk to young children through ingestion. Dust/soil ingestion rates for young children can be estimated using micro-level activity time series (MLATS) as model inputs. MLATS allow for the generation of frequency and duration of children's contact activities, along with sequential contact patterns. Models using MLATS consider contact types, and transfer dynamics to assign mechanisms of contact and appropriate exposure factors for cumulative estimates of ingestion rates. Objective: The objective of this study is to describe field implementation, data needs, advanced field collection, laboratory methodologies, and challenges for integrating into and updating a previously validated physical-stochastic MLATS-based model framework called the Child-Specific Aggregate Cumulative Human Exposure and Dose (CACHED) model. The manuscript focuses on describing the methods implemented in the current study. Methods: This current multidisciplinary study (Dust Ingestion childRen sTudy [DIRT]) was implemented across three US regions: Tucson, Arizona; Miami, Florida and Greensboro, North Carolina. Four hundred and fifty participants were recruited between August 2021 to June 2023 to complete a 4-part household survey, of which 100 also participated in a field study. Discussion: The field study focused on videotaping children's natural play using advanced unattended 360° cameras mounted for participants' tracking and ultimately conversion to MLATS. Additionally, children's hand rinses were collected before and after recording, along with indoor dust and outdoor soil, followed by advanced mass analysis. The gathered data will be used to quantify dust/soil ingestion by region, sociodemographic variables, age groups (from 6 months to 6 years), and other variables for indoor/outdoor settings within an adapted version of the CACHED model framework. Significance: New innovative approaches for the estimation of dust/soil ingestion rates can potentially improve modeling and quantification of children's risks to contaminants from dust exposure.
Subject(s)
Dust , Environmental Exposure , Soil , Humans , Dust/analysis , Child, Preschool , Environmental Exposure/analysis , Female , Male , Infant , Environmental Monitoring/methods , North Carolina , Arizona , Child , Eating , FloridaABSTRACT
This study sought to investigate the impact of exposure to metals and per- and polyfluoroalkyl substances (PFASs) on cardiovascular disease (CVD)-related risk. PFASs, including PFOA, PFOS, PFNA, and PFHxS, as well as metals such as lead (Pb), cadmium (Cd), and mercury (Hg), were analyzed to elucidate their combined effects on CVD risk. METHODS: Utilizing data from the National Health and Nutrition Examination Survey (NHANES) spanning from 2007 to 2014, this investigation explored the effects of PFASs and metals on CVD risk. A spectrum of individual CVD markers, encompassing systolic blood pressure (SBP), diastolic blood pressure (DBP), high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol, and triglycerides, was examined. Additionally, comprehensive CVD risk indices were evaluated, namely the Overall Cardiovascular Biomarkers Index (OCBI), including the Framingham Risk Score and an Overall Cardiovascular Index. Linear regression analysis was employed to probe the relationships between these variables. Furthermore, to assess dose-response relationships between exposure mixtures and CVD while mitigating the influence of multicollinearity and potential interaction effects, Bayesian Kernel Machine Regression (BKMR) was employed. RESULTS: Our findings indicated that exposure to PFAS and metals in combination increased CVD risk, with combinations occurring with lead bringing forth the largest impact among many CVD-related markers. CONCLUSIONS: This study finds that combined exposure to metals and PFASs significantly elevates the likelihood of CVD risk. These results highlight the importance of understanding the complex interplay between multipollutant exposures and their potential implications for cardiovascular health.