Individual and joint association of Life's Essential 8 metrics with pre-sarcopenia among U.S. adults.

BACKGROUND: In recent times, the American Heart Association has updated its approach to evaluating cardiovascular health (CVH) by replacing the previous "Life's Simple 7" with the more demanding "Life's Essential 8" (LE8). However, the impact of enhancing CVH on reducing the risk of pre-sarcopenia and the association of LE8 metrics with pre-sarcopenia remain unexplored. METHODS: LE8 score was calculated among 9857 participants. Multivariable logistic regression was utilized to investigate the associations between LE8 and pre-sarcopenia. Additionally, the weighted quantile sum (WQS) model was employed to determine the combined and individual impact of LE8 metrics on pre-sarcopenia. To assess the indirect effects of peripheral immune responses on the relationships between cardiovascular health and pre-sarcopenia, mediation analyses were performed. RESULTS: In this study, 827 participants had pre-sarcopenia. After accounting for potential confounding factors, the group with excellent cardiovascular health demonstrated an 83% lower risk of pre-sarcopenia compared to the poor cardiovascular health group (OR: 0.17, 95% CI: 0.11-0.27) and a 33% decreased risk of pre-sarcopenia for each 10-point increase in LE8 score (OR: 0.67, 95% CI: 0.62-0.73). Body mass index (BMI) and physical activity (PA) were the critical contributors that decreased the prevalence of pre-sarcopenia in the obese and non-obese populations, respectively. CONCLUSIONS: A negative association was found between LE8 score and pre-sarcopenia prevalence. Body mass index and physical activity are the primary contributors to the obese and non-obese populations, respectively.

Association Between Dietary Flavonoid Intake and Cardiovascular Health in Cancer Survivors: A Cross-Sectional Study.

Purpose: Flavonoids are naturally occurring compounds with diverse health-promoting properties. The purpose of this study was to explore the associations between dietary flavonoid intake and cardiovascular health in cancer survivors. Patients and Methods: We obtained data from the National Health and Nutrition Examination Survey (NHANES) 2007-2008, 2009-2010, and 2017-2018 cycles. Weighted linear regression and restricted cubic spline (RCS) were used to explore the correlation between dietary flavonoid intake and cardiovascular health (Life's Essential 8 (LE8) score) in cancer survivors. Then, weighted quantile sum (WQS) regression and quantile-based g-computation (qgcomp) models were performed to assess the mixed effects of the six flavonoid subclasses and to determine the major flavonoid types. Additionally, the protective effect of high flavonoid intake on cardiovascular health was further evaluated in different subgroups, and mediation analysis was used to explore mediating factors. Results: After adjusting for all covariates, compared to those in the first quartile, participants in the fourth quartile of total flavonoids, anthocyanidins, flavonols, flavanones, and flavones intake exhibited increases in LE8 scores of 3.24% (95% CI: 0.45-6.03, P for trend=0.030), 6.25% (95% CI: 3.14-9.36, P for trend<0.001), 3.01% (95% CI: 1.33-4.69, P for trend= 0.003), 3.23% (95% CI: 0.18-6.27, P for trend=0.030), and 5.01% (95% CI: 2.42-7.61, P for trend<0.001), respectively. Meanwhile, significant non-linear relationships were supported by the RCS models. However, the weighted linear regression and RCS models did not reveal any clear correlations between isoflavone or flavan-3-ol intake and the LE8 score. Regarding mixed effects, anthocyanidin, flavonol, flavanone, and flavone intake were positively related to the LE8 score according to both the WQS and qgcomp models, and anthocyanidin intake was the major contributor. Conclusion: Our study indicated that dietary flavonoid intake is positively associated with cardiovascular health in cancer survivors, among which anthocyanidin intake might provide the most benefit.

Relationship between mixed exposure to phenyl hydroxides, polycyclic aromatic hydrocarbons, and phthalates and the risk of arthritis.

BACKGROUND: To determine the relationship between mixed exposure to three types of endocrine-disrupting chemicals (EDCs), namely phenyl hydroxides, polycyclic aromatic hydrocarbons (PAHs), and phthalates (PAEs), and risk of arthritis. METHODS: Participants were selected from National Health and Nutrition Examination Survey (NHANES). The relationships between the urinary concentrations of phenyl hydroxides, PAHs, and PAEs and the risk of arthritis were analyzed by generalized linear regression model. The mixed exposure to these EDCs and the risk of arthritis was analyzed by weighted quantile sums (WQSs) and Bayesian kernel machine regression (BKMR) model. RESULTS: Our analysis showed that participants with urinary benzophenone-3 and methylparaben concentrations in the highest quartile (Q4) had an increased risk of arthritis compared with those in Q1. For each one-unit increase in the natural logarithm-converted urinary concentrations of 1-hydroxynapthalene and 2-hydroxynapthalene, the risk of arthritis increased by 5% and 8%, respectively. Chemical mixing index coefficients were significantly associated with risk of arthritis in both WQS positive- and negative-constraint models. In the BKMR model, there was a significant positive correlation between mixed exposure and the risk of arthritis. CONCLUSION: Mixed exposure to phenyl hydroxides, PAHs, and PAEs increased the risk of arthritis, with exposure to PAHs being the key factor.

Pollutants-mediated viral hepatitis in different types: assessment of different algorithms and time series models.

The escalating frequency of environmental pollution incidents has raised significant concerns regarding the potential health impacts of pollutant fluctuations. Consequently, a comprehensive study on the role of pollutants in the prevalence of viral hepatitis is indispensable for the advancement of innovative prevention strategies. Monthly incidence rates of viral hepatitis from 2005 to 2020 were sourced from the Chinese Center for Disease Control and Prevention Infectious Disease Surveillance Information System. Pollution data spanning 2014-2020 were obtained from the National Oceanic and Atmospheric Administration (NOAA), encompassing pollutants such as CO, NO2, and O3. Time series analysis models, including seasonal auto-regressive integrated moving average (SARIMA), Holt-Winters model, and Generalized Additive Model (GAM), were employed to explore prediction and synergistic effects related to viral hepatitis. Spearman correlation analysis was utilized to identify pollutants suitable for inclusion in these models. Concurrently, machine learning (ML) algorithms were leveraged to refine the prediction of environmental pollutant levels. Finally, a weighted quantile sum (WQS) regression framework was developed to evaluate the singular and combined impacts of pollutants on viral hepatitis cases across different demographics, age groups, and environmental strata. The incidence of viral hepatitis in Beijing exhibited a declining trend, primarily characterized by HBV and HCV types. In predicting hepatitis prevalence trends, the Holt-Winters additive seasonal model outperformed the SARIMA multiplicative model ((1,1,0) (2,1,0) [12]). In the prediction of environmental pollutants, the SVM model demonstrated superior performance over the GPR model, particularly with Polynomial and Besseldot kernel functions. The combined pollutant risk effect on viral hepatitis was quantified as ßWQS (95% CI) = 0.066 (0.018, 0.114). Among different groups, PM2.5 emerged as the most sensitive risk factor, notably impacting patients with HCV and HEV, as well as individuals aged 35-64. CO predominantly affected HAV patients, showing a risk effect of ßWQS (95% CI) = - 0.0355 (- 0.0695, - 0.0016). Lower levels of PM2.5 and PM10 were associated with heightened risk of viral hepatitis incidence with a lag of five months, whereas elevated levels of PM2.5 (100-120 µg/m3) and CO correlated with increased hepatitis incidence risk with a lag of six months. The Holt-Winters model outperformed the SARIMA model in predicting the incidence of viral hepatitis. Among machine learning algorithms, SVM and GPR models demonstrated superior performance for analyzing pollutant data. Patients infected with HAV and HEV were primarily influenced by PM10 and CO, whereas SO2 and PM2.5 significantly impacted others. Individuals aged 35-64 years appeared particularly susceptible to these pollutants. Mixed pollutant exposures were found to affect the development of viral hepatitis with a notable lag of 5-6 months. These findings underscore the importance of long-term monitoring of pollutants in relation to viral hepatitis incidence.

Sex and obesity influence the relationship between perfluoroalkyl substances and lean body mass: NHANES 2011-2018.

Objective: Polyfluoroalkyl substances (PFAS) are known endocrine disruptors, that have been the subject of limited research regarding their impact on human lean body mass. The aim of this study was to investigate the effects of PFAS exposure on lean body mass. Methods: We performed a cross-sectional data analysis involving 1022 adolescents and 3274 adults from the National Health and Nutrition Examination Survey (NHANES) 2011-2018, whose lean body mass was measured by dual-energy X-ray absorptiometry. The lean mass index (LMI) was calculated as lean body mass dividing by the square of height. The association between PFAS and LMI was examined through a multivariate-adjusted weighted generalized linear model. Moreover, weighted quantile sum (WQS) regression models were employed to futher examine the relationship between the mixture of PFAS and LMI. Results: Regression analyses revealed an inverse correlation between PFAS exposure and LMI after adjusting for potential covariates. Adults with higher serum PFAS concentrations manifested a reduction in whole LMI ( ß  = -0.193, 95 % confidence interval (CI): -0.325 to -0.06). Notably, this correlation was particularly significant in adult females and individuals with obesity, and it was observed across diverse anatomical regions, including lower limbs, right arm, trunk, and whole lean body mass. In adult females, the association between PFAS and whole LMI was statistically significant ( ß  = -0.294, 95 % CI: -0.495 to -0.094), and a similar trend was found in obese individuals ( ß  = -0.512, 95 % CI: -0.762 to -0.261). WQS regression analyses supported the results obtained from weighted linear regression analyses. Conclusions: Our study suggests that exposure to PFAS, whether individually or in combination, is associated with decreased lean body mass in specific body areas, with sex and obesity serving as major influencing factors.

Single and mixed associations of composite antioxidant diet on triglyceride-glucose index.

BACKGROUND: Although the relationship between oxidative stress and insulin resistance (IR) has been established, the associations of the composite dietary antioxidant index (CDAI) and its components with the surrogate index of insulin resistance (IR), triglyceride-glucose index (TyG), is still not clear. METHODS: This study analyzed the cross-sectional data of the National Health and Nutrition Examination Survey (NHANES) from 2003 to 2018. Multivariate linear regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) were used to analyze the associations of the CDAI and its components with the TyG. In addition, subgroup analysis and several sensitivity analyses were conducted. RESULTS: A total of 14,673 participants with complete data were included, with a median age of 50 years and 7,257 women (49%). Multivariate linear regression showed that after full adjustment, the CDAI was significantly negatively associated with the TyG [ß: -0.005, 95% CI: (-0.008, -0.002), p = 0.002]. The model in which six nutrients were mutually corrected showed that vitamin E (per-SD increase) was most strongly associated with the TyG [ß: -0.062, 95% CI: (-0.074, -0.050), p < 0.0001]. In the WQS model, the WQS index of the antioxidant diet was negatively associated with the TyG (ß: -0.060; P < 0.0001). Similar effects were observed in the BKMR analysis. Notably, in the WQS and BKMR models, vitamin E became the most influential component. In addition, in the subgroup analysis, the association between the CDAI and the TyG in overweight or obese and diabetic populations was significantly weaker. CONCLUSION: Antioxidant diets, especially vitamin E, are significantly negatively correlated with TyG. This study emphasizes the important value of supplementing vitamin E to improve IR. However, patients with poor weight management and diabetes seem to benefit less from antioxidant diets.

Associations of the intake of individual and multiple fatty acids with depressive symptoms among adults in NHANES 2007-2018.

BACKGROUND: Previous studies have mainly focused on the effects of individual fatty acids on depressive symptoms, while the combined effect of fatty acids on the risk of depressive symptoms has not yet been extensively reported. This study evaluate the associations between individual and multiple fatty acids with depressive symptoms in U.S. adults. METHODS: Data sets were obtained from the National Health and Nutrition Examination Survey (NHANES) 2007-2018 cycles. Both males and females aged above 18 years with complete information about dietary fatty acids intake, depression symptoms, and covariates were included. Weighted linear regression models were conducted to evaluate the relationships between individual fatty acid intake and depressive symptoms, and restricted cubic spline (RCS) models were utilized to explore the corresponding dose-response relationships. Additionally, we implemented the weighted quantile sum (WQS) regression and quantile g-computation (QGC) models to estimate the mixed effects of 19 fatty acids and identify the predominant types. RESULTS: After multivariable adjustments, an increase of one unit in Linoleic acid (LA), Alpha-Linolenic Acid (ALA), Arachidonic acid (AA), Docosapentaenoic acid(DPA), Docosahexaenoic acid(DHA), was associated with a decrease in depressive scores by -0.021 (95 % CI: -0.039,-0.003, p = 0.021),-0.028 (95 % CI: -0.045,-0.011, p = 0.002),-0.026 (95 % CI: -0.044,-0.008, p = 0.005), -0.026 (95 % CI: -0.042,-0.009, p = 0.003), and - 0.022 (95 % CI: -0.041,-0.003, p = 0.022), respectively. However, a per unit increase in Hexanoic acid and Octanoic acid was associated with an increase in depressive scores of 0.020 (95 % CI: 0.002,0.038, p = 0.029) and 0.026 (95 % CI: 0.004,0.048, p = 0.020), respectively. Meanwhile, significant dose-response relationships were supported by the RCS models. As for the mixed effects, both WQS and QGC models demonstrated that the mixture of polyunsaturated fatty acids (PUFAs) was inversely related to depressive symptoms, and ALA and DPA were the most critical contributors. DHA was negatively correlated with depressive symptoms in WQS analysis, but positively correlated with depressive symptoms in QGC analysis. LIMITATIONS: The cross-sectional design limits our ability to establish causality, and 24-hour dietary recall can lead to potential inaccuracies reflecting participants' true eating habits. CONCLUSION: Our study suggests that the single effects of each PUFA were inversely associated with depressive symptoms, except for octadecatetraenoic acid. Moreover, higher combined intake of dietary PUFAs is inversely associated with depressive symptoms in U.S. adults. Among the mixed effects of PUFAs, ALA and DPA may play predominant roles. However, DHA mixed with other fatty acids may have different effects on depressive symptoms, and further study is needed.

Associations between urinary rare Earth elements with renal function: Findings from a cross-sectional study in Guangxi, China.

BACKGROUND: With increased applications of rare earth elements (REEs) across various industries, evaluating the relationship between REEs exposure and potential health effects has become a public concern. In vivo experiments have established that REEs impact renal function. However, relevant epidemiological evidence on this relationship remains scarce. The objective of this study is to examine the impact of exposure to REEs on renal function. METHODS: In this cross-sectional study, 1052 participants were recruited from Guangxi, China. We measured urinary concentrations of 12 REEs using an inductively coupled plasma-mass spectrometer (ICP-MS). Multiple linear regression models were developed to explore the relationship between a single REEs exposure and the estimated glomerular filtration rate (eGFR), a marker of renal function. Weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were used to examine the combined effects of REE co-exposure on eGFR. RESULTS: In the multiple linear regression analysis, increasing the concentrations of lanthanum (La, ß: 8.22, 95% CI: 5.67-10.77), cerium (Ce, ß:6.61, 95% CI: 3.80-9.43), praseodymium (Pr, ß: 8.46, 95% CI: 5.85-11.07), neodymium (Nd, ß:8.75, 95% CI: 6.10-11.41), and dysprosium (Dy, ß:7.38, 95% CI: 4.85-9.91) significantly increased the eGFR. In the WQS regression model, the WQS index was significantly associated with eGFR (ß: 4.03, 95% CI: 2.46-5.60), with Pr having the strongest correlation with eGFR. Similar results were obtained in the BKMR model. Additionally, interactions between Pr and La, and Pr and Nd were observed. CONCLUSIONS: Co-exposure to REEs is positively associated with elevated eGFR. Pr is likely to have the most significant influence on increased eGFRs and this might be exacerbated when interacting with La and Nd. Mixed exposure to low doses of REEs had a protective effect on renal function, which can provide some evidence for the exposure threshold of REEs in the environment. TRIAL REGISTRATION: The study has been approved by the Guangxi Medical University Medical Ethics Committee (#20170206-1), and all participants provided written informed consent.

Association between brominated flame retardants (PBDEs and PBB153) exposure and hypertension in U.S. adults: results from NHANES 2005-2016.

BACKGROUND: Brominated Flame Retardants (BFRs) have attracted widespread concern due to their environmental persistence and potential toxicity. This study aims to examine the association between BFRs exposure and hypertension. METHODS: We used data from the National Health and Nutrition Examination Survey (NHANES) spanning 2005 to 2016 for the cross-sectional analysis. To evaluate the individual and combined impacts of BFRs exposure on hypertension, we utilized multivariate models, including generalized additive models, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) models. RESULTS: 9882 individuals (48% male) aged ≥ 20 were included in the final analysis, of whom 4114 had hypertension. After controlling for potential covariates, higher serum concentrations of PBDE100 (OR: 1.26; 95% CI: 1.01, 1.57) and PBDE153 (OR: 1.50; 95% CI: 1.18, 1.88) were significantly associated with hypertension. A nonlinear relationship between PBDE28 and hypertension was observed (P = 0.03). Moreover, BFRs mixture were positively associated with the prevalence of hypertension in both the WQS (ß:1.09; 95% CI: 1.02, 1.17; P = 0.02) and BKMR models. CONCLUSION: Our study suggested that BFRs exposure is positively associated with hypertension in the general population. To confirm this association and elucidate the mechanisms, further research is required.

Association of Life's Essential 8 with metabolic dysfunction-associated steatotic liver disease (MASLD), a cross-sectional study from the NHANES 2003-2018.

There is limited research on the relationship between Life's Essential 8 (LE8) score and metabolic dysfunction-associated steatotic liver disease (MASLD). Our aim is to investigate the relationship between overall lifestyle assessed by LE-8 score and MASLD in a nationally representative sample. We employed the LE8 score to comprehensively evaluate cardiovascular health, the assessment of MASLD primarily utilized the Fatty Liver Index. The weighted logistic regression models, restrictive cubic splines (RCS), subgroup analyses and the weighted quantile sum (WQS) regression were used to evaluate the relationship between the cardiovascular health and MASLD. Logistic regression models revealed that higher LE8 scores were associated with lower odds of having MASLD. The RCS revealed a significant nonlinear dose-response relationship between LE8 scores and MASLD. The WQS regression model indicated that blood glucose contributed the most to the risk of MASLD. The subgroup analysis indicates that there are significant differences in this association across age, educational level, and poverty income ratio. Our study suggests that an inverse correlation between LE8 and the risk of MASLD. Our findings underscore the utility of the LE8 algorithm in MASLD risk assessment and provide support for MASLD prevention through the promotion of healthy lifestyles.

Association of volatile organic compound levels with chronic obstructive pulmonary diseases in NHANES 2013-2016.

Volatile organic compounds (VOCs) represent a significant component of air pollution. However, studies evaluating the impact of VOC exposure on chronic obstructive pulmonary disease (COPD) have predominantly focused on single pollutant models. This study aims to comprehensively assess the relationship between multiple VOC exposures and COPD. A large cross-sectional study was conducted on 4983 participants from the National Health and Nutrition Examination Survey. Four models, including weighted logistic regression, restricted cubic splines (RCS), weighted quantile sum regression (WQS), and the dual-pollution model, were used to explore the association between blood VOC levels and the prevalence of COPD in the U.S. general population. Additionally, six machine learning algorithms were employed to develop a predictive model for COPD risk, with the model's predictive capacity assessed using the area under the curve (AUC) indices. Elevated blood concentrations of benzene, toluene, ortho-xylene, and para-xylene were significantly associated with the incidence of COPD. RCS analysis further revealed a non-linear and non-monotonic relationship between blood levels of toluene and m-p-xylene with COPD prevalence. WQS regression indicated that different VOCs had varying effects on COPD, with benzene and ortho-xylene having the greatest weights. Among the six models, the Extreme Gradient Boosting (XGBoost) model demonstrated the strongest predictive power, with an AUC value of 0.781. Increased blood concentrations of benzene and toluene are significantly correlated with a higher prevalence of COPD in the U.S. population, demonstrating a non-linear relationship. Exposure to environmental VOCs may represent a new risk factor in the etiology of COPD.

Associations of exposure to volatile organic compounds with sleep health and potential mediators: analysis of NHANES data.

Objective: The effect of environmental pollution on sleep has been widely studied, yet the relationship between exposure to volatile organic compounds (VOCs) and sleep health requires further exploration. We aimed to investigate the single and mixed effect of urinary VOC metabolites on sleep health and identify potential mediators. Methods: Data for this cross-sectional study was collected from the National Health and Nutrition Examination Surveys (NHANES) (2005-2006, 2011-2014). A weighted multivariate logistic regression was established to explore the associations of 16 VOCs with four sleep outcomes. Following the selection of important VOCs through the least absolute shrinkage and selection operator (LASSO) regression, principal component analyses (PCA), weight quantile sum (WQS), and Bayesian kernel machine regression (BKMR) analyses were conducted to explore the associations between exposure to single and mixed VOCs and sleep outcomes, as well as identify the most contributing components. A mediation analysis was performed to explore the potential effect of depression scores. Results: Of the 3,473 participants included in the study, a total of 618 were diagnosed with poor sleep patterns. In logistic regression analyses, 7, 10, 1, and 5 VOCs were significantly positively correlated with poor sleep patterns, abnormal sleep duration, trouble sleeping, and sleep disorders, respectively. The PCA analysis showed that PC1 was substantially linked to a higher risk of poor sleep patterns and its components. The WQS model revealed a positive association between VOC mixture of increased concentrations and poor sleep patterns [OR (95% CI): 1.285 (1.107, 1.493)], abnormal sleep duration [OR (95% CI): 1.154 (1.030, 1.295)], trouble sleeping [OR (95% CI): 1.236 (1.090, 1.403)] and sleep disorders [OR (95% CI): 1.378 (1.118, 1.705)]. The BKMR model found positive associations of the overall VOC exposure with poor sleep patterns, trouble sleeping, and sleep disorders. PCA, WQS, and BKMR models all confirmed the significant role of N-acetyl-S-(N-methylcarbamoyl)-l-cysteine (AMCC) in poor sleep patterns and its components. The depression score was a mediator between the positive VOC mixture index and the four sleep outcomes. Conclusion: Exposure to single and mixed VOCs negatively affected the sleep health of American population, with AMCC playing a significant role. The depression score was shown to mediate the associations of VOC mixtures with poor sleep patterns and its components.

Associations between exposure to pesticides mixture and semen quality among the non-occupationally exposed males: Four statistical models.

Most epidemiological studies on the associations between pesticides exposure and semen quality have been based on a single pesticide, with inconsistent major results. In contrast, there was limited human evidence on the potential effect of pesticides mixture on semen quality. Our study aimed to investigate the relationship of pesticide profiles with semen quality parameters among 299 non-occupationally exposed males aged 25-50 without any clinical abnormalities. Serum concentrations of 21 pesticides were quantified by gas chromatography-tandem mass spectrometry (GC-MS/MS). Semen quality parameters were abstracted from medical records. Generalized linear regression models (GLMs) and three mixture approaches, including weighted quantile sum regression (WQS), elastic net regression (ENR) and Bayesian kernel machine regression (BKMR), were applied to explore the single and mixed effects of pesticide exposure on semen quality. In GLMs, as the serum levels of Bendiocarb, ß-BHC, Clomazone, Dicrotophos, Dimethenamid, Paclobutrazole, Pentachloroaniline and Pyrimethanil increased, the straight-line velocity (VSL), linearity (LIN) and straightness (STR) decreased. This negative association also occurred between the concentration of ß-BHC, Pentachloroaniline, Pyrimethanil and progressive motility, total motility. In the WQS models, pesticides mixture was negatively associated with total motility and several sperm motility parameters (ß: -3.07∼-1.02 per decile, FDR-P<0.05). After screening the important pesticides derived from the mixture by ENR model, the BKMR models showed that the decreased qualities for VSL, LIN, and STR were also observed when pesticide mixtures were at ≥ 70th percentiles. Clomazone, Dimethenamid, and Pyrimethanil (Posterior inclusion probability, PIP: 0.2850-0.8900) were identified as relatively important contributors. The study provides evidence that exposure to single or mixed pesticide was associated with impaired semen quality.

Associations of mixed metal exposure with chronic kidney disease from NHANES 2011-2018.

Metals have been proved to be one of risk factors for chronic kidney disease (CKD) and diabetes, but the effect of mixed metal co-exposure and potential interaction between metals are still unclear. We assessed the urine and whole blood levels of cadmium (Cd), manganese (Mn), lead (Pb), mercury (Hg), and renal function in 3080 adults from National Health and Nutrition Survey (NHANES) (2011-2018) to explore the effect of mixed metal exposure on CKD especially in people with type 2 diabetes mellitus (T2DM). Weighted quantile sum regression model and Bayesian Kernel Machine Regression model were used to evaluate the overall exposure impact of metal mixture and potential interaction between metals. The results showed that the exposure to mixed metals was significantly associated with an increased risk of CKD in blood glucose stratification, with the risk of CKD being 1.58 (1.26,1.99) times in urine and 1.67 (1.19,2.34) times in whole blood higher in individuals exposed to high concentrations of the metal mixture compared to those exposed to low concentrations. The effect of urine metal mixture was elevated magnitude in stratified analysis. There were interactions between urine Pb and Cd, Pb and Mn, Pb and Hg, Cd and Mn, Cd and Hg, and blood Pb and Hg, Mn and Cd, Mn and Pb, Mn and Hg on the risk of CKD in patients with T2DM and no significant interaction between metals was observed in non-diabetics. In summary, mixed metal exposure increased the risk of CKD in patients with T2DM, and there were complex interactions between metals. More in-depth studies are needed to explore the mechanism and demonstrate the causal relationship.

Association between concentrations of rare earth elements in chorionic villus and risk for unexplained spontaneous abortion.

Rare earth elements (REEs) exposure during pregnancy may increase the risk of unexplained spontaneous abortion. However, the association between REEs intrauterine exposure and unexplained spontaneous abortion had yet to be studied. In order to conduct this large case-control study, we thus collected chorionic villus from 641 unexplained spontaneous abortion and 299 control pregnant women and detected the concentrations of 15 REEs by inductively coupled plasma mass spectrometer (ICP-MS). Because the detection rates of 10 REEs were less than 80%, the remaining 5 REEs, which were lanthanum (La), cerium (Ce), praseodymium (Pr), neodymium (Nd) and yttrium (Y), underwent to further analysis. The association between 5 REEs and unexplained spontaneous abortion was assessed by using the logistic regression, bayesian kernel regression (BKMR) and weighted quantile sum regression (WQS) models. In the adjusted logistic regression model, Pr, Nd and Y enhanced the incidence of unexplained spontaneous abortion in a dose-dependent way and Ce increased the risk only at high concentration group. The result of BKMR model demonstrated that the risk of unexplained spontaneous abortion increased as the percentile of five mixed REEs increased. Y and Nd were both significantly associated with an increased incidence of unexplained spontaneous abortion, but La was correlated with a decrease in the risk of unexplained spontaneous abortion. Pr was substantially associated with an increase in the risk of unexplained spontaneous abortion when other REEs concentrations were fixed at the 25th and 50th percentiles. According to WQS regression analysis, the WQS index was significantly associated with unexplained spontaneous abortion (OR = 3.75, 95% CI:2.40-5.86). Y had the highest weight, followed by Nd and Pr, which was consistent with the analysis results of our other two models. In short, intrauterine exposure to REEs was associated with an increased risk of unexplained spontaneous abortion, with Y, Nd and Pr perhaps playing an essential role.

The associations between dietary flavonoids intake and risk of depressive symptom in diabetic patients: Data from NHANES 2007-2008, 2009-2010, and 2017-2018.

BACKGROUND: The increasing incidence of depressive symptoms in diabetic patients contributes to the global burden of disease, but few epidemiological studies have evaluated the relationship between dietary flavonoids intake and depressive symptoms in diabetic patients in American adults. OBJECTIVE: This study intended to evaluate the associations of dietary flavonoids intake and depressive symptoms in diabetic patients in American adults. METHODS: We conducted a cross-sectional analysis of 1993 adults aged ≥20 years old who participated in the 2007-2008, 2009-2010, and 2017-2018 National Health and Nutrition Examination Surveys (NHANES). Chi-square test and independent-sample t-test were used to compare subjects' characteristics. Logistic regression model was further used to analyze the relationship between dietary flavonoid intake and depressive symptoms in diabetic patients. Restricted cubic spline (RCS) analysis was used to investigate the non-linear relationship between dietary flavonoid intake and the prevalence of depressive symptoms in diabetic patients. The weighted quartile sum (WQS) regression was used to analyze the effect of 29 flavonoids monomers. RESULTS: The results showed that the total flavonoid intake in the third quartile (OR, 0.635; 95 % CI,0.419-0.962; P, 0.032) was significantly associated with a reduced risk of depressive symptoms in diabetic patients compared with the lowest quartile. And there was a U-shaped association between dietary flavonoid intake and risk of depressive symptoms in diabetic patients. Top contributors of flavonoid monomers were eriodictyol, naringenin, and theaflavin-3'-gallate, accounting for a percentage of 30.83 %, 22.17 %, and 6.92 %, respectively. CONCLUSION: Moderate (56.07-207.12 mg/day) dietary flavonoid intake was associated with a reduced risk of depressive symptoms in diabetic patients. The important flavonoid monomers were eriodictyol, naringenin, and theaflavin-3'-gallate.

A multi-environmental source approach to explore associations between metals exposure and olfactory identification among school-age children residing in northern Italy.

BACKGROUND: Metal exposures can adversely impact olfactory function. Few studies have examined this association in children. Further, metal exposure occurs as a mixture, yet previous studies of metal-associated olfactory dysfunction only examined individual metals. Preventing olfactory dysfunctions can improve quality of life and prevent neurodegenerative diseases with long-term health implications. OBJECTIVE: We aimed to test the association between exposure to a mixture of 12 metals measured in environmental sources and olfactory function among children and adolescents residing in the industrialized province of Brescia, Italy. METHODS: We enrolled 130 children between 6 and 13 years old (51.5% females) and used the "Sniffin' Sticks" test to measure olfactory performance in identifying smells. We used a portable X-ray fluorescence instrument to determine concentrations of metals (arsenic (As), calcium, cadmium (Cd), chromium, copper, iron, manganese, lead (Pb), antimony, titanium, vanadium and zinc) in outdoor and indoor deposited dust and soil samples collected from participants' households. We used an extension of weighted quantile sum (WQS) regression to test the association between exposure to metal mixtures in multiple environmental media and olfactory function adjusting for age, sex, socio-economic status, intelligence quotient and parents' smoking status. RESULTS: A higher multi-source mixture was significantly associated with a reduced Sniffin' Sticks identification score (ß = -0.228; 95% CI -0.433, -0.020). Indoor dust concentrations of Pb, Cd and As provided the strongest contributions to this association (13.8%, 13.3% and 10.1%, respectively). The metal mixture in indoor dust contributed more (for 8 metals out of 12) to the association between metals and olfactory function compared to soil or outdoor dust. IMPACT STATEMENT: Among a mixture of 12 metals measured in three different environmental sources (soil, outdoor and indoor dust), we identified Pb, Cd and As measured in indoor dust as the main contributors to reduced olfactory function in children and adolescents residing in an industrialized area. Exposure to indoor pollution can be effectively reduced through individual and public health interventions allowing to prevent the deterioration of olfactory functions. Moreover, the identification of the factors that can deteriorate olfactory functions can be a helpful instrument to improve quality of life and prevent neurodegenerative diseases as long-term health implications.

Associations between prenatal metal and metalloid mixtures in teeth and reductions in childhood lung function.

BACKGROUND: Metal(oid)s have been cross-sectionally associated with lung function outcomes in childhood but there is limited data on their combined effects starting in utero. Child sex may further modify these effects. OBJECTIVE: Examine associations between in utero and early life exposure to metals assessed via novel dentine biomarkers and childhood lung function and explore effect modification by child sex. METHODS: Analyses included 291 children enrolled in the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) study, a longitudinal birth cohort study in Mexico City. Weekly dentine levels of arsenic (As), cadmium (Cd), cobalt (Co), copper (Cu), manganese (Mn), nickel (Ni), and lead (Pb) were measured from 15 weeks pre-birth to 15 weeks post birth in deciduous children's teeth. Lung function was tested at ages 8-14 years and then modeled as age, height and sex adjusted z-scores. Associations were modeled using lagged weighted quantile sum (LWQS) regression to evaluate the potential for a time-varying mixture effect adjusting for maternal age and education at enrollment and exposure to environmental tobacco smoke in pregnancy. Models were also stratified by sex. RESULTS: We identified a window of susceptibility at 12-15 weeks pre-birth in which the metal mixture was associated with lower FVC z-scores in children aged 8-14 years. Cd and Mn were the largest contributors to the mixture effect (70 %). There was also some evidence of effect modification by sex, in which the mean weights and weighted correlations over the identified window was more evident in males when compared to females. In the male stratum, Cd, Mn and additionally Pb also dominated the mixture association. CONCLUSIONS: Prenatal metal(oid) exposure was associated with lower lung function in childhood. These findings underscore the need to consider both mixtures and windows of susceptibility to fully elucidate effects of prenatal metal(oid) exposure on childhood lung function.

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

BACKGROUND: Volatile 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. METHODS: We 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. RESULTS: In 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. CONCLUSIONS: Our 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.

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.