Weighted Quantile Sum Research Articles

Heart failure risk assessment using biomarkers in patients with atrial fibrillation: analysis of 32,041 patients from the COMBINE-AF study

Abstract Introduction Heart failure (HF) is one of the most common comorbidities in patients with AF, resulting in a clinical need for robust risk assessment. Purpose To investigate the incremental value of adding NTproBNP, high-sensitivity cardiac troponin T (hs-cTnT), and growth-differentiation factor-15 (GDF-15) to clinical predictors for HF risk stratification in patients with AF, and the individual contribution of each biomarker accounting for inter-biomarker correlation. Methods We used pooled individual patient data from 3 large RCTs investigating DOACs versus VKAs (ARISTOTLE, ENGAGE AF-TIMI 48, RE-LY) from the COMBINE-AF cohort and included all patients with available biomarkers at baseline. The composite primary endpoint was hospitalization for HF (HHF) or CV death (CVD), with HHF as secondary endpoint. We employed analyses of absolute risk and Cox-regression adjusting for clinical factors to assess the association of the individual biomarkers with both endpoints, testing incremental discrimination with the likelihood ratio test from nested models. To address the inter-biomarker correlation, weighted quantile sum (WQS) regression analysis summarizing the adjusted risk of all biomarkers (per quartile) in one index was applied, thereby exploring the individual and additive contribution of each biomarker to risk assessment. Results Data were available in 32,041 patients (median age 71 [IQR 64-77] years, 36.7% female, 23.0% with paroxysmal AF, 41.6% with established HF). Higher biomarker values were associated with a graded increase in absolute risk for HHF/CVD and HHF (Figure 1). In a model adjusting for clinical variables and all biomarkers, hs-cTnT (HR per 1-SD 1.39 [95% CI 1.33-1.44]), NT-proBNP (HR 1.67 [95% CI 1.58-1.76]), and GDF-15 (HR 1.20 [95% CI 1.15-1.25]) were associated with HHF/CVD. The c-index increased with addition of biomarkers (0.70 [0.69, 0.70] to 0.77 [0.76, 0.78]; Likelihood ratio test p<0.001). Results were similar for HHF alone. NTproBNP was significantly correlated with hs-cTnT (r=0.40, p<0.0001) and GDF-15 (r=0.36, p<0.001). To address this correlation, WQS regression analysis was conducted (Figure 2). NTproBNP and hs-cTnT contributed nearly equally to the risk assessment for HHF/CVD and HHF, with GDF-15 providing statistically significant but less contribution to risk assessment (Figure 2). Conclusion Hs-cTnT, NT-proBNP and GDF-15 contribute individually and additively to the risk assessment for HHF/CVD and HHF in patients with AF. Our analysis suggests that hs-cTnT is as important as NTproBNP for HF risk assessment, with significant but less contribution of GDF-15. Our findings support the possible future routine use of biomarkers to distinguish patients with AF at low or high risk for HF and could guide the introduction of therapies to mitigate the risk of HF events in this growing population.Event incidence by biomarker quartilesWeighted quantil sum regression analysis

A cross-sectional study of the association between blood metal mixtures exposure and hyperuricemia.

To determine the association between blood metal mixture and HUA risk. A cross-sectional study was performed based on the populations from Kailuan cohort trial in China. Inductively coupled plasma mass spectrometry was utilized to detect the blood concentrations of iron (Fe), lead (Pb), calcium (Ca), copper (Cu), magnesium (Mg), zinc (Zn), selenium (Se), and manganese (Mn). Multivariate logistic regression (MLR) models and weighted quantile sum (WQS) regression models were employed to assess the relationships. There were 3706 participants included in this study, and 464 (12.52%) were with HUA. The mean level of uric acid was 485.60μmol/L in the subjects with HUA, which was remarkably increased compared to those without HUA (293.10μmol/L). The multivariate-adjusted odds ratios (95% confidence intervals) of HUA were 2.15 (1.40, 3.29) for Pb, 3.42 (2.24, 5.23) for Fe, 1.61 (1.15, 2.25) for Ca, 3.06 (2.04, 4.59) for Mg, and 1.69 (1.26, 2.28) for Zn by comparing the highest and lowest metal quartiles using the single-metal logistic regression model. Meanwhile, the WQS regression models demonstrated a positive association between metal mixtures and HUA risk, to which, Fe, Mg, Pb, and Zn were the major contributors. Pb, Fe, and Zn were still robust in multiple-metal models. Age, gender, weight, smoking, and drinking status could modify these relationships with significant interactions. Co-exposure to Fe, Pb, Ca, Cu, Zn, Mg, Se, and Mn were related to increased HUA risk in Chinese adults, of with, Pb, Fe, and Zn appeared to have greater impacts. These relationships were more obvious in adults aged < 60years, or women, or overweight, or non-smoking, or drinking with significant interactions. Key Points • Increased Fe, Pb, Mg, Ca, and Zn were related to increased HUA risk in dose-response fashion among Chinese adults. • The metal mixture dominated by Fe, Mg, Pb, and Zn was positively associated with HUA risk. Fe, Pb, and Zn were still robust in MM model. • Such association was stronger showed in adults aged < 60years, or women, or overweight, or non-smoking, or drinking with significant interactions.

Combined short-term exposure to meteorological, pollution factors and pertussis in different groups from Jining, China.

Previous studies have typically explored daily lagged relationships among pertussis and meteorology, with little assessment of effect and interaction among pollutants mixtures. Our researchers collected pertussis cases data from 2017-2022 as well as meteorological and contaminative factors for the Jining region. First, we reported the application of the Moving Epidemic Method (MEM) to estimate epidemic threshold and intensity level. Then we developed a Weighted Quantile Sum (WQS) regression and Bayesian Kernel Machine Regression (BKMR) model to assess single, multiple effects and interaction of meteorological and pollution factors on pertussis cases for different sex, delayed and epidemic threshold groups. There has been a yearly upward trend in the incidence of pertussis in Jining regions. High prevalence threshold years were in 2018-2019, the epidemic peak was mainly concentrated in 32 weeks. Totally, pertussis infections disease was separately 2.1% (95% confidence Interval (CI) = 1.3, 2.8) and 1.1% (95% CI = 0.3, 1.9) higher per decile increase in temperature and sulphur dioxide (SO2). And pertussis infections disease was 1.1% lower per decile increase in humidity. In the different stratified analyses, air pressure was a strong negative effect in males and in the lagged 11-20 days group, with 7.3 and 14.7%, respectively. Sulphur dioxide had a relatively weak positive effect in males, females and the group after 20 days lag, ranging from 0.5 to 0.6%. The main positive effectors affecting the onset of disease at low and high threshold levels were ozone (O3) and SO2, respectively, while the negative effectors were SO2 and carbon monoxide (CO), respectively. This is the first mathematically based study of seasonal threshold of pertussis in China, which allows accurate estimation of epidemic level. Our findings support that short-term exposure to pollutants is the risk factor for pertussis. We should concentrate on pollutants monitoring and effect modeling.

Biological aging mediates the association between volatile organic compounds and cardiovascular disease

BackgroundEvidence for the relationship between individual and combined volatile organic compounds (VOCs) and cardiovascular disease (CVD) is limited. Besides, the mediating role of biological aging (BA) has not been studied. Therefore, this study aimed to examine the association between VOCs and CVD risk and to explore the mediating effects of BA.MethodsLogistic regression models were used to investigate the relationships of metabolites of volatile organic compounds (mVOCs) and BA with CVD. In addition, weighted quantile sum (WQS) regression, adaptive elastic networks, and Environmental Risk Score (AENET-ERS) were utilized to assess overall associations of mixed VOCs co-exposure with CVD. Mediation analyses were used to identify potential mediating effects of BA.ResultsIn the single-pollutant model, CYMA was shown to be associated with an increased risk of CVD. Additionally, we identified significantly positive associations between the WQS index and CVD (odds ratio (OR) = 1.292, 95% confidence interval (CI): 1.006, 1.660), and DHBMA had the greatest contribution for CVD (0.246). Furthermore, the AENET-ERS results showed that 8 mVOCs were significantly associated with CVD, and ERS was related to an elevated risk of CVD (OR = 1.538, 95%CI: 1.255, 1.884). Three BA indicators mediated the association of the mVOCs mixture with CVD, with mediating effect proportions of 11.32%, 34.34%, and 7.92%, respectively.ConclusionThe risk of CVD was found to increase with both individual and combined exposure to VOCs. BA mediates the positive effects of VOCs on CVD, suggesting that this pathway may be one of the mechanisms of CVD.

The association between brominated flame retardants exposure with Parkinson’s disease in US adults: a cross-sectional study of the National Health and Nutrition Examination Survey 2009–2016

BackgroundIncreasing evidence suggests that environmental factors play a crucial role in the pathogenesis of Parkinson’s disease (PD). Humans are simultaneously exposed to multiple brominated flame retardants (BFRs) in the environment. However, the relationship between BFRs and PD remains unclear. This study was designed to investigate the overall association between BFRs and PD in a nationally representative US population and to further identify significant chemicals.MethodsThis study used data from 7,161 NHANES participants from 2009 through 2016. The serum BFRs registry included PBDE-28, PBDE-47, PBDE-85, PBDE-99, PBDE-100, PBDE-153, PBDE-154, PBDE-183, PBDE-209, and PBB-153. A survey-weighted generalized logistic regression model with restricted cubic splines (RCS) was used to evaluate the association between single BFRs exposure and periodontitis. Meanwhile, weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were used to evaluate the overall association of mixed frankincense powder with periodontitis and to identify significant chemicals. Sensitivity analysis was performed to evaluate the robustness of the results.ResultsAmong the 7,161 participants, 65 had PD. PD patients were older (mean age 57.79 vs. 46.57 years) and had a higher proportion of females (70.86%) compared to non-PD participants. Serum levels of PBB-153 were significantly higher in those with PD. Logistic regression analyses revealed a non-linear, inverted U-shaped relationship between serum PBB-153 and PD risk. The risk of PD increased with higher PBB-153 levels up to the 3rd quartile (Q3), beyond which the risk declined (Q3 vs. Q1: OR = 4.98, 95% CI = 1.79–13.86; Q4 vs. Q1: OR = 3.23, 95% CI = 1.03–10.08). PBB-153 (43.40%), PBDE-153 (24.75%), and PBDE-85 (19.51%) contributed most to the weighted quantile sum index associated with PD risk. Bayesian kernel machine regression confirmed the inverted U-shaped dose–response pattern for PBB-153 and the overall BFR mixture. Restricted cubic spline analyses corroborated the non-linear relationship between PBB-153 and PD, which was more pronounced among women and those aged 37–58 years. Sensitivity analyses substantiated these findings.ConclusionThis nationally representative cross-sectional study revealed a novel non-linear, inverted U-shaped relationship between serum levels of the brominated flame retardant PBB-153 and Parkinson’s disease risk in U.S. adults. The risk increased with higher PBB-153 exposure up to a point, beyond which it declined. This complex dose–response pattern highlights the importance of considering potential hormetic mechanisms and effect modifiers when evaluating environmental exposures and neurodegenerative diseases. Further research is warranted to elucidate the underlying biological pathways and inform risk mitigation strategies.

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

BackgroundIn 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.MethodsLE8 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.ResultsIn 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.ConclusionsA 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.

Thyroid-stimulating hormone (TSH) mediates the associations between maternal metals and neurodevelopment in children: A prospective cohort study

Insufficient research has focused on the effects of metal mixtures on children's neurodevelopment and TSH's potential mediating effect. Plasma concentrations of ten metals were measured among 2887 pregnant women in a persistent Chinese birth cohort. At age two, children's neurodevelopment was assessed using mental development indexes (MDIs) and psychomotor development indexes (PDIs), defining neurodevelopmental delay as MDI≤ 79 (cognitive delay) or PDI≤ 79 (motor delay). The associations between single and mixed metals with neurodevelopment delay risk were examined using generalized linear regression complemented by weighted quantile sum (WQS) regression. To investigate the mediated effects of infant Thyroid-Stimulating Hormone (TSH) on metal-associated neurodevelopment delay risk, mediation analyses were conducted. According to the single-metal model, V, Mn, and Pb levels are positively associated with neurodevelopment delay. The WQS model found consistent associations (Odds Ratio [OR] 1.55, 95% Confidence Interval [CI] 1.23 to 1.95), highlighting V, Mn, and Pb as the main causes of cognitive delay. Further mediation analysis revealed that the association between metals (mainly V, Mn, and Pb) and neurodevelopment delay risk is mediated by TSH, with proportions ranging from 3.18 to 10.14% (all P < 0.05). Our findings highlighted prenatal exposure to metals was associated with higher risks of neurodevelopmental delay, with TSH possibly mediating this effect.

Associations of co-exposure to polycyclic aromatic hydrocarbons and heavy metals with sex steroid hormones among children aged 6-19 years.

Introduction Polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) are endocrine-disrupting chemicals (EDCs) that may have a combined effect on sex hormone levels in children. This study investigated the correlations between co-exposure to PAHs and HMs and levels of sex steroid hormones in children. Methods We employed the data from the National Health and Nutrition Examination Survey (NHANES) from 2013 to 2016, including 1,167 participants aged 6-19 years. Sex hormone indicators include testosterone (TT), estradiol (E2), sex hormone-binding globulin (SHBG), free androgen index (FAI), and the TT/E2 ratio. Weighted multivariate linear regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) were used to analyze the associations between co-exposure to PAHs and HMs and sex steroid hormone levels. Results Co-exposure to PAHs and HMs was associated with a 16.2% reduction [95%CI (-0.321, -0.004)] in SHBG level among prepubertal males and a 16% reduction [95%CI (-0.30, -0.03)] in E2 level among pubertal males by the weighted quantile sum (WQS) regression, and cadmium (Cd) and mercury (Hg) contributed the highest weight respectively. In the Bayesian kernel machine regression (BKMR) model, co-exposure to PAHs and HMs was positively associated with TT/ E2 in pubertal males and negatively correlated with FAI in pubertal females, and 1-hydroxypyrene (1-PYR) and Cd were the most important components respectively. Conclusions Co-exposure to PAHs and HMs was associated with sex hormone levels in children. These findings highlight the necessity for preventing the effects of these chemicals on sex hormones.

Effects of single and combined urinary polycyclic aromatic hydrocarbon effects on lung function in the U.S. adult population

BackgroundThe impact of polycyclic aromatic hydrocarbons (PAHs) on lung function has garnered attention, but studies mostly focus on individual effect. This study investigates urinary PAH metabolites as biomarkers of exposure and assesses the relationships between single and combined exposures to nine urinary PAH metabolites and lung function in adults.MethodsData from 4040 adults in the 2007–2012 National Health and Nutrition Examination Survey (NHANES) were analyzed. Weighted generalized linear models estimated the effects of individual PAH metabolites on lung function. Additionally, weighted quantile sum (WQS) regression, quantile g-computation (qgcomp), and Bayesian kernel machine regression (BKMR) were employed to evaluate the combined impacts of multiple PAH metabolites.ResultsAnalyses of individual PAH metabolites revealed negative associations with lung function, excluding forced vital capacity (FVC). The WQS, qgcomp, and BKMR models consistently showed that exposure to multiple PAH metabolites was associated with lung function decrease. WQS indicated that 2-hydroxynaphthalene (2-NAP) was the largest contributor to the reductions in forced expiratory volume in 1 s (FEV1), FVC, peak expiratory flow (PEF), and forced expiratory flow from 25 to 75% of FVC (PEF25-75%). Additionally, 1-hydroxypyrene (1-PYR) was the primary PAH metabolite contributing to the decreases in FEV1/FVC and fractional exhaled nitric oxide (FeNO). The combined effect of urinary PAH metabolites did not affect FVC in the current smokers or FeNO in nonsmokers, but decreased FEV1/FVC in current smokers.ConclusionThis study strengthens the negative relationships between multiple PAH metabolites exposure and lung function in adults. Given the limitations of this study, including the lack of knowledge of other exposure pathways and the uncertainty of urinary metabolites, further research is necessary to explore the mechanisms underlying these associations and to address the limitations in exposure assessment.

Analysis of brominated flame retardants exposure-associated chronic kidney disease risk in the US population from the NHANES

BackgroundExposure to brominated flame retardants (BFRs) may contribute the advancement of chronic kidney disease (CKD). The objective is to evaluate the renal effects of BFRs in patients with CKD. MethodsTotally 7235 US participants of whom 1187 (16.41 %) were diagnosed with CKD were screened for this investigation from the National Health and Nutrition Examination Survey (NHANES) database spanning from 2005 to 2016. The isotope dilution gas chromatography high-resolution mass spectrometry (GC/IDHRMS) was employed for identification of 11 polybrominated diphenyl ethers (PBDEs) and PBB153 serving as the exposure factor. A set of covariates concerning basic characteristics, renal function indicators and suffering from diseases of these participants was considered as potential confounding factors. Subgroup analyses to examine the impact of age and gender on the relationship between serum BFRs and CKD, estimated glomerular filtration rate (eGFR), urinary albumin-to-creatinine ratio (UACR), serum creatinine (Scr), and blood urea nitrogen (BUN). Weighted Quantile Sum (WQS) regression and Quantile G-computation (QGC) analyses were applied to identify relationship of individual BFRs and other anthropometric indicators in CKD. ResultsAfter adjusting for available confounding factors, PBDE100, PBDE28, PBDE85, PBDE47, PBDE99, and PBDE154 were positively correlated with CKD. PBDE28, PBDE66, PBDE47, PBDE183, PBDE100, PBDE99, PBDE85, PBDE154, and PBB153 were significantly negatively correlated with eGFR. PBDE66 and PBDE183 were positively correlated with UACR. PBDE28, PBDE17, PBDE66, PBDE100, PBDE47, PBDE85, PBDE154, PBDE99, PBDE183 and PBB153 were positively correlated with Scr. PBDE17, PBDE28, PBDE154, PBDE66, PBDE47, PBDE99, and PBDE209 were negatively associated with BUN. PBB153 was positively correlated with BUN. The subgroup results gender and age are key factors affecting the relationship of PBDEs and renal function indicators. Both WQS and QGS analyses revealed that exposure to mixed BFR was negatively correlated with eGFR and BUN, of which PBB153 and PBDE66 contributed the most, respectively, as well as positively correlated with Scr, in which PBDE66 contributed the most. ConclusionSpecific BFRs exposure was significantly correlated with renal function indicators, enhancing the potential risk of CKD. This pioneer investigation shed light on an overlooked impact of BFR exposure on CKD in US.

Identifying effects of volatile organic compounds exposure on kidney stone prevalence in U.S. adults: a cross-sectional analysis of NHANES 2007-2020.

Our aim was to comprehensively investigate the relationship between blood volatile organic compounds (VOCs) and kidney stone prevalence for U.S. adults. In this cross-sectional study, 10,052 participants from the 2007-2020 National Health and Nutrition Examination Survey (NHANES) were included. Multivariate logistic regression model was employed to investigate the association between 9 blood VOCs and kidney stones. We explored the dose-response relationship between blood VOCs and kidney stones using restricted cubic spline (RCS) analysis. Additionally, weighted quantile sum (WQS) regression model was performed to assess the overall association of 9 blood VOCs with kidney stones. Finally, subgroup analyses were conducted to identify the findings in different populations at high prevalence. Logistic regression analysis and dose-response risk curves revealed that blood benzene (aOR = 1.308, 95% CI: 1.118-1.530, P = 0.001), blood ethylbenzene (aOR = 1.280, 95% CI: 1.054-1.554, P = 0.013), blood m-/p-xylene (aOR = 1.187, 95% CI: 1.008-1.398, P = 0.040), blood 2,5-dimethylfuran (aOR = 1.319, 95% CI: 1.135-1.533, P < 0.001) and blood furan (aOR = 1.698, 95% CI: 1.305-2.209, P < 0.001) were positively associated with the prevalence of kidney stones. WQS regression analysis revealed that exposure to mixed blood VOCs was positively correlated with kidney stone prevalence (OR = 1.34, 95% CI: 1.14-1.57), with furans carrying the greatest weight. Subgroup analyses suggested that kidney stones were more susceptible to the effects of blood VOCs in young and middle-aged, female, overweight and obese, non-hypertensive, and non-diabetic populations. In this study, the results indicated that high VOC exposure was positively and independently associated with kidney stones in U.S. adults. This finding highlighted the need for public health strategies to reduce VOC exposure and its role in kidney stone prevention and treatment.

B-158 Association between multiple heavy metals exposure and blood lipid levels: evidence from a cross-sectional study of Korean adults

Abstract Background Metals are ubiquitous in our environment and enter human body via various pathways, such as air, soil, food, water, etc. Increasing studies have found that metals are important risk factors in developing dyslipidemia. However, there is no consensus regarding the effects of co-exposure to multiple metals on blood lipid levels. We investigated both the joint and individual effects of this metal mixture exposure on human blood lipid levels. Methods Blood concentrations of four human toxic metals (Pb, Cs, Hg, and Cd) in 2,798 general populations from Korea were simultaneously determined as a measure of exposure. Weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were used to estimate associations of four blood metals and metals mixture with lipid profiles, including total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Results The mean age of the overall study population was 41.2 ± 9.85 years, and 66.9% were men. The prevalence of overweight or obesity, diabetes, and hypertension in the population was 62.5, 6.8, and 13.9%, respectively. In the multivariable linear regression model, the blood Cs was positively associated with TC and LDL-C(p &amp;lt; 0.05, all), and the blood Pb was positively associated with serum TG (p &amp;lt; 0.05, all). Also, the blood Cd was positively associated with serum HDL-C (p &amp;lt; 0.05, all). We did not identify any other obvious interaction between metals on the lipid profiles using a bivariate exposure-response function in BKMR. Conclusions Our finding suggests that combined exposure to this metal mixture may affect human blood lipid levels. Therefore, reducing exposure to heavy metals, such as Cs and Pb, should be a priority for the general population. However, future studies with a larger number of heavy metals are still needed to focus on the detrimental effects of single metals on lipid profiles as well as to identify key components.

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

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. 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. 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. 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.

Glycolysis mediates the association between phthalate exposure and the prevalence of childhood asthma: The National Health and Nutrition Examination Survey 2009–2018

Identified as a critical risk factor for childhood asthma, environmental pollution plays a pivotal role. However, research on the effects and mechanisms of phthalates mixture and their interactions in relation to childhood asthma is still lacking. In the National Health and Nutrition Examination Survey (NHANES) conducted from 2009 to 2018, our research explored the link between phthalates in urine and the prevalence of childhood asthma. In this study, which involved 810 participants, we used four different statistical analysis methods to investigate the association between urinary phthalate levels and childhood asthma. Additionally, we conducted a mediation analysis to explore whether the impact mechanism of phthalate exposure on childhood asthma operates through the glycolysis. Among the participants, 525 (64.81 %) individuals were diagnosed with asthma, with 330 (40.74 %) individuals undergoing testing for glycolytic markers. Through Spearman correlation analysis and weighted principal component analysis (W-PCA), it was found that mono-2-ethyl-5-carboxypentyl phthalate (MECPP), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-(2-ethyl)-hexyl phthalate (MEHP) and mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP) are the four most highly correlated phthalates. In addition, comprehensive analysis by the weighted generalized linear models (W-GLM), weighted quantile sum (WQS) and Bayesian kernel machine regression (BKMR) models showed that phthalates mixture were positively associated with the prevalence of childhood asthma, especially MECPP, MEHHP and MEOHP. More importantly, glycolysis participated as a mediator in the relationship between MECPP, MEHHP and MEOHP exposure and the prevalence of childhood asthma, explaining 41.194 %, 38.322 % and 39.871 % of the effects respectively. Therefore, our study revealed that phthalate exposure is a risk factor for asthma in children, and glycolysis may be involved as a potential mediator in this process. This conclusion will be verified through more prospective studies in the future.

Association between the levels of toxic heavy metals and schizophrenia in the population of Guangxi, China: A Case-Control Study

The relationship between body levels of heavy metals and the risk of schizophrenia remains unclear. This study investigates the relationship between plasma levels of toxic heavy metals and the risk of schizophrenia among adults in Guangxi, China. Plasma concentrations of lead (Pb), cadmium (Cd), arsenic (As), and chromium (Cr) were measured using inductively coupled plasma mass spectrometry (ICP-MS). To evaluate both the single and combined effects of metal exposure on the risk of schizophrenia, we employed multivariate logistic regression, Bayesian Kernel Machine Regression (BKMR), and generalized Weighted Quantile Sum (gWQS) models. Additionally, we employed the Comparative Toxicogenomics Database (CTD) to analyze the mechanistic pathways through which metal mixtures may induce schizophrenia. Relative mRNA expression levels were measured using Real-Time Quantitative Reverse Transcription Polymerase Chain Reaction (RT-qPCR). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to predict potential biological functions. In logistic regression models, compared to the lowest exposure group (Q1), the odds ratios (ORs) for Pb in groups Q2, Q3, and Q4 were 2.18 (95% CI: 1.20 - 3.94), 4.74 (95% CI: 2.52 - 8.95), and 3.62 (95% CI: 1.80 - 7.28), respectively. Both BKMR and gWQS models indicated a positive correlation between the combined effects of toxic heavy metal mixtures and the risk of schizophrenia, with Pb demonstrating the most substantial impact, particularly in older adults and females. Elevated levels of tumor necrosis factor (TNF) and interleukin-1 beta (IL-1β) were observed in patients with schizophrenia, while the expression of tumor protein p53 (TP53) was significantly reduced. These findings underscore the critical need to avoid exposure to toxic heavy metals to prevent schizophrenia, highlighting significant public health implications.

Association between Healthy Eating Index-2015 total and component food scores with reproductive lifespan among postmenopausal women: a population-based study from NHANES 2005–2016

BackgroundPrior research has demonstrated that nutrition plays a crucial role in the establishment and maturation of the reproductive lifetime. Although the specific dietary components involved in preventing or postponing the reproductive lifespan are still unknown, a healthy diet can affect the reproductive lifespan. Here, the study aimed to explore the relationship between reproductive lifespan and diet quality by utilizing the Healthy Eating Index-2015 (HEI-2015).MethodsIn this study, a total of 2761 postmenopausal women were selected from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2016. Diet quality was determined using HEI-2015 based on two 24-hour dietary recalls. Reproductive lifespan was defined as the number of years between self-reported age at menarche and menopause. Weighted linear regression and eXtreme Gradient Boosting (XGBoost) models were used to analyze the relationship between HEI-2015 and reproductive lifespan. Subsequently, the impact of various components of HEI-2015 on reproductive lifespan was assessed through weighted quantile sum (WQS) regression models.ResultsAmong 2761 postmenopausal women, the mean age was 63.7 years. 41.5% were obese, and 49.7% were non-Hispanic white. After adjusting for sociodemographic characteristics, lifestyle factors, and medical history, individuals in the highest tertile of HEI-2015 had a 4.81% (95% CI: 1.82–7.79%) longer reproductive time life. Higher HEI-2015 was also significantly associated with a higher likelihood of late menopause (p for trend < 0.05). Based on XGBoost models, the relative importance of HEI-2015 on reproductive lifespan was determined. Whole fruits, whole grains, total protein foods, and greens and beans significantly contributed to extending age at menopause and reproductive time life in the HEI-2015. The weights of the WQS index for age at menopause were 27.1%, 23.2%, 10.1%, and 7.5% respectively, while the weights of the WQS index for reproductive time life were 30.2%, 14.6%, 9.3%, and 14.0% respectively.ConclusionThere is a positive association between the HEI-2015 and reproductive lifespan. This underscores the significance of enhancing adherence to healthy dietary patterns in preventing a shorter reproductive lifespan.

The influence of multivitamins on neurological and growth disorders: a cross-sectional study.

While vitamin deficiencies can pose serious health consequences for the body, excessive intake of vitamins can also lead to health risks. However, there is limited data about the impact of multivitamins on neurological and growth disorders. This study aimed to investigate the relationship between multivitamins and neurological and growth disorders. A cross-sectional study was conducted with 16,921 subjects who visited the Children's Hospital of Nanjing Medical University from 2019 to 2021. The subjects were categorized into two groups based on their health status including 9,368 cases (4,484 with neurological disorders and 4,884 with growth disorders) and 7,553 healthy controls. Statistical tests including the T-test, Wilcoxon Rank Sum test, and Chi-Square test were employed to compare the groups, and logistic regression and Weighted Quantile Sum (WQS) regression were used to identify associations. In the adjusted logistic regression, serum 25 hydroxyvitamin D [25(OH)D], vitamin B2, and vitamin B9 were associated with decreasing risks of neurological disorders, whereas vitamin A, vitamin B1, and vitamin B12 were associated with increasing risks of neurological disorders. Nevertheless, vitamin A and vitamin B2 were associated with increasing risks of growth disorders. In the WQS model, nine multivitamins were positively associated with risks of neurological disorders, and Vitamins D and C were weighted the most. In addition, the inverse association but not statistically significant was observed between multivitamins and growth disorders, particularly growth retardation revealed a negative association, and some individual growth disorders revealed positive associations including obesity and malnutrition. In general, the study observed that multivitamins may be associated with neurological and growth disorders either positive or negative depending on the type of disorder.

The association of organochlorine pesticides and polychlorinated biphenyls exposure with dyslipidemia and blood lipids: The mediating effect of white blood cell counts

Epidemiological evidence regarding the associations of organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) with lipid metabolism and its potential biological mechanisms remain largely unknown. We intended to explore the associations of OCPs and PCBs with dyslipidemia and blood lipid levels, and further evaluate the mediating role of total and differential white blood cell (WBC) counts. We measured the blood lipid levels, the concentration of OCPs/PCBs and WBC counts in serum among 2036 adults in Wuhan city, China. In the multiple-pollutant models, the results showed that β-hexachlorocyclohexane (HCH), p,p′-dichlorodiphenyldichloroethylene (DDE), and PCB-153 were positively correlated with increased odds of dyslipidemia. p,p′-DDE and PCB-153 were correlated with elevated triglyceride (TG) and lowered high-density lipoprotein cholesterol (HDL-c). A positive relationship was observed between p,p′-DDE and total cholesterol (TC) as well. Meanwhile, weighted quantile sum (WQS) regression analyses revealed that PCB and OCP mixtures were positively related to dyslipidemia risk and TG and negatively associated with HDL-c, to which p,p′-DDE was the major contributor. BMI, gender and age might modify the associations of OCPs and PCBs with dyslipidemia and TG. Furthermore, we found that WBC counts were significantly associated with dyslipidemia and blood lipid levels, and a positive correlation was also found between p,p′-DDE and lymphocyte count. Mediation analysis further indicated that lymphocyte count might mediate the associations of p,p′-DDE with dyslipidemia, TG, and TC. Accordingly, our results showed that OCPs and PCBs were related to abnormal lipid metabolism, which was partially mediated by WBC counts.

The correlation between single and mixed trace elements exposure in systemic lupus erythematosus: A case-control study

BackgroundRecent studies have shown an association between trace elements and systemic lupus erythematosus (SLE), but the relationship between trace elements and SLE is still unclear. This study aims to determine the distribution of plasma trace elements in newly diagnosed SLE patients and the association between these essential and toxic element mixtures and SLE. MethodsIn total, 110 SLE patients and 110 healthy controls were included. Blood samples were collected. 15 plasma trace elements were quantified using an inductively coupled plasma mass spectrometer (ICP-MS). Multivariate logistic regression, restricted cubic spline (RCS), weighted quantile sum (WQS) regression, quantile g-computation (qgcomp), and Bayesian kernel machine regression (BKMR) are used to analyze the association between single and mixed exposure of elements and SLE. ResultsThe logistic regression model shows that, plasma lithium (Li) [OR (95 % CI): 1.963 (1.49–2.586)], vanadium (V) [OR (95 % CI): 2.617(1.645–4.166)] and lead (Pb) [OR (95 % CI): 1.603(1.197–2.145)] were positively correlated with SLE, while selenium (Se) [OR (95 % CI): 0.055(0.019–0.157)] and barium (Ba) [OR (95 % CI): 0.792(0.656–0.957)] had been identified as protective factors for SLE. RCS results showed a non-linear correlation between the elements Li, V, Ni, copper, Se, rubidium and SLE. In addition, WQS regression, qgcomp, and BKMR models consistently revealed significant positive effects of plasma Li and Pb on SLE, as well as significant negative effects of plasma Se. ConclusionsExposure to heavy metals such as Li and Pb is significantly positively correlated with SLE, but Se may be protective factors for SLE. In addition, there is a nonlinear correlation between the elements Li and Se and SLE, and there are complex interactions between the elements. In the future, larger populations and prospective studies are needed to confirm these associations.

Association between heavy metal exposure and biomarkers for non-alcoholic fatty liver disease in Korean adolescents

ObjectivesThe global prevalence of non-alcoholic fatty liver disease (NAFLD) in adolescents has increased. In addition to childhood obesity, environmental risk factors, such as heavy metals that are known to be involved in hepatotoxicity, play role in NAFLD occurrence. However, their association with NAFLD remains unclear. This study aimed to investigate the association between heavy metal exposure and NAFLD biomarkers in adolescents. MethodsIn this cross-sectional study, we used the data of a total of 1505 adolescents aged 12–17 years who participated in the Korean National Environmental Health Survey III (2015–2017) and IV (2018–2020). The presence of blood lead (BPb), blood mercury (BHg), urinary mercury (UHg), and urinary cadmium (UCd) were measured. Liver enzymes including serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), and gamma-glutamyl transferase (GGT) were evaluated. For NAFLD biomarkers, the hepatic steatosis index (HSI) was calculated. Multivariate linear regression models, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) model were used to investigate the association between heavy metals and NAFLD biomarkers. ResultsAmong heavy metals, mercury presence showed a significant association with NAFLD biomarkers. Two-fold increases in BHg and UHg were associated with 0.21 points (95 % confidence interval [CI]: 0.08–0.35) and 0.19 points (95 % CI: 0.09–0.30) higher HSI, respectively. In the WQS model, heavy metal mixture was significantly associated with increased HSI (β = 0.06, 95 % CI: 0.01–0.11). Similarly, in the BKMR model, heavy metal mixture was positively associated with NAFLD biomarkers, and BHg was the most important contributor in the association. ConclusionsBHg and UHg were significantly associated with NAFLD biomarkers in adolescents, indicating that organic and inorganic mercury exposure could potentially be a risk factor for NAFLD. To mitigate and address the risk of NAFLD associated with heavy metal exposure, it is imperative to take measure to reduce avoidable mercury exposure is necessary.