The link between exposure to a particular heavy metal or metalloid and the development of anemia is well established. However, the association between combined exposure to multiple heavy metal(loid)s and anemia in children is still lacking in evidence. In this study, a total of 266 children aged 3 to 7 were recruited from Guiyu, China. Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure blood heavy metal(loid) concentrations. Blood cell count, hemoglobin (HGB), mean corpuscular hemoglobin (MCH), mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), hematocrit (HCT), and red blood cell distribution width (RDW) were measured by an automated hematology analyzer. Erythrocyte-related parameters were negatively correlated with the Cu and Cu/Zn ratios and positively correlated with Cr, Ni, Zn, and Se by Spearman correlation analysis. Only blood Cu level was negatively correlated with HGB [β = -2.74, (95% Cl: -4.49, -0.995)], MCH [β = -0.505, (95% Cl: -0.785, -0.226)], MCV [β = -1.024, (95% Cl: -1.767, -0.281)], and MCHC [β = -2.137, (95% Cl: -3.54, -0.734)] by multiple linear regression analysis. The Bayesian Kernel Machine Regression (BKMR) model analysis indicated a negative correlation between the combined exposure to Cu, Zn, Pb, and Cr and MCH and MCV. The single-factor analysis showed a considerable statistical difference only with Cu on MCV, MCH, and HGB. Furthermore, the interaction analysis highlighted the interdependent effects of Cu and Zn, Pb and Zn, and Cr and Zn on MCH and MCV levels. Additionally, the oxidation and/or antioxidation reactions may play a significant role in the development of metal(loid)-induced anemia risk. It is crucial to investigate the effects of co-exposure to multiple heavy metal(loid) elements on anemia, especially the interrelationships and mechanisms among them.

UNASSIGNED: Accumulating studies have demonstrated associations between single lifestyle exposures and metabolic dysfunction-associated fatty liver disease (MAFLD). However, the joint effects of lifestyle exposures remain unclear, hindering the development of targeted prevention and control strategies. We aimed to investigate the joint associations between lifestyle exposomes and MAFLD.
UNASSIGNED: This study included 5,002 participants from NHANES 2017-2020. Lifestyle exposomes, including sleep duration, metabolic equivalent of task (MET), Healthy Eating Index (HEI)-2015 score, alcohol consumption, and smoke exposure, were identified from questionnaire data. MAFLD was diagnosed by vibration-controlled transient elastography measurements and laboratory data. A logistic regression model and the weighted quantile sum method were used to evaluate the associations of single and joint lifestyle exposomes, respectively, with MAFLD. The population attributable fractions (PAFs) were calculated to assess the population benefits of different intervention strategies.
UNASSIGNED: Per-quartile range increases in sleep duration (OR=0.883, 95% CI: 0.826-0.944), MET (0.916, 0.871-0.963), and HEI-2015 score (0.827, 0.756-0.904) were significantly associated with MAFLD. The joint exposure of sleep duration, MET, and HEI-2015 score was associated with MAFLD (0.772, 0.688-0.865), with the highest weight (importance) for MET (0.526). PAFs revealed greater intervention benefits for sleep and the HEI-2015 when the majority of the population (>5%) had a low MAFLD risk (weak intervention targets), whereas MET was the most efficient intervention strategy when minority populations (≤5%) had a low MAFLD risk (strong intervention targets).
UNASSIGNED: This study demonstrated significant associations between MAFLD and single and joint exposures to sleep duration, MET, and HEI-2015 and identified physical activity as the most important lifestyle factor. Further population benefit analyses may provide evidence and suggestions for population-level interventions.

BACKGROUND: Stroke is the second leading cause of death for all human beings and poses a serious threat to human health. Environmental exposure to a mixture of metals may be associated with the occurrence and development of stroke, but the evidence in the Chinese population is not yet conclusive.
OBJECTIVE: This study evaluated the association between stroke risk and 13 metals METHODS: Metal concentrations in whole blood samples from 100 stroke cases and 100 controls were measured by ICP-MS. The cumulative impact of mixed metal on stroke risk was investigated by using three statistical models, BKMR, WQS and QGC.
RESULTS: The case group had higher concentrations of Mg, Mn, Zn, Se, Sn, and Pb than the control group (p<0.05). BKMR model indicated a correlation between the risk of stroke and exposure to mixed metals. WQS model showed that Mg (27.2 %), Se (25.1 %) and Sn (14.8 %) were positively correlated with stroke risk (OR=1.53; 95 %Cl: 1.03-2.37, p=0.013). The QGC model showed that Mg (49.2 %) was positively correlated with stroke risk, while Ti (31.7 %) was negatively correlated with stroke risk.
CONCLUSIONS: Mg may be the largest contributor to the cumulative effect of mixed metal exposure on stroke risk, and the interaction between metals requires more attention. These findings could provide scientific basis for effectively preventing stroke by managing metals in the environment.

With increasing prevalence rate of depression by years, more attention has been paid to the influence of environmental pollutants on depression, but relationship between exposure to volatile organic compounds (VOCs) and depression is rarely studied. Therefore, this cross-sectional study use the National Center for Health Statistics (NHANES) database (2013-2016 years) to explore association between exposure to multiple VOCs and depression in general population. Multiple linear and logistic regression models were used to analyze the association between urinary VOC metabolism (mVOCs) and depression. To further analyze effect of multiple mVOCs mixed exposure, Bayesian kernel machine regression (BKMR) models were performed. A total of 3240 participants and 16 mVOCs were included in the analysis. Results showed that 10 mVOCs exposure were positively correlated with depression by multiple linear and logistic regression models, especially CYMA and MHBMA3, which also showed significant positive association with depression in BKMR model. Mixed exposure of multiple mVOCs was significantly positively correlated with depression. Gender differences were existed in effects of some VOCs concentrations on depression. AAMA, CYMA and MA had significant positive correlations with depression by women, and DHBMA had significant positive correlations with depression by men. Hence, this study showed that exposing to VOCs might have negative impacts on depression, and impact of CYMA and MHBMA3 on depression may be more evident, which provide new ideas for prevention and control of depression. But further research and exploration are needed to clarify the mechanism and influence factors of this relationship, to demonstrate the reliability of these relationship.

BACKGROUND: Organic phosphorus insecticides (OPPs) are a class of environmental pollutants widely used worldwide with potential human health risks. We aimed to assess the association between exposure to OPPs and osteoarthritis (OA) particularly in participants with atherosclerotic cardiovascular disease (ASCVD).
METHODS: Participants\' information was obtained from data in the National Health and Nutrition Examination (NHANES). Weighted logistic regression models were utilized to detect associations between OPPs metabolites and OA. Restricted cubic spline plots (RCS) were drawn to visualize the dose-response relationship between each metabolite and OA prevalence. Weighted quantile sum (WQS) regression and Bayesian kernel-machine regression (BKMR), were applied to investigate the joint effect of mixtures of OPPs on OA.
RESULTS: A total of 6871 samples were included in our study, no significant associations between OPPs exposure and OA incidence were found in whole population. However, in a subset of 475 individuals with ASCVD, significant associations between DMP (odds ratio [OR] as a continuous variable = 1.22, 95% confidence interval [CI]: 1.07,1.28), DEP ((odds ratio [OR] of the highest tertile compared to the lowest = 2.43, 95% confidence interval [CI]: 1.21,4.86), and OA were observed. DMP and DEP showed an increasing dose-response relationship to the prevalence of OA, while DMTP, DETP, DMDTP and DEDTP showed a nonlinear relationship. Multi-contamination modeling revealed a 1.34-fold (95% confidence intervals:0.80, 2.26) higher prevalence of OA in participants with high co-exposure to OPPs compared to those with low co-exposure, with a preponderant weighting (0.87) for the dimethyl dialkyl phosphate metabolites (DMAPs). The BKMR also showed that co-exposure of mixed OPPs was associated with an increased prevalence of OA, with DMP showing a significant dose-response relationship.
CONCLUSIONS: High levels of urine dialkyl phosphate metabolites (DAP) of multiple OPPs are associated with an increased prevalence of OA in patients with ASCVD, suggesting the need to prevent exposure to OPPs in ASCVD patients to avoid triggering OA and further avoid the occurrence of cardiovascular events caused by OA.

BACKGROUND: Polycyclic aromatic hydrocarbons and phthalate acid esters (PAHs & PAEs), known as endocrine disrupting chemicals (EDCs), widely exist in daily life and industrial production. Previous studies have suggested that PAHs & PAEs may modify the intrauterine homeostasis and have adverse effects on fetal development. However, epidemiological evidence on the associations between PAHs & PAEs and gestational diabetes mellitus (GDM) is still limited.
OBJECTIVE: To investigate the effects of prenatal PAHs &PAEs exposure on the risk of GDM and hyperglycemia in pregnant women.
METHODS: The study population was a total of 725 pregnant women from a prospective birth cohort study conducted from December 2019 to December 2021. Blood glucose levels were collected by the hospital information system. Urinary PAHs & PAEs concentrations were determined by gas chromatography tandem mass spectrometry. The Poisson regression in a generalized linear model (GLM), multiple linear regression, quantile-based g-computation method (qgcomp), and Bayesian kernel machine regression (BKMR) were applied to explore and verify the individual and overall effects of PAHs & PAEs on glucose homeostasis. Potential confounders were adjusted in all statistical models.
RESULTS: A total of 179 (24.69%) women were diagnosed with GDM. The Poisson regression suggested that a ln-unit increment of 4-OHPHE (4-hydroxyphenanthrene) (adjusted Risk Ratio (aRR) = 1.13; 1.02-1.26) was associated with the increased GDM risk. Mixed-exposure models showed similar results. We additionally found that MBZP (mono-benzyl phthalate) (aRR = 1.19; 1.02-1.39) was positively related to GDM risk in qgcomp model. Although neither model demonstrated that 2-OHNAP (2-hydroxynaphthalene) and 9-OHFLU (9-hydroxyfluorene) increased the risk of GDM, 2-OHNAP and 9-OHFLU exposure significantly increased blood glucose levels. BKMR model further confirmed that overall effects of PAHs & PAEs were significantly associated with the gestational hyperglycemia and GDM risk.
CONCLUSIONS: Our study presents that environmental exposure to PAHs & PAEs was positively associated with gestational glucose levels and the risks of developing GDM. In particular, 2-OHNAP, 9-OHFLU, 4-OHPHE and MBZP may serve as important surveillance markers to prevent the development of GDM.

Previous studies have related single toxic metals (TMs) to hyperuricemia (HUA) among the general population, however, the association of the TM mixture with HUA, especially in older adults, remains poorly understood. We aimed to examine the relationships between individual TMs and their mixture and HUA in Chinese rural older adults. This study consisted of 2075 rural older adults aged 60 years or over. Blood concentrations of aluminum (Al), arsenic (As), barium (Ba), cadmium (Cd), cesium (Cs), gallium (Ga), mercury (Hg), lead (Pb), thallium (Tl), and uranium (U) were detected using inductively coupled plasma mass spectrometry. The associations of single TMs with HUA were assessed using logistic regression and restricted cubic spline (RCS) models, and the association of TM mixture with HUA was explored using the elastic net with environmental risk score (ENET-ERS), quantile g-computation (QGC), and Bayesian kernel machine regression (BKMR) models, respectively. Adjusted logistic regression model showed that Cs (OR = 1.65, 95% CI 1.37-1.99) and Pb (OR = 1.46, 95% CI 1.28-1.67) were positively related to HUA, and RCS model exhibited a positive linear association of Cs and Pb with HUA. ENET-ERS and QGC models quantified a positive correlation between the TM mixture and the odds of HUA, with estimated ORs of 1.15 (95% CI 1.11-1.19) and 1.84 (95% CI 1.37-2.47), respectively, and Cs and Pb had the most weight. BKMR model demonstrated a significant linear association between the TM mixture and increased odds of HUA, with the posterior inclusion probabilities (PIPs) of both Cs and Pb being 1.00. Moreover, we observed a positive interaction between Cs and Pb on HUA. The TM mixture is associated with increased odds of HUA in rural older adults, which may mainly be driven by Cs and Pb. Subsequent studies are warranted to confirm these findings and clarify the mechanisms linking multiple TMs with HUA.

BACKGROUND: Organophosphate esters (OPEs) and Per- and polyfluoroalkyl substances (PFAS) are ubiquitous environmental contaminants with common exposure sources, leading to their widespread presence in human body. However, evidence on co-exposure to OPEs and PFAS and its impact on cardiovascular-kidney-liver-metabolic biomarkers remains limited.
METHODS: In this cross-sectional study, 467 adults were enrolled from January to May 2022 during physical visits in Shijiazhuang, Hebei province. Eleven types of OPEs and twelves types of PFAS were detected, among which eight OPEs and six PFAS contaminants were detected in more than 60% of plasma samples. Seventeen biomarkers were assessed to comprehensively evaluate the cardiovascular-kidney-liver-metabolic function. Multiple linear regression, multipollutant models with sparse partial least squares, and Bayesian kernel machine regression (BKMR) models were applied to examine the associations of individual OPEs and PFAS and their mixtures with organ function and metabolism, respectively.
RESULTS: Of the over 400 exposure-outcome associations tested when modelling, we observed robust results across three models that perfluorohexanoic acid (PFHxS) was significantly positively associated with alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), and indirect bilirubin (IBIL). Perfluorononanoic acid was significantly associated with decreased AST/ALT and increased very-low-density lipoprotein cholesterol levels. Besides, perfluorodecanoic acid was correlated with increased high lipoprotein cholesterol and perfluoroundecanoic acid was consistently associated with lower glucose level. BKMR analysis showed that OPEs and PFAS mixtures were positively associated with IBIL and TBIL, among which PFHxS was the main toxic chemicals.
CONCLUSIONS: Our findings suggest that exposure to OPEs and PFAS, especially PFHxS and PFNA, may disrupt organ function and metabolism in the general population, providing insight into the potential pathophysiological mechanisms of OPEs and PFAS co-exposure and chronic diseases.

UNASSIGNED: Heavy metal exposure is an important cause of reduced bone mineral density (BMD). Epidemiological studies focusing on the effects of mixed heavy metal exposure on BMD in middle-aged and older people are scarce. In single-metal studies, men and women have shown distinct responses of BMD to environmental metal exposure. This study therefore aimed to elucidate the association between mixed heavy metal exposure and BMD and to investigate whether it is sex-specific.
UNASSIGNED: Data from the 2017-2020 National Health and Nutrition Examination Survey were selected for this cross-sectional study. The study used three statistical methods, i.e., linear regression, Bayesian kernel machine regression (BKMR) modeling, and weighted quartiles (WQS) regression, to explore the association between the urinary concentrations of 11 metals (barium, cadmium, cobalt, cesium, manganese, molybdenum, lead, antimony, tin, thallium, and Tungsten), either individually or as a mixture, and total femoral BMD.
UNASSIGNED: A total of 1,031 participants were included in this study. Femoral BMD was found to be higher in men than women. A significant negative correlation between the urinary concentrations of the 10 metals and femoral BMD was found in the overall cohort. Further gender sub-stratified analyses showed that in men, urinary metal concentrations were negatively correlated with femoral BMD, with cobalt and barium playing a significant and non-linear role in this effect. In women, although urinary metal concentrations negatively modulated femoral BMD, none of the correlations was statistically significant. Antimony showed sex-specific differences in its effect.
UNASSIGNED: The urinary concentrations of 10 mixed heavy metals were negatively correlated with femoral BMD in middle-aged and older participants, and this effect showed gender differences. These findings emphasize the differing role of mixed metal exposure in the process of BMD reduction between the sexes but require further validation by prospective studies.

An increasing number of studies suggest that environmental pollution may increase the risk of vitamin D deficiency (VDD). However, less is known about arsenic (As) exposure and VDD, particularly in Chinese pregnant women.
This study examines the correlations of different urinary As species with serum 25 (OH) D and VDD prevalence.
We measured urinary arsenite (As3+), arsenate (As5+), monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) levels and serum 25(OH)D2, 25(OH)D3, 25(OH) D levels in 391 pregnant women in Tianjin, China. The diagnosis of VDD was based on 25(OH) D serum levels. Linear relationship, Logistic regression, and Bayesian kernel machine regression (BKMR) were used to examine the associations between urinary As species and VDD.
Of the 391 pregnant women, 60 received a diagnosis of VDD. Baseline information showed significant differences in As3+, DMA, and tAs distribution between pregnant women with and without VDD. Logistic regression showed that As3+ was significantly and positively correlated with VDD (OR: 4.65, 95% CI: 1.79, 13.32). Meanwhile, there was a marginally significant positive correlation between tAs and VDD (OR: 4.27, 95% CI: 1.01, 19.59). BKMR revealed positive correlations between As3+, MMA and VDD. However, negative correlations were found between As5+, DMA and VDD.
According to our study, there were positive correlations between iAs, especially As3+, MMA and VDD, but negative correlations between other As species and VDD. Further studies are needed to determine the mechanisms that exist between different As species and VDD.