Sex-specific associations of blood and urinary manganese levels with glucose levels, insulin resistance and kidney function in US adults: National health and nutrition examination survey 2011-2016

Associations between Life's Essential 8 and risks of all-cause and cardiovascular mortality in cancer survivors: A prospective cohort study from NHANES

Background

Life's Essential 8 (LE8), an indicator of cardiovascular health (CVH), can predict overall and cardiovascular mortality in the general population. Considering that cancer survivors have a higher risk of cardiovascular disease (CVD), our study aimed to investigate the association between LE8 and the prognosis of cancer survivors.

Methods

A total of 2191 cancer survivors were included from the National Health and Nutrition Examination Survey (2005-2018). LE8 scores, derived from eight individual metrics, were categorized into three groups: low (0-49), moderate (50-79), and high (80-100). Cox regression analysis, nonlinear analysis, sensitivity analysis, and subgroup analysis were conducted to explore the association between LE8 scores and mortality risks, adjusting for potential confounders.

Results

During a median follow-up of six years, 479 deaths were recorded, including 118 CVD events and 156 cancer events. LE8 scores showed an inverse linear relationship with all-cause and cardiovascular mortality. A 10-point increase in LE8 scores was associated with a 25 % reduction in all-cause mortality (hazard ratio [HR], 0.75; 95 % CI, 0.66-0.85) and a 29 % reduction in cardiovascular mortality (HR, 0.71; 95 % CI, 0.57-0.89). Additionally, moderate CVH was linked to a lower risk of all-cause mortality (HR, 0.55; 95 % CI, 0.37-0.81), while high CVH was associated with an even lower risk (HR, 0.35; 95 % CI, 0.19-0.68). Similarly, moderate CVH demonstrated a decreased risk of cardiovascular mortality (HR, 0.31; 95 % CI, 0.15-0.63), with high CVH showing an even lower risk (HR, 0.23; 95 % CI, 0.09-0.58). However, LE8 scores was not associated with cancer-specific mortality.

Conclusions

A higher LE8 score was independently associated with a decreased risk of both all-cause and cardiovascular mortality in cancer survivors, underscoring the significance of optimizing CVH during the survivorship phase of cancer care.

Removal of metals and assimilable organic carbon by activated carbon and reverse osmosis point-of-use water filtration systems

Activated carbon (AC) systems and reverse osmosis (RO) systems are commonly used point-of-use (POU) water filtration systems for removing trace-level contaminants in tap water to protect human health. However, limited research has been done to evaluate their effectiveness in removing heavy metals like manganese (Mn) and uranium (U), or to assess the potential for undesired microbial growth within POU systems, which can reduce their treatment efficiency. This study aimed to systematically evaluate the removal of metals and assimilable organic carbon (AOC) in POU systems. AC systems were operated to 200% of their designed treatment capacities and RO systems were run for three weeks. The results showed that AC systems were generally ineffective at removing metals from drinking water, while RO systems effectively removed them. Both Mn and U were poorly removed by AC systems. Calcium (Ca) and magnesium (Mg) were poorly removed by AC systems, with efficiencies of less than 1%. Iron (Fe) removal by AC systems varied between 61% and 84%. Copper (Fe), likely due to its low influent concentration (<30 μg L-1), was effectively removed by AC systems with efficiencies over 95%. In contrast, RO systems consistently removed all metals effectively. Mn and U removal in RO systems exceeded 95%, while Ca, Mn, Fe, and Cu were all removed with efficiencies greater than 98%. AOC was effectively removed from all AC and RO systems, but with high variability in removal efficiency, which is likely attributed to the heterogeneity of biofilm and microbial growth within the POU systems. The new knowledge generated from this study can improve our understanding of chemical contaminant removal in POU systems and inform the development of better strategies for designing and operating POU systems to remove chemical contaminants in drinking water and mitigate their associated health risks.

Associations between individual and mixed urinary metal exposure and dyslipidemia among Chinese adults: Data from the China Multi-Ethnic Cohort Study

The prevalence of dyslipidemia is increasing, and it has become a significant global public health concern. Some studies have demonstrated contradictory relationships between urinary metals and dyslipidemia, and the combined effects of mixed urinary metal exposure on dyslipidemia remain ambiguous. In this study, we examined how individual and combined urinary metal exposure are associated with the occurrence of dyslipidemia. According to the data from the 2018-2019 baseline survey database of the China Multi-Ethnic Cohort (CMEC) Study, a population of 9348 individuals was studied. Inductively coupled plasmamass spectrometry (ICP-MS) was used to measure 21 urinary metal concentrations in the collected adult urinary samples. The associations between urinary metals and dyslipidemia were analyzed by logistic regression, weighted quantile sum regression (WQS), and quantile-based g-computation (qgcomp), controlled for potential confounders to examine single and combined effects. Dyslipidemia was detected in 3231 individuals, which represented approximately 34.6 % of the total population. According to the single-exposure model, Al and Na were inversely associated with the risk of dyslipidemia (OR = 0.95, 95 % CI: 0.93, 0.98; OR = 0.89, 95 % CI: 0.83, 0.95, respectively), whereas Zn, Ca, and P were positively associated (OR = 1.69, 95 % CI: 1.42, 2.01; OR = 1.12, 95 % CI: 1.06, 1.18; OR = 1.21, 95 % CI: 1.09, 1.34, respectively). Moreover, Zn and P were significantly positively associated even after adjusting for these metals, whereas Al and Cr were negatively associated with the risk of dyslipidemia. The results of the WQS and qgcomp analyses showed that urinary metal mixtures were positively associated with the risk of dyslipidemia (OR = 1.26, 95 % CI: 1.15, 1.38; OR = 1.09, 95 % CI: 1.01, 1.19). This positive association was primarily driven by Zn, P, and Ca. In the sensitivity analyses with collinearity diagnosis, interaction, and stratified analysis, the results remained, confirming the reliability of the study findings. In this study, the individual and combined effects of urinary Zn, P, and Ca on dyslipidemia were determined, which provided novel insights into the link between exposure to metals and dyslipidemia.

Crohn's Disease-Associated Pathogenic Mutation in the Manganese Transporter ZIP8 Shifts the Ileal and Rectal Mucosal Microbiota Implicating Aberrant Bile Acid Metabolism

BACKGROUND

A pathogenic mutation in the manganese transporter ZIP8 (A391T; rs13107325) increases the risk of Crohn's disease. ZIP8 regulates manganese homeostasis and given the shared need for metals between the host and resident microbes, there has been significant interest in alterations of the microbiome in carriers of ZIP8 A391T. Prior studies have not examined the ileal microbiome despite associations between ileal disease and ZIP8 A391T.

METHODS

Here, we used the Pediatric Risk Stratification Study (RISK) cohort to perform a secondary analysis of 16S ribosomal RNA gene sequencing data obtained from ileal and rectal mucosa to study associations between ZIP8 A391T carrier status and microbiota composition.

RESULTS

We found sequence variants mapping to Veillonella were decreased in the ileal mucosa of ZIP8 A391T carriers. Prior human studies have demonstrated the sensitivity of Veillonella to bile acid abundance. We therefore hypothesized that bile acid homeostasis is differentially regulated in carriers of ZIP8 A391T. Using a mouse model of ZIP8 A391T, we demonstrate an increase in total bile acids in the liver and stool and decreased fibroblast growth factor 15 (Fgf15) signaling, consistent with our hypothesis. We confirmed dysregulation of FGF19 in the 1000IBD cohort, finding that plasma FGF19 levels are lower in ZIP8 A391T carriers with ileocolonic Crohn's disease.

CONCLUSIONS

In the search for genotype-specific therapeutic paradigms for patients with Crohn's disease, these data suggest targeting the FGF19 pathway in ZIP8 A391T carriers. Aberrant bile acid metabolism may precede development of Crohn's disease and prioritize study of the interactions between manganese homeostasis, bile acid metabolism and signaling, and complicated ileal Crohn's disease.

Sex- and age-specific associations of serum essential elements with diabetes among the Chinese adults: a community-based cross-sectional study

BACKGROUND

Although several studies have found the relationship between essential elements and diabetes, the studies about the association of essential elements with diabetes diagnosed according to an oral glucose tolerance test (OGTT) and glycated hemoglobin (HbA1c) in a sex- and age-specific manner were limited. To investigate the linear and nonlinear relationship of five essential elements including iron (Fe), copper (Cu), Zinc (Zn), magnesium (Mg), and calcium (Ca) with diabetes, fasting plasma glucose (FPG), 2-h postprandial plasma glucose (PPG), and HbA1c and to evaluate the sex- and age-specific heterogeneities in these relationships.

METHODS

A total of 8392 community-dwelling adults were recruited to complete a questionnaire and undergo checkups of anthropometric parameters and serum levels of five metals (Fe, Cu, Zn, Mg, and Ca). The multivariable logistic and linear regression, the restricted cubic spline (RCS) analysis, and subgroup analysis were applied to find the associations between the essential elements and the prevalence of diabetes as well as FPG, PPG, and HbA1c.

RESULTS

In the multivariable logistic regression and multivariable linear regression, serum Cu was positively associated with FPG, PPG, and HbA1c while serum Mg was significantly inversely correlated with FPG, PPG, HbA1c, and diabetes (all P < 0.001). In the RCS analysis, the non-linear relationship of Cu and diabetes (P < 0.001) was found. In the subgroup analysis, stronger positive associations of Cu with diabetes (P for interaction = 0.027) and PPG (P for interaction = 0.002) were found in younger women.

CONCLUSIONS

These findings may lead to more appropriate approaches to essential elements supplementation in people with diabetes of different ages and sexes. However, more prospective cohort and experimental studies are needed to probe the possible mechanism of sex- and age-specific associations between serum essential elements and diabetes.

Analysis of relationship between mixed heavy metal exposure and early renal damage based on a weighted quantile sum regression and Bayesian kernel machine regression model

BACKGROUND

Occupation, environmental heavy metal exposure, and renal function impairment are closely related. The relationship between mixed metal exposure and chronic renal injury is inadequately described, and the interaction between each metal is poorly explored.

OBJECTIVE

This cross-sectional study assessed mixed heavy metal exposure in the general population and their relationship with early renal impairment, as well as possible interactions between metals.

METHODS

The study was conducted in two communities in Taiyuan City in northern China. Multiple linear regression, weighted quantile sum (WQS) and bayesian kernel machine regression (BKMR) regression were used to explore the relationship of mixed heavy metal exposure with indicators of early kidney injury (N-acetyl-β-D- glucosidase (UNAG), urinary albumin (UALB)). Meanwhile, BKMR was used to explore the possible interactions between mixed heavy metal and indicators of early kidney injury.

RESULTS

Based on the WQS regression results, we observed adjusted WQS coefficient β (β-WQS) of 0.711 (95% CI: 0.543, 0.879). Notably, this change was primarily driven by As (35.6%) and Cd (22.5%). In the UALB model, the adjusted β-WQS was 0.657 (95% CI: 0.567, 0.747), with Ni (30.5%), Mn (22.1%), Cd (21.2%), and As (18.6%) exhibiting higher weights in the overall effect. The BKMR results showed a negative interaction between As and other metals in the UNAG and UALB models, a positive interaction between Mn and Ni and other metals. No significant pairwise interaction was observed in the association of metals with indicators of early kidney injury.

CONCLUSION

Through multiple linear regression, WQS regression, and BKMR analyses, we found that exposure to mixed heavy metals such as Cd, Cr, Pb, Mn, As, Co and Ni was positively correlated with UNAG and UALB. Moreover, there are complex interactions between two or more heavy metals in more than one direction.

Complex interplay of heavy metals and renal injury: New perspectives from longitudinal epidemiological evidence

BACKGROUND

Epidemiological studies have reported associations between heavy metals and renal function. However, longitudinal studies are required to further validate these associations and explore the interactive effects of heavy metals on renal function and their directional influence.

METHOD

This study, conducted in Northeast China from 2016 to 2021, included a four-time repeated measures design involving 384 participants (1536 observations). Urinary concentrations of chromium (Cr), cadmium (Cd), manganese (Mn), and lead (Pb) were measured, along with renal biomarkers including urinary microalbumin (umAlb), urinary albumin-to-creatinine ratio (UACR), N-acetyl-β-D-glucosaminidase (NAG), and β2-microglobulin (β2-MG) levels. Estimated glomerular filtration rate (eGFR) was calculated. A Linear Mixed Effects Model (LME) examined the association between individual metal exposure and renal biomarkers. Subsequently, Quantile g-computation and Bayesian Kernel Machine Regression (BKMR) models assessed the overall effects of heavy metal mixtures. Marginal Effect models examined the directional impact of metal interactions in the BKMR on renal function.

RESULT

Results indicate significant impacts of individual and combined exposures of Cr, Cd, Pb, and Mn on renal biomarkers. Metal interactions in the BKMR model were observed, with synergistic effects of Cd-Cr on NAG, umAlb, UACR; Cd-Pb on NAG, UACR; Pb-Cr on umAlb, UACR, eGFR-MDRD, eGFR-EPI; and an antagonistic effect of Mn-Pb-Cr on UACR.

CONCLUSION

Both individual and combined exposures to heavy metals are associated with renal biomarkers, with significant synergistic interactions leading to renal damage. Our findings elucidate potential interactions among these metals, offering valuable insights into the mechanisms linking multiple metal exposures to renal injury.

Association between machine learning-assisted heavy metal exposures and diabetic kidney disease: a cross-sectional survey and Mendelian randomization analysis

Background and objective

Heavy metals, ubiquitous in the environment, pose a global public health concern. The correlation between these and diabetic kidney disease (DKD) remains unclear. Our objective was to explore the correlation between heavy metal exposures and the incidence of DKD.

Methods

We analyzed data from the NHANES (2005-2020), using machine learning, and cross-sectional survey. Our study also involved a bidirectional two-sample Mendelian randomization (MR) analysis.

Results

Machine learning reveals correlation coefficients of -0.5059 and - 0.6510 for urinary Ba and urinary Tl with DKD, respectively. Multifactorial logistic regression implicates urinary Ba, urinary Pb, blood Cd, and blood Pb as potential associates of DKD. When adjusted for all covariates, the odds ratios and 95% confidence intervals are 0.87 (0.78, 0.98) (p = 0.023), 0.70 (0.53, 0.92) (p = 0.012), 0.53 (0.34, 0.82) (p = 0.005), and 0.76 (0.64, 0.90) (p = 0.002) in order. Furthermore, multiplicative interactions between urinary Ba and urinary Sb, urinary Cd and urinary Co, urinary Cd and urinary Pb, and blood Cd and blood Hg might be present. Among the diabetic population, the OR of urinary Tl with DKD is a mere 0.10, with a 95%CI of (0.01, 0.74), urinary Co 0.73 (0.54, 0.98) in Model 3, and urinary Pb 0.72 (0.55, 0.95) in Model 2. Restricted Cubic Splines (RCS) indicate a linear linkage between blood Cd in the general population and urinary Co, urinary Pb, and urinary Tl with DKD among diabetics. An observable trend effect is present between urinary Pb and urinary Tl with DKD. MR analysis reveals odds ratios and 95% confidence intervals of 1.16 (1.03, 1.32) (p = 0.018) and 1.17 (1.00, 1.36) (p = 0.044) for blood Cd and blood Mn, respectively.

Conclusion

In the general population, urinary Ba demonstrates a nonlinear inverse association with DKD, whereas in the diabetic population, urinary Tl displays a linear inverse relationship with DKD.

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 serum copper and blood glucose: a mediation analysis of inflammation indicators in the NHANES (2011-2016)

Background

The rising prevalence of diabetes underscores the need for identifying effective prevention strategies. Recent research suggests environmental factors, particularly heavy metals like copper, significantly influence health outcomes, including diabetes, through mechanisms involving inflammation and oxidative stress. This study aims to explore how serum copper levels affect blood glucose, employing NHANES data from 2011 to 2016, to provide insights into environmental health's role in diabetes prevention and management.

Methods

The study analyzed data from 2,318 NHANES participants across three cycles (2011-2016), focusing on those with available data on serum copper, inflammatory markers, and blood glucose levels. We utilized principal component analysis for selecting inflammatory markers, mediation analysis to examine direct and indirect effects, multiple linear regression for assessing relationships between markers and glucose levels, and weighted quantile sum regression for evaluating individual and collective marker effects, adjusting for demographic variables and serum copper.

Results

Participants averaged 42.70 years of age, with a near-even split between genders. Average serum copper was 119.50 μg/dL, white blood cell count 6.82 × 109/L, and fasting blood glucose 107.10 mg/dL. Analyses identified significant mediation by inflammatory markers (especially white blood cells: 39.78%) in the copper-blood glucose relationship. Regression analyses highlighted a positive correlation between white blood cells (estimate: 1.077, 95% CI: 0.432 to 2.490, p = 0.013) and copper levels and a negative correlation for monocyte percentage (estimate: -1.573, 95% CI: 0.520 to -3.025, p = 0.003). Neutrophil percentage was notably influential in glucose levels. Sensitive analyses confirmed the study's findings.

Conclusion

Serum copper levels significantly impact blood glucose through inflammatory marker mediation, highlighting the importance of considering environmental factors in diabetes management and prevention. These findings advocate for public health interventions and policies targeting environmental monitoring and heavy metal exposure reduction, emphasizing the potential of environmental health measures in combating diabetes incidence.

Associations of metals and metal mixtures with glucose homeostasis: A combined bibliometric and epidemiological study

This study employs a combination of bibliometric and epidemiological methodologies to investigate the relationship between metal exposure and glucose homeostasis. The bibliometric analysis quantitatively assessed this field, focusing on study design, predominant metals, analytical techniques, and citation trends. Furthermore, we analyzed cross-sectional data from Beijing, examining the associations between 14 blood metals and 6 glucose homeostasis markers using generalized linear models (GLM). Key metals were identified using LASSO-PIPs criteria, and Bayesian kernel machine regression (BKMR) was applied to assess metal mixtures, introducing an "Overall Positive/Negative Effect" concept for deeper analysis. Our findings reveal an increasing research interest, particularly in selenium, zinc, cadmium, lead, and manganese. Urine (27.6%), serum (19.0%), and whole blood (19.0%) were the primary sample types, with cross-sectional studies (49.5%) as the dominant design. Epidemiologically, significant associations were found between 9 metals-cobalt, copper, lithium, manganese, nickel, lead, selenium, vanadium, zinc-and glucose homeostasis. Notably, positive-metal mixtures exhibited a significant overall positive effect on insulin levels, and notable interactions involving nickel were identified. These finding not only map the knowledge landscape of research in this domain but also introduces a novel perspective on the analysis strategies for metal mixtures.

Manganese induces podocyte injury through regulating MTDH/ALKBH5/NLRP10 axis: Combined analysis at epidemiology and molecular biology levels

Manganese (Mn) is an essential micronutrient required for various biological processes but excess exposure to Mn can cause neurotoxicity. However, there are few reports regarding the toxicity effect of Mn on the kidney as well as the underlying molecule mechanism. Herein, in vivo experiments were adopted to assess the toxicity effects associated with Mn, and found that chronic Mn treatment induced the injury of glomerular podocytes but not renal tubule in rats. Genome-wide CRISPR/Cas9 knockout screen was then employed to explore the biotargets of the toxic effect of Mn on podocytes. Through functional analyses of the enriched candidate genes, NLRP10 was found to be significantly up-regulated and mediated Mn-induced podocyte apoptosis. Further mechanism investigation revealed that NLRP10 expression was regulated by demethylase AlkB homolog 5 (ALKBH5) in an m6A-dependent fashion upon Mn treatment. Moreover, Mn could directly bind to Metadherin (MTDH) and promoted its combination with ALKBH5 to promote NLRP10 expression and cell apoptosis. Finally, logistic regressions, restricted cubic spline regressions and uniform cubic B-spline were used to investigate the association between Mn exposure and the risk of chronic kidney disease (CKD). A U-shaped nonlinear relationship between CKD risk and plasma Mn level, and a positive linear relationship between CKD risk and urinary Mn levels was found in our case-control study. To sum up, our findings illustrated that m6A-dependent NLRP10 regulation is indispensable for podocyte apoptosis and nephrotoxicity induced by Mn, providing fresh insight into understanding the health risk of Mn and a novel target for preventing renal injury in Mn-intoxicated patients.

The relationship between plasma nickel concentrations and type 2 diabetes mellitus risk: A protective effect within a specific range

BACKGROUND

Nickel is considered an essential nutrient for certain microbial, plant, and animal species, but its role in human health remains controversial. Some studies have reported the relationship between nickel and type 2 diabetes mellitus (T2DM), but the results are not consistent and the mechanism is not clear, which needs further exploration.

AIM

To investigate the possible correlation between nickel and T2DM.

METHODS

We conducted a case-control study of 192 patients with T2DM and 189 healthy controls at a hospital in central China. Plasma concentrations of nickel and six other trace elements were measured with inductively coupled plasma mass spectrometry. Logistic regression models, restricted cubic spline models (RCS), and Bayesian kernel machine regression (BKMR) were used to evaluate the relationship between plasma nickel and T2DM and its metabolic risk factors, as well as the presence or absence of interactions between nickel and other elements.

RESULTS

The T2DM group exhibited considerably lower plasma nickel levels than the control group (P < 0.001). Whether using a crude or adjusted model, logistic regression analysis finds a negative correlation between nickel levels and the risk of T2DM (P trend < 0.001). According to the RCS, the risk of T2DM reduces with rising nickel levels when the value is below 6.1 μg/L; nickel has a negative linear correlation with fasting plasma glucose (FPG), an inverse U-shaped connection with superoxide dismutase (SOD), and a positive linear correlation with malondialdehyde (MDA) (all P overall < 0.05). The plasma nickel concentration was positively correlated with zinc, vanadium, and chromium (r = 0.23, 0.11, and 0.19, respectively; all P < 0.05) and negatively correlated with copper (r = - 0.11, P < 0.05). In the BKMR model, interactions of nickel with zinc on T2DM and SOD, nickel with chromium on T2DM and homeostasis model assessment of β cell (HOMA-β), and nickel with copper on FPG, homeostasis model assessment of insulin (HOMA-IR), and MDA were observed.

CONCLUSION

Nickel may have a dual effect on the risk of T2DM, with a protective range of less than 6.1 μg/L. Potential interactions between nickel, copper, zinc, and chromium existed in their associations with T2DM and its metabolic risk factors.

Associations Between Individual and Combined Metal Exposures in Whole Blood and Kidney Function in U.S. Adults Aged 40 Years and Older

The effects of metal exposure on kidney function have been reported in previous literature. There is limited and inconsistent information on the associations between individual and combined exposures to metals and kidney function among the middle-aged and older population. The aim of this study was to clarify the associations of exposure to individual metals with kidney function while accounting for potential coexposure to metal mixtures and to evaluate the joint and interactive associations of blood metals with kidney function. A total of 1669 adults aged 40 years and older were enrolled in the present cross-sectional study using the 2015-2016 National Health and Nutrition Examination Survey (NHANES). Single-metal and multimetal multivariable logistic regression models, quantile G-computation, and Bayesian kernel machine regression models (BKMR) were fitted to explore the individual and joint associations of whole blood metals [lead (Pb), cadmium (Cd), mercury (Hg), cobalt (Co), manganese (Mn), and selenium (Se)] with the odds of decreased estimated glomerular filtration rate (eGFR) and albuminuria. A decreased eGFR was defined as an eGFR ≤ 60 mL/min per 1.73 m2, and albuminuria was categorized as a urinary albumin-creatinine ratio (UACR) of ≥ 30.0 mg/g. The results from quantile G-computation and BKMR indicated positive associations between exposure to the metal mixture and the prevalence of decreased eGFR and albuminuria (all P values < 0.05). These positive associations were mainly driven by blood Co, Cd, and Pb. Furthermore, blood Mn was identified as an influential element contributing to an inverse correlation with kidney dysfunction within metal mixtures. Increasing blood Se levels were negatively associated with the prevalence of decreased eGFR and positively associated with albuminuria. In addition, a potential pairwise interaction between Mn-Co on decreased eGFR was identified by BKMR analysis. Findings from our study suggested a positive association between exposure to the whole blood metal mixture and decreased kidney function, with blood Co, Pb, and Cd being the main contributors to this association, while Mn demonstrated an inverse relationship with renal dysfunction. However, as our study was cross-sectional in nature, further prospective studies are warranted to better understand the individual and combined effects of metals on kidney function.

Manganese and Sleep Outcomes in United States Adults: Results from the 2017-2020 National Health and Nutrition Examination Survey (NHANES)

BACKGROUND

Manganese (Mn) is an essential micronutrient, but inadequate or excess Mn intake can have a detrimental impact on human health. Despite the essentiality, little is known about the relationship between Mn and sleep.

OBJECTIVE

This study aimed to examine the relationship between blood Mn concentrations and sleep outcomes in US adults.

METHODS

This cross-sectional study used data on blood Mn and sleep from the 2017-2020 National Health and Nutrition Examination Survey (NHANES) (n = 8356, age ≥18 y). Multivariable logistic regression was used to examine associations between quintiles of blood Mn concentrations and subjective sleep outcomes (short sleep duration, late sleep midpoint, trouble sleeping, and obstructive sleep apnea [OSA] symptoms), adjusting for age, gender, body mass index, race/ethnicity, income, smoking, inflammation-adjusted serum ferritin concentration (iron status), caffeine, and alcohol intake. Gender-stratified models were used due to interactions with gender.

RESULTS

The mean (SE) blood Mn concentration was 9.7 (0.1) μg/L in US adults. In males, a nonlinear association was noted in the relationship between blood Mn levels and short sleep duration on weekdays and weekends. The third Mn quintile (Q3) group had lower odds of short sleep duration (<7 h) on weekdays (odds ratio [OR]=0.6, 95% confidence interval [CI]: 0.4, 0.9) than the lowest Mn quintile (Q1, reference) after adjusting for covariates in males. The second Mn quintile (Q2) group had lower odds of late sleep midpoint on weekdays than Q1 (OR=0.6, 95% CI: 0.4, 0.8). In females, Q2 group had lower odds of OSA symptoms than Q1 (OR: 0.6, 95% CI: 0.4, 0.9). No relationship was noted between Mn and trouble sleeping.

CONCLUSIONS

Gender differences exist in the association between Mn and sleep in adults. Q1 group had the poorest sleep outcomes, including higher odds of short sleep duration (in males), late sleep midpoint (in males), and OSA symptoms (in females).

Exploring the association between two groups of metals with potentially opposing renal effects and renal function in middle-aged and older adults: Evidence from an explainable machine learning method

BACKGROUND

Machine learning models have promising applications in capturing the complex relationship between mixtures of exposures and outcomes.

OBJECTIVE

Our study aimed at introducing an explainable machine learning (EML) model to assess the association between metal mixtures with potentially opposing renal effects and renal function in middle-aged and older adults.

METHODS

This study extracted data from two cycle years of the National Health and Nutrition Examination Survey (NHANES). Participants aged 45 years or older with complete data on six metals (lead, cadmium, manganese, mercury, and selenium) and related covariates were enrolled. The EML model was developed by the optimized machine learning model together with Shapley Additive exPlanations (SHAP) to assess the chronic kidney disease (CKD) risk with metal mixtures. The results from EML were further compared in detail with multiple logistic regression (MLR) and Bayesian kernel machine regression (BKMR).

RESULTS

After adjusting for included covariates, MLR pointed out the lead and arsenic were generally positively associated with CKD, but manganese had a negative association. In the BKMR analysis, each metal was found to have a non-linear association with the risk of CKD, and interactions can exist between metals, especially for arsenic and lead. The EML ranked the feature importance: lead, manganese, arsenic and selenium were close behind in importance after gender, age or BMI for participants with CKD. Strong interactions between mercury and lead, manganese and cadmium and arsenic and manganese were identified by partial dependence plot (PDP) of SHAP and bivariate exposure-response effect plots of BKMR. The EML model determined the "trigger point" at which the risk of CKD abruptly changed.

CONCLUSION

Co-exposure to metals with different nephrotoxicity could have different joint association with renal function, and EML can be a powerful method for studying complex exposure mixtures.

Synergistic impact of co-exposures to whole blood metals on chronic kidney disease in general US adults: a cross‑sectional study of the National Health and Nutrition Examination Survey 2011-2020

The impact of exposure to metals on chronic kidney disease (CKD) has only been investigated in two-way or single metal interactions in previous studies. We investigated the associations between five single metals in blood and their mixed exposure and CKD by using the machine learning approach. Relevant data were extracted from the National Health and Nutrition Examination Survey (NHANES 2011-2020), and the level of five metals in blood detected by inductively coupled plasma mass spectrometry was considered as exposures, namely, cadmium (Cd), lead (Pb), total mercury (Hg), manganese (Mn), and selenium (Se). The correlations between individual metal and metal mixtures and CKD were then evaluated by survey-multivariable logistic regression (SMLR), generalized weighted quantile sum (WQS), and Bayesian kernel machine regression (BKMR). Altogether, our study included 12,412 participants representing 572.6 million non-institutionalized US adults. Several single metals with the high quartile of exposure showed a positive association with the CKD ratio including Cd [(AOR = 1.873, 95% CI: 1.537, 2.284), Q4], Pb [(AOR = 1.559, 95% CI: 1.295, 1.880), Q4], and total Hg [(AOR = 1.169, 95% CI: 1.018, 1.343), Q2], while Mn [(AOR = 0.796, 95% CI: 0.684, 0.927), Q2] and Se [(AOR = 0.805, 95% CI: 0.664, 0.976), Q4] were negatively associated with the CKD ratio. In light of the positive fit of the WQS regression model, a significantly positive correlation was found between mixed metals and CKD (AOR = 1.373, 95% CI: 1.224, 1.539) after full covariate adjustment, and a similar finding was also detected in the BKMR model. Our study revealed that each single metal including Cd, Pb, and total Hg might have a positive association with CKD while this association was negative for both Mn and Se. The five metals might have a positive joint effect on CKD.

Association and interactions between mixed exposure to trace elements and the prevalence of kidney stones: a study of NHANES 2017-2018

Background

The association between exposure to trace elements mixture and the prevalence of kidney stones and the interactions between elements are unclear. The aim of this study was to explore the association between exposure to trace elements mixture and the prevalence of kidney stones and the interactions between the elements.

Methods

A total of 1,244 participants (139 kidney stone formers and 1,105 non-stone former participants) in NHANES 2017-2018 were included. The exposure to trace elements was evaluated by measuring their concentration in urine samples. Three methods, Logistic regression, quantile-based g computation (qgcomp), and Bayesian kernel machine regression (BKMR), were used for analysis.

Results

According to the results from qgcomp and BKMR, a negative association was found between exposure to the 13 trace elements and the prevalence of kidney stones [OR = 0.50 (0.32, 0.78)]. Subgroup analysis revealed that Co, As, and iodine in the whole population, Co, As, and Ni in males, and Cs, iodine, and Sb in females, were most strongly associated with kidney stones. Kidney stone was found to be positively correlated with Co and negatively correlated with the other elements. Besides, there were significant interactions between Ni and Pb in the whole population, Co and iodine in males, and Pb and iodine in females.

Conclusion

There was a negative association between exposure to the mixture of 13 trace elements and the prevalence of kidney stones.

Association of blood manganese concentrations with 24-h based brachial and central blood pressure, and pulse-wave velocity

Potential environmental determinants of BP and hypertension in older adults are far less known than their lifestyle risk factors. Manganese (Mn) is an essential element for life that may induce changes in blood pressure (BP), but the direction of the association is unclear. We aimed to examine the association of blood manganese (bMn) with 24-h-based brachial, central BP (cBP), and pulse-wave velocity (PWV). With this purpose, we analyzed data from 1009 community-living adults aged >65 years without BP medication. bMn was measured using inductively-coupled plasma-mass spectrometry and 24-h BP with validated devices. The association of bMn (median: 6.77 μg/L; IQR: 5.59-8.27) with daytime brachial and central systolic (SBP) and with diastolic BP (DBP) was non-linear, with BP increases up to around the median of Mn and then stabilization or slight rightward decrease. Mean BP differences (95% confidence interval) comparing Mn Q2 to Q5 (vs Q1 quintile) for brachial daytime SBP were 2.56 (0.22; 4.90), 3.59 (1.22; 5.96), 3.14 (0.77; 5.51) and 1.72 (-0.68; 4.11) mmHg, respectively; and 2.22 (0.70, 3.73), 2.55 (1.01, 4.08), 2.45 (0.91; 3.98), and 1.68 (0.13; 3.24), respectively, for DBP. Daytime central-pressures showed a similar dose-response relationship with bMn as daytime brachial-pressures. The association with nighttime BP was linearly positive for brachial BPs, and only increasing for Q5 for cBP. Regarding PWV, a tendency to significant linear increase along bMn levels was observed (p-trend = 0.042). The present findings extend the scarce evidence on the association between Mn and brachial BP to 2 other vascular parameters, suggesting Mn levels as a candidate risk factor for increasing levels of both brachial and cBPs in older adults, yet further research is needed with larger cohort studies in adults at all age ranges.

Exposure to multiple metals and diabetes mellitus risk in dong ethnicity in China: from the China multi-ethnic cohort study

Metals play an important role in the development of diabetes mellitus (DM). The association of metals with diabetes among the Dong ethnicity in China remains poorly understood. The current study aimed to evaluate the association of single metal exposure and multi-metal co-exposure with DM risk. Urinary concentrations of arsenic, cadmium, chromium, copper, iron, lead, manganese, mercury, molybdenum, nickel, strontium, vanadium, and zinc were measured using inductively coupled plasma-mass spectrometry (ICP-MS) among 4479 Dong ethnic participants aged 30-79 years from the China Multi-Ethnic Cohort (CMEC) study. Based on tertiles, the metal exposure can be divided into three groups: low, middle, and high exposure. Multivariate logistic regression models and principal component analysis were performed to determine exposure to single-metal and multi-metal co-exposure in relation to DM. A decrease in risk of DM was associated with iron (OR = 0.78, 95% CI: 0.61-1.00 and 0.68, 0.53-0.88 for the middle and high vs. low) and strontium (OR = 0.87, 95% CI: 0.69-1.12 and 0.67, 0.51-0.86 for the middle and high vs. low), respectively. A principal component 3 (PC3) characterized by iron and strontium showed an inverse association with DM. A principal component 4 (PC4) characterized by manganese and lead positively associated with DM. Exposure to high concentrations of urinary iron and strontium may reduce the risk of diabetes mellitus. This study revealed an increase in the risk of diabetes mellitus by co-exposure to high concentrations of urinary manganese and lead.

Sex-Specific Associations of Urinary Metals with Renal Function: a Cross-sectional Study in China

BACKGROUND

Extensive studies have revealed the link between heavy metals and CKD. Compared to single meta-elements, mixture of metals reflect real-life metals exposure scenarios and are of interest. However, the mechanism of action of metal mixture on renal function is unclear.

METHODS

This study aimed to explore the potential relationship between urinary arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and chromium (Cr) contents with estimated glomerular filtration rate (eGFR) levels in 2775 participants. The levels of metals in urine were determined by inductively coupled plasma-mass spectrometry. We used linear regression models and the Bayesian kernel machine regression (BKMR) to evaluate the association between metals and eGFR levels.

RESULTS

In linear regression analysis, urinary As (β = 2.723, 95%CI: 0.29, 5.157) and Pb (β = 3.081, 95%CI: 1.725, 4.438) were positively associated with eGFR in the total population. In the BKMR model, a mixture of the five metals had a positive joint effect on eGFR levels, while Pb (PIP = 0.996) contributed the most to eGFR levels. Pb was positively associated with eGFR levels in the total participants and women. As was positively correlated with eGFR levels in women. Pb and eGFR levels were positively correlated when the other metals were set at 25th, 50th, and 75th percentiles.

CONCLUSIONS

To the best of our knowledge, all five metals mixed exposure was positively associated with eGFR. Pb showed more important effects than the other four metals in the mixture, especially in women.

Sex-specific and dose-response relationships of urinary cobalt and molybdenum levels with glucose levels and insulin resistance in U.S. adults

Growing studies have linked metal exposure to diabetes risk. However, these studies had inconsistent results. We used a multiple linear regression model to investigate the sex-specific and dose-response associations between urinary metals (cobalt (Co) and molybdenum (Mo)) and diabetes-related indicators (fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), homeostasis model assessment for insulin resistance (HOMA-IR), and insulin) in a cross-sectional study based on the United States National Health and Nutrition Examination Survey. The urinary metal concentrations of 1423 eligible individuals were stratified on the basis of the quartile distribution. Our results showed that the urinary Co level in males at the fourth quartile (Q4) was strongly correlated with increased FPG (β = 0.61, 95% CI: 0.17-1.04), HbA1c (β = 0.31, 95% CI: 0.09-0.54), insulin (β = 8.18, 95% CI: 2.84-13.52), and HOMA-IR (β = 3.42, 95% CI: 1.40-5.44) when compared with first quartile (Q1). High urinary Mo levels (Q4 vs. Q1) were associated with elevated FPG (β = 0.46, 95% CI: 0.17-0.75) and HbA1c (β = 0.27, 95% CI: 0.11-0.42) in the overall population. Positive linear dose-response associations were observed between urinary Co and insulin (P_nonlinear = 0.513) and HOMA-IR (P_nonlinear = 0.736) in males, as well as a positive linear dose-response relationship between urinary Mo and FPG (P_nonlinear = 0.826) and HbA1c (P_nonlinear = 0.376) in the overall population. Significant sex-specific and dose-response relationships were observed between urinary metals (Co and Mo) and diabetes-related indicators, and the potential mechanisms should be further investigated.

Joint Effect of Multiple Metals on Hyperuricemia and Their Interaction with Obesity: A Community-Based Cross-Sectional Study in China

Metal exposures have been inconsistently related to the risk of hyperuricemia, and limited research has investigated the interaction between obesity and metals in hyperuricemia. To explore their associations and interaction effects, 3300 participants were enrolled from 11 districts within 1 province in China, and the blood concentrations of 13 metals were measured to assess internal exposure. Multivariable logistic regression, restricted cubic spline (RCS), Bayesian kernel machine regression (BKMR), and interaction analysis were applied in the single- and multi-metal models. In single-metal models, five metals (V, Cr, Mn, Co, and Zn) were positively associated with hyperuricemia in males, but V was negatively associated with hyperuricemia in females. Following the multi-metal logistic regression, the multivariate-adjusted odds ratios (95% confidence intervals) of hyperuricemia were 1.7 (1.18, 2.45) for Cr and 1.76 (1.26, 2.46) for Co in males, and 0.68 (0.47, 0.99) for V in females. For V and Co, RCS models revealed wavy and inverted V-shaped negative associations with female hyperuricemia risk. The BKMR models showed a significant joint effect of multiple metals on hyperuricemia when the concentrations of five metals were at or above their 55th percentile compared to their median values, and V, Cr, Mn, and Co were major contributors to the combined effect. A potential interaction between Cr and obesity and Zn and obesity in increasing the risk of hyperuricemia was observed. Our results suggest that higher levels of Cr and Co may increase male hyperuricemia risk, while higher levels of V may decrease female hyperuricemia risk. Therefore, the management of metal exposure in the environment and diet should be improved to prevent hyperuricemia.

Trends in elevated waist-to-height ratio and waist circumference in U.S. adults and their associations with cardiometabolic diseases and cancer, 1999-2018

Introduction

Although waist-to-height ratio (WHtR) has established association with cardiometabolic disease, the trend of changes in elevated WHtR among general population have not been examined adequately.

Methods

This study examined the prevalence of elevated WHtR and waist circumference (WC) and their trends over time using Joinpoint regression models among adults who participated in the United States National Health and Nutrition Examination Survey (U.S. NHANES) 1999-2018. We performed weighted logistic regression to identify the association between central obesity subtypes and the prevalence of comorbidities, including diabetes, chronic kidney disease, hypertension, cardiovascular disease, and cancer.

Results

The prevalence of elevated WHtR has increased from 74.8% in 1999-2000 to 82.7% in 2017-2018 while elevated WC also increased from 46.9% in 1999-2000 to 60.3% in 2017-2018. Men, older adults, former smokers, and people with lower education levels were more likely to have elevated WHtR. A total of 25.5% of American adults had normal WC but elevated WHtR, and they had a significantly higher chance of suffering from diabetes (odds ratio [OR] = 2.06 [1.66, 2.55]), hypertension (OR = 1.75 [1.58, 1.93]) and CVD (OR = 1.32 [1.11, 1.57]).

Discussion

In conclusion, the burden of elevated WHtR and WC have been increasing among U.S. adults throughout the years, and the changes have been more significant across most subgroups. It is also notable that approximately a quarter of the population had normal WC but elevated WHtR, which had increased likelihood of having cardiometabolic diseases, especially diabetes. Future clinical practices should pay more attention to this subgroup of the population with overlooked health risks.

Single and combined associations of blood lead and essential metals with serum lipid profiles in community-dwelling adults

Background

Although several studies have examined the relationships between lead (Pb) exposure and serum lipid profiles, the associations of the metal mixture, including lead (Pb) and essential metals with lipid profiles, remain unclear.

Objective

To investigate the associations of the metal mixture including Pb and essential metals [magnesium (Mg), manganese (Mn), copper (Cu), iron (Fe), zinc (Zn), and calcium (Ca)] with serum lipid profiles [total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C)], as well as the potential interactions among the metals.

Methods

Nine hundred and ninety-eight Chinese community-dwelling adults completed a questionnaire and underwent checkups of anthropometric parameters, serum lipid profile levels (TC, TG, LDL-C, and HDL-C), and blood metal concentrations (Pb, Mg, Mn, Cu, Fe, Zn, and Ca). The multivariable linear regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) were applied to evaluate the single and combined associations of blood Pb and essential metals with serum lipid profiles.

Results

In the multivariable linear regression model, the blood Pb was positively associated with TC, LDL-C, and HDL-C (p < 0.05, all), and the blood Mg were positively associated with serum TC, LDL-C, and Ln TG (p < 0.05, all). In the WQS regression and BKMR models, the metal mixture of blood Pb and the essential metals was positively associated with all of the serum lipid profiles. In addition, an inverse U-shaped association of Pb with Ln TG and the positive interactive effect between blood Pb and Mg levels on TC and LDL-C were found.

Conclusion

The levels of blood Pb, together with the essential metals, especially Mg levels, are suggested to be considered when assessing dyslipidemia risk. However, more evidence is still needed to validate the conclusions.

Sex-specific associations of the urinary fourteen-metal mixture with NAFLD and liver fibrosis among US adults: A nationally representative study

Although previous studies have examined the hepatotoxicity of single metal exposure, the associations between metal mixture and non-alcoholic fatty liver disease (NAFLD) or fibrosis remain unclear. This study investigated the associations of urinary metal mixture with the risks of NAFLD and liver fibrosis in US adults using data from the National Health and Nutrition Examination Survey (NHANES) from 2017.01 to 2020.03. Vibration-controlled transient elastography was used to detect the controlled attenuation parameter (CAP) and liver stiffness measurement (LSM), which are indicators of NAFLD and liver fibrosis respectively. Three novel mixture modeling approaches including the Bayesian kernel machine regression (BKMR), weighted quantile sum (WQS) regression and quantile g-computation (qgcomp) were used to estimate the associations of the urinary fourteen-metal mixture with Ln CAP and Ln LSM. There were 2283 adults aged over 18 years (1209 women and 1074 men) were included. Among women, urinary metal mixture was positively associated with Ln CAP in the BKMR and qgcomp models (both P < 0.05). However, no significantly associations of urinary metal mixture with Ln CAP were observed among men in all models (all P > 0.05). The metal mixture was not associated with Ln LSM in the three models regardless of genders (all P > 0.05). In conclusion, we observed sex-specific associations between urinary metal mixture and the prevalence of NAFLD in US adults. These findings emphasize the role of environmental heavy metal exposure in the development of NAFLD, and confirm the need for more prospective cohort studies on sex-specific manner.

Association of organophosphate ester exposure with cardiovascular disease among US adults: Cross-sectional findings from the 2011-2018 National Health and Nutrition Examination Survey

Organophosphate esters (OPEs) are widely used as flame retardants and plasticizers worldwide. Therefore, the potentially deleterious effect of OPE on human beings deserves extensive attention. The primary objective of this present study was to untangle the relationship between OPE exposure and cardiovascular disease (CVD) among general population. Detailed information about participants' baseline characteristics, involving socioeconomic data, demographic data and key covariates was obtained from National Health and Nutrition Examination Survey (NHANES) 2011-2018. Multivariate logistic regression models with adjustment for prior-determined covariates were utilized to examine the relationship between various OPEs and CVD among US adults and calculate odd ratios (ORs) and corresponding confidence intervals (CIs). Two multi-pollutant statistical strategies (weighted quantile sum regression and Bayesian kernel machine regression) were employed to investigate the joint effect of OPE mixture on CVD. A total of 5067 participants were included in this study. In completely-adjusted logistic model, the highest tertiles of OPE metabolites were positively associated with CVD risk, while the relationships did not reach statistical significance. The weighted quantile sum (WQS) index was significantly correlated with increased prevalence of CVD (adjusted OR: 1.25; CI: 1.02, 1.53, p value = 0.032) and Diphenyl phosphate (DPHP) was the greatest contributor (31.38%). The BKMR also indicated that mixed OPE exposure associated with an increased risk of CVD. Taken together, the present study demonstrated that there were possible links between OPE exposures and increased risk of CVD, while the relationships did not reach statistical significance. Our study provided the suggestive evidence that cumulative effect of OPE mixtures on CVD. DPHP may be a major driver of this positive association. Given the limitation of cross-sectional design and relatively limited kinds of OPE metabolites, further studies are warranted to longitudinally evaluate the potential effect of a wider range of OPEs on CVD or cardiac metabolism.

Associations of serum perfluoroalkyl substances with concentrations of blood manganese and selenium

The aim of this study was to estimate the associations of blood manganese and selenium with serum concentrations of selected perfluoroalkyl substances (PFAS). The presence or absence of this association is important because PFAS have documented pro-oxidant properties, whereas manganese and selenium are critical to antioxidant responses. For this purpose, the data from NHANES for US adults aged ≥ 20 years (N = 3982), adolescents aged 12-19 years (N = 1524), and children aged 3-11 years (N = 639) were analyzed. Among adults, concentrations of blood manganese were found to be inversely associated with serum concentrations of perfluorooctanoic acid or PFOA (β =  - 0.04204, p < 0.01), perfluorononanoic acid or PFNA (β =  - 0.02700, p < 0.01), perfluorohexane sulfonate or PFHxS (β =  - 0.04306, p < 0.01), and perfluorooctane sulfonate or PFOS (β =  - 0.04494, p < 0.01). Blood concentrations of selenium were found to be positively associated with PFHxS only among adults (β = 0.000678, p = 0.047) and adolescents (β = 0.01377, p = 0.02). The Mn results but not the less consistent Se associations were robust to adjustments for serum albumin. Possible reasons for the inverse association of PFOA, PFHxS, PFNA, and PFOS with Mn among US adults are discussed. The finding raises concerns about manganese's diminished ability to mount antioxidant responses to PFAS exposure.

A Longitudinal Study of Exposure to Manganese and Incidence of Metabolic Syndrome

The association between manganese (Mn) and metabolic syndrome (MetS) is unclear, and no prior study has studied this association longitudinally. The aim of this study was to assess longitudinal associations of Mn exposure with MetS and metabolic outcomes. We used data from the San Luis Valley Diabetes Study (SLVDS), a prospective cohort from rural Colorado with data collected from 1984−1998 (n = 1478). Urinary Mn was measured at baseline (range = 0.20−42.5 µg/L). We assessed the shape of the cross-sectional association between Mn and MetS accounting for effect modification by other metals at baseline using Bayesian kernel machine regression. We assessed longitudinal associations between baseline quartiles of Mn and incident MetS using Fine and Gray competing risks regression models (competing risk = mortality) and between quartiles of Mn and metabolic outcomes using linear mixed effects models. We did not observe evidence that quartiles of Mn were associated with incident MetS (p-value for trend = 0.52). Quartiles of Mn were significantly associated with lower fasting glucose (p-value for trend < 0.01). Lead was found to be a possible effect modifier of the association between Mn and incident MetS. Mn was associated with lower fasting glucose in this rural population. Our results support a possible beneficial effect of Mn on diabetic markers.

Cross-Sectional Association of Blood Selenium with Glycemic Biomarkers among U.S. Adults with Normoglycemia in the National Health and Nutrition Examination Survey 2013–2016

Selenium (Se) remains to have an inconsistent relationship with glycemic biomarkers and the risk of developing type 2 diabetes (T2D). Few studies have investigated the relationship between blood Se and glycemic biomarkers among people with normoglycemia. We conducted a cross-sectional analysis using the U.S. National Health and Nutrition Examination Survey 2013–2016. Multivariable linear regression models were developed to examine the associations of blood Se with glycemic biomarkers, namely, fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), insulin, and the oral glucose tolerance test (OGTT). Blood Se was treated as continuous (per log-10 increment) and categorical exposure (in quartiles) in separate regression models. We assessed the dose–response relationships by restricted cubic spline analysis. After excluding the participants with T2D or incomplete data, 2706 participants were analyzed. The highest quartile of blood Se was associated with increased FPG [adjusted β = 0.12, 95% Confidence Intervals (CI) = 0.04, 0.20], OGTT (adjusted β = 0.29, 95% CI = 0.02, 0.56), HbA1c (adjusted β = 0.04, 95% CI = 0.00, 0.07), and insulin (adjusted β = 2.50, 95% CI = 1.05, 3.95) compared with the lowest quartile. Positive associations were also observed between every log-10 increment of blood Se level and glycemic biomarkers, except for OGTT. A positive linear dose–response relationship existed between blood Se and FPG (P_overall = 0.003, P_nonlinear = 0.073) and insulin (P_overall = 0.004, P_nonlinear =0.060). BMI, age, and smoking status modified the associations of the highest quartile of Se (compared with the lowest quartile) with glycemic biomarkers. Overall, positive associations of blood Se with glycemic biomarkers were observed among U.S. adults with normoglycemia. These findings implied that people with normoglycemia need to be aware of the level of Se and other mineral intakes from diet and supplements. Further research is required to identify the mechanisms of excess Se in the progression of diabetes.

Joint Associations of Food Groups with All-Cause and Cause-Specific Mortality in the Mr. OS and Ms. OS Study: A Prospective Cohort

Despite continuous growth in dietary pattern research, the relative importance of each dietary component in the overall pattern and their joint effects on mortality risk have not been examined adequately. We explored the individual and joint associations of multiple food groups with all-cause and cause-specific mortality (cardiovascular disease (CVD) or cancer), by analyzing data from a cohort of 3995 Hong Kong Chinese older adults in the Mr. Osteoporosis (OS) and Ms. OS Study. Cox proportional hazards models were used to examine the associations of food groups with mortality risk. The individual and joint contribution of food groups to mortality risk has been quantified by a machine learning approach, i.e., the Quantile G-Computation. When comparing the highest with the lowest quartile of intake, dark green and leafy vegetables (hazard ratio (HR) = 0.82, 95% confidence interval (CI) = 0.70 to 0.96, Ptrend = 0.049), fruit (HR = 0.79, 95% CI = 0.68 to 0.93, Ptrend = 0.006), legumes (HR = 0.75, 95% CI = 0.63 to 0.87, Ptrend = 0.052), mushroom and fungi (HR = 0.76, 95% CI = 0.65 to 0.88, Ptrend = 0.023), soy and soy products (HR = 0.77, 95% CI = 0.66 to 0.90, Ptrend = 0.143), and whole grains (HR = 0.76, 95% CI = 0.65 to 0.89, Ptrend = 0.008) were inversely associated with all-cause mortality. Legume intake was associated with a lower risk of CVD mortality, while fruit, nuts, soy and soy products were associated with a lower risk of cancer mortality. From the Quantile G-Computation, whole grains, legumes, fruits, mushroom and fungi, soy and soy products had a higher relative weighting on mortality risk, and the joint effect of food groups was inversely associated with the mortality risk due to all-causes (HR = 0.39, 95% CI = 0.27 to 0.55), CVD (HR = 0.78, 95% CI = 0.67 to 0.91), and cancer (HR = 0.31, 95% CI = 0.15 to 0.65). From a sex-stratified analysis, most associations between food groups (whole grains, legumes, fruits, mushroom and fungi, soy and soy products) and mortality risk remained significant among men. In conclusion, whole grains, legumes, fruits, mushroom and fungi, soy and soy products were the main contributors to a reduction in mortality risk, and their joint effects were stronger than individual food groups. Moreover, the sex-specific association of sweets and desserts with cancer mortality may be worth further investigation.

Co-exposure to perfluoroalkyl acids and heavy metals mixtures associated with impaired kidney function in adults: A community-based population study in China

BACKGROUND

Previous studies have separately linked either perfluoroalkyl acid (PFAA) or heavy metal exposure with kidney dysfunction. However, the relationships of co-exposure to PFAAs and heavy metals with kidney function are still unclear.

OBJECTIVES

To explore the associations between exposure to PFAAs and heavy metals mixtures and kidney function in adults.

METHODS

We conducted a cross-sectional community-based population study in Guangzhou, China, enrolling 1312 adults from November 2018 to August 2019. We quantified 13 PFAAs in serum and 14 heavy metals in plasma. We chose estimated glomerular filtration rate (eGFR) and chronic kidney disease (CKD) as outcomes of interest. Distributed lag non-linear models (DLNMs) were used to check nonlinearity of individual pollutant with kidney function. Joint associations of pollutant mixtures on kidney function were assessed by Bayesian Kernel Machine Regression (BKMR) models. We further explored modification effects of gender.

RESULTS

Most individual PFAA and heavy metal were associated with declined kidney function in single-pollutant models. We also observed significant dose-response relationships of pollutant mixtures with reduced eGFR levels and increased odds of CKD in BKMR models. Perfluoroheptanesulfonic acid (PFHpS), arsenic (As) and strontium (Sr) were the predominant contributors among pollutant mixtures. A change in log PFHpS, As and Sr concentrations from the 25th to the 75th percentile were associated with a decrease in eGFR of -5.42 (95% confidence interval (CI): -6.86, -3.98), -2.14 (95% CI: -3.70, -0.58) and -1.87 (95% CI: -3.03, -0.72) mL/min/1.73 m², respectively, when other pollutants were at their median values. In addition, the observed associations were more obvious in females.

CONCLUSIONS

We provided new evidence that co-exposure to PFAAs and heavy metals mixtures was associated with reduced kidney function in adults and PFHpS, As and Sr appeared to be the major contributors. Further studies are warranted to confirm our findings and elucidate the underlying mechanisms.

Association between serum manganese levels and diabetes in chinese adults with hypertension

Manganese (Mn) is an essential trace metal element that is associated with diabetes; however, the results of previous studies are inconsistent. Furthermore, few studies have been conducted in a hypertensive population. The purpose of this study is to explore the relationship between manganese and diabetes in a population with hypertension. A cross‐sectional study was conducted, including 2575 hypertensive individuals from 14 provinces in China. Serum manganese concentrations were measured by the inductively coupled plasma mass spectrometry (ICP‐MS) method. And logistic regression models were used to analyze the association between serum manganese and the risk of diabetes. The prevalence of diabetes was 27.0% in this hypertensive population. In logistic regression models, the odds ratios (95% confidence interval) for diabetes in tertile subgroups were 1.40 (1.12, 1.76) and 1.32 (1.05, 1.65) for tertiles 1 and tertiles 3, respectively, compared to tertile 2 (reference). Additionally, an interaction between sex and manganese was observed. The odds ratios (95% confidence interval) for diabetes were 1.29 (0.95, 1.75) and 0.96 (0.70, 1.31) for tertiles 1 and tertiles 3 among males, and 1.44 (1.01, 2.04) and 1.81 (1.29, 2.55) for tertiles 1 and tertiles 3 among females, respectively, compared to tertile 2. In conclusion, a U‐shaped association between serum manganese and diabetes was observed in a Chinese population with hypertension, and the association was modified by sex.

Identifying Effects of Urinary Metals on Type 2 Diabetes in U.S. Adults: Cross-Sectional Analysis of National Health and Nutrition Examination Survey 2011-2016

Growing evidence supports the associations of metal exposures with risk of type 2 diabetes (T2D), but the methodological limitations overlook the complexity of relationships within the metal mixtures. We identified and estimated the single and combined effects of urinary metals and their interactions with prevalence of T2D among 3078 participants in the NHANES 2011-2016. We analyzed 15 urinary metals and identified eight metals by elastic-net regression model for further analysis of the prevalence of T2D. Bayesian kernel machine regression and the weighted quantile sum (WQS) regression models identified four metals that had greater importance in T2D, namely cobalt (Co), tin (Sn), uranium (U) and strontium (Sr). The overall OR of T2D was 1.05 (95% CI: 1.01-1.08) for the positive effects and 1.00 (95% CI: 0.98-1.02) for the negative effect in the WQS models. We observed positive (Poverall = 0.008 and Pnon-linear = 0.100 for Co, Poverall = 0.011 and Pnon-linear = 0.138 for Sn) and inverse (Poverall = 0.001, Pnon-linear = 0.209 for Sr) linear dose-response relationships with T2D by restricted cubic spline analysis. Both additive and multiplicative interactions were found in urinary Sn and Sr. In conclusion, urinary Co, Sn, U and Sr played important roles in the development of T2D. The levels of Sn might modify the effect of Sr on T2D risk.

Trends in Urinary and Blood Cadmium Levels in U.S. Adults with or without Comorbidities, 1999-2018

Although cadmium (Cd) exposure has been declining in the United States (U.S.) over the years, the level of exposure for people with pre-existing comorbidities is unclear. This study characterized the trends of blood Cd levels (bCd) (n = 44,498) and urinary Cd levels (uCd) (n = 15,107) by pre-existing comorbidities among adults participating in the U.S. National Health and Nutrition Examination Survey. We calculated age- and sex-standardized annual geometric mean (GM) levels, and used aJoinpoint regression model to examine the trends over time. The GM levels of bCd declined from 1999–2000 to 2017–2018 survey cycles (from 0.49 to 0.33 μg/L), while women and current smokers had higher levels. Participants with comorbidities had higher bCd and declined over time: cardiovascular disease (CVD) (0.50 to 0.42 μg/L), hypertension (0.49 to 0.35 μg/L), chronic kidney disease (CKD) (0.54 to 0.37 μg), and cancer (0.57 to 0.38 μg) versus those without these comorbidities. We observed the similar pattern of changes for uCd and participants with CVD, CKD, and cancer had higher levels. To conclude, the trend in urinary and blood Cd levels in U.S adults decreased in the past 20 years, and the levels varied by sex, smoking status, and comorbidities.

Associations between multiple heavy metals exposure and glycated hemoglobin in a Chinese population

BACKGROUND

Heavy metals may play an important role as environmental risk factors in diabetes mellitus. This study aimed to explore the association of HbA1c with As, Cd, Cu, Ni, Pb, and Zn in single-metal exposure and multi-metal co-exposure models.

METHODS

A cross-sectional study involving 3472 participants was conducted. Plasma concentrations of heavy metals were determined by inductively coupled plasma mass spectrometry. We estimated the association of each metal with HbA1c by linear regression. Potential heterogeneities by sex, age, and smoking were investigated, and metal mixtures and interactions were assessed by the Bayesian kernel machine regression (BKMR).

RESULTS

In linear regression, Cu (β = 0.324, p < 0.05) and Ni (β = -0.19, p < 0.05) showed significant association with HbA1c in all participants. In BKMR analyses, all exposure-response relationships were approximately linear. Cu was significantly and positively associated with HbA1c levels in overall participants, women, participants aged 60 years old and above, and nonsmokers. Ni was significantly and negatively associated with HbA1c levels in overall participants. We did not observe the overall effect of plasma metal mixtures on HbA1c or the interaction effect of the metals on HbA1c.

CONCLUSION

Cu was positively correlated with HbA1c, whereas Ni was negatively correlated with HbA1c, when evaluated individually or in a metal mixture. Additional studies are necessary to confirm these correlations and to control for exposure to different metals in the general population.

The associations between urinary metals and metal mixtures and kidney function in Chinese community-dwelling older adults with diabetes mellitus

BACKGROUND

Previous studies have found associations between single toxic metals, such as arsenic and cadmium, and kidney function in adults with diabetes. However, studies with regards to other metals and metal mixtures are still limited.

OBJECTIVE

Our study aimed to investigate the associations between urinary concentrations of 5 selected metals and metal mixtures and kidney function using a sample of older adults with diabetes mellitus in Chinese communities.

METHODS

In a sample of older adults (n = 5186), 592 eligible subjects were included in this study. Urinary concentrations of 5 metals, i.e., arsenic (As), cadmium (Cd), vanadium (V), cobalt (Co), and thallium (Tl), were measured by inductively coupled plasma mass spectrometer (ICP-MS). Estimated glomerular filtration rate (eGFR) was calculated and dichotomized into indicator of chronic kidney disease (CKD). Logistic analysis and Bayesian kernel machine regression (BKMR) were used to explore the associations between single metals and metal mixtures and CKD, respectively.

RESULTS

Urinary levels of As and V were positively correlated with CKD (OR=2.37, 95% CI: 1.31-4.30 for As; OR=2.24, 95% CI: 1.25-4.03 for V), when compared the 4th quartile with the 1st quartile. After adjustment for potential confounders, the significant association between As and CKD still existed (OR=2.73, 95% CI: 1.23-6.07). BKMR analyses showed strong linear positive associations between As and V and CKD. Higher urinary levels of the mixture were significantly associated with higher odds of CKD in a dose-response pattern. As and V showed the highest posterior inclusion probabilities.

CONCLUSION

Urine As and V were positively associated with CKD in older adults with diabetes mellitus, separately and in a mixture. The metals mixture showed a linear dose-response association with the odds of CKD. The analyses of mixtures, rather than of single metals, may provide a real-world perspective on the relationship between metals and kidney function.

Associations of Habitual Mineral Intake with New-Onset Prediabetes/Diabetes after Acute Pancreatitis

Associations between habitual dietary intake of minerals and glucose metabolism have been extensively studied in relation to metabolic disorders. However, similar research has yet to be conducted in individuals after acute pancreatitis (AP). The main aim was to investigate the associations between habitual intake of 13 minerals and glycaemic status: new-onset prediabetes/diabetes after AP (NODAP), pre-existing prediabetes/type 2 diabetes (T2DM), and normoglycaemia after AP (NAP). Associations between the dietary intake of minerals and markers of glucose metabolism (glycated haemoglobin and fasting plasma glucose) were also studied. The EPIC-Norfolk food frequency questionnaire was used in a cross-sectional fashion to determine the habitual intake of 13 dietary minerals. ANCOVA as well as multiple linear regression analyses were conducted and five statistical models were built to adjust for covariates. The study included 106 individuals after AP. In the NODAP group, intake of 4 minerals was significantly less when compared with the NAP group: iron (B = -0.076, p = 0.013), nitrogen (B = -0.066, p = 0.003), phosphorous (B = -0.046, p = 0.006), and zinc (B = -0.078, p = 0.001). Glycated haemoglobin was significantly associated with iodine intake (B = 17.763, p = 0.032) and manganese intake (B = -17.147, p = 0.003) in the NODAP group. Fasting plasma glucose was significantly associated with manganese intake (B = -2.436, p = 0.027) in the NODAP group. Habitual intake of minerals differs between individuals with NODAP, T2DM, and NAP. Prospective longitudinal studies and randomised controlled trials are now warranted to further investigate the associations between mineral intake and NODAP.

Type 2 diabetes attributable to PM2.5: A global burden study from 1990 to 2019

BACKGROUND

Long-term exposure to fine particulate matter (PM_2.5) is associated with an increased risk of type 2 diabetes (T2D). However, limited data on trends in the global burden of T2D attributed to PM_2.5, particularly in different regions by social-economic levels. We evaluated the spatio-temporal changes in the disease burden of T2D attributed to PM_2.5 from 1990 to 2019 in 204 countries and regions with different socio-demographic indexes (SDI).

METHODS

This is a retrospective analysis with data from the Global Burden of Disease Study 2019 (GBD2019) database. The burden of T2D attributed to PM_2.5, age-standardized mortality rate (ASMR) and age-standardized disability-adjusted life year rate (ASDR) were estimated according to sex, age, nationality and SDI. The annual percentage change (APCs) and the average annual percentage change (AAPCs) were calculated by using the Joinpoint model to evaluate the changing trend of ASMR and ASDR attributed to PM_2.5 from 1990 to 2019. The Gaussian process regression model was used to estimate the relationship of SDI with ASMR and ASDR.

RESULTS

Overall, the global burden of T2D attributable to PM_2.5 increased significantly since 1990, particularly in the elderly, men, Africa, Asia and low-middle SDI regions. The ASMR and ASDR of T2D attributable to PM_2.5 in 2019 were 2.47 (95% CI: 1.71, 3.24) per 100,000 population and 108.98 (95% CI: 74.06, 147.23) per 100,000 population, respectively. From 1990 to 2019, the global ASMR and ASDR of T2D attributed to T2D increased by 57.32% and 86.75%, respectively. The global AAPCs of ASMR and ASDR were 1.57 (95% CI: 1.46, 1.68) and 2.17 (95% CI: 2.02, 2.32), respectively. Declining trends were observed in North America, South America, Europe, Australia, and other regions with high SDI.

CONCLUSIONS

Over this 30-years study, the global T2D burden attributable to PM_2.5 has increased particularly in regions with low-middle SDI. PM_2.5 remains a great concern on the global burden of diabetes.

Association of Manganese Biomarker Concentrations with Blood Pressure and Kidney Parameters among Healthy Adolescents: NHANES 2013-2018

Deficiency or excess exposure to manganese (Mn), an essential mineral, may have potentially adverse health effects. The kidneys are a major organ of Mn site-specific toxicity because of their unique role in filtration, metabolism, and excretion of xenobiotics. We hypothesized that Mn concentrations were associated with poorer blood pressure (BP) and kidney parameters such as estimated glomerular filtration rate (eGFR), blood urea nitrogen (BUN), and albumin creatinine ratio (ACR). We conducted a cross-sectional analysis of 1931 healthy U.S. adolescents aged 12-19 years participating in National Health and Nutrition Examination Survey cycles 2013-2014, 2015-2016, and 2017-2018. Blood and urine Mn concentrations were measured using inductively coupled plasma mass spectrometry. Systolic and diastolic BP were calculated as the average of available readings. eGFR was calculated from serum creatinine using the Bedside Schwartz equation. We performed multiple linear regression, adjusting for age, sex, body mass index, race/ethnicity, and poverty income ratio. We observed null relationships between blood Mn concentrations with eGFR, ACR, BUN, and BP. In a subset of 691 participants, we observed that a 10-fold increase in urine Mn was associated with a 16.4 mL/min higher eGFR (95% Confidence Interval: 11.1, 21.7). These exploratory findings should be interpreted cautiously and warrant investigation in longitudinal studies.

Associations between blood and urinary manganese with metabolic syndrome and its components: Cross-sectional analysis of National Health and Nutrition Examination Survey 2011-2016

Manganese (Mn) may improve cardiometabolic health with its anti-oxidative ability. However, epidemiological evidence on the overall and sex-specific relationship between Mn exposure and metabolic syndrome (MetS) has been inconclusive. We evaluated the associations of urinary (n = 1713) and blood (n = 3335) Mn levels with the prevalence of MetS, its components (elevated waist circumference, impaired glucose metabolism, elevated blood pressure and dyslipidemia) and sex-dependent heterogeneities among participants in the United States National Health and Nutrition Examination Survey 2011-2016. After adjusting for multiple covariates and the levels of other metals (Arsenic, Barium, Cadmium, Mercury, Molybdenum, Tin and Uranium), urinary Mn at the third quartile associated with a lower odd of MetS (odds ratio [OR] = 0.55, 95% confidence interval [C.I.] = 0.32-0.97), elevated waist circumference (OR = 0.56, 95% C.I. = 0.36-0.86) and elevated fasting plasma glucose (OR = 0.46, 95% C.I. = 0.27-0.76) among overall participants, and lower odds of MetS (OR = 0.40, 95% C.I. = 0.16-0.99), elevated waist circumference (OR = 0.39, 95% C.I. = 0.19-0.81) and elevated fasting plasma glucose (OR = 0.44, 95% C.I. = 0.22-0.90) among men. The U-shaped dose-response relationship between urinary Mn and MetS (P non-linear = 0.008) was observed among all participants. We did not observe the significant associations of blood Mn with the prevalence of MetS. Compared with other metals, urinary Mn played a less important role in development of MetS (posterior inclusion probabilities [PIP] = 0.49 for Mn versus 0.54 to 0.91 for other metals), but the contribution of blood Mn (PIP = 0.59 versus 0.60 to 0.61) was similar to other blood metals (Cadmium, Lead, Mercury and Selenium). These findings have provided new evidence of the potential roles of Mn in cardiometabolic health, and the needs to explore how Mn interacts with multiple metals in sex-specific manner.

Bioaccumulation of Toxic Metals in Children Exposed to Urban Pollution and to Cement Plant Emissions

Cement plants located in urban areas can increase health risk. Although children are particularly vulnerable, biomonitoring studies are lacking. Toenail concentration of 24 metals was measured in 366 children (6-10 years), who live and attend school in a city hosting a cement plant. Living addresses and schools were geocoded and attributed to exposed or control areas, according to modeled ground concentrations of PM10 generated by the cement plant. Air levels of PM10 and NO2 were monitored. PM10 levels were higher in the exposed, than in the control area. The highest mean PM10 concentration was recorded close to the cement plant. Conversely, the highest NO2 concentration was in the control area, where vehicular traffic and home heating were the prevalent sources of pollutants. Exposed children had higher concentrations of Nickel (Ni), Cadmium (Cd), Mercury (Hg), and Arsenic (As) than controls. These concentrations correlated each other, indicating a common source. Toenail Barium (Ba) concentration was higher in the control- than in the exposed area. The location of the attended school was a predictor of Cd, Hg, Ni, Ba concentrations, after adjusting for confounders. In conclusion, children living and attending school in an urban area exposed to cement plant emissions show a chronic bioaccumulation of toxic metals, and a significant exposure to PM10 pollution. Cement plants located in populous urban areas seem therefore harmful, and primary prevention policies to protect children health are needed.

Sex-specific associations of plasma metals and metal mixtures with glucose metabolism: An occupational population-based study in China

Studies with multi-pollutant approach on the relationships between multiple metals and fasting plasma glucose (FPG) are limited. Few studies are available on the potential sex-specific associations between metal exposures and glucose metabolism. We explored the associations between 22 plasma metals and FPG level among the 769 participants from the manganese-exposed workers healthy cohort in China. We applied a sparse partial least squares (sPLS) regression followed by ordinary least-squares regression to evaluate multi-pollutant association. Bayesian kernel machine regression (BKMR) model was used to deal with metal mixtures and evaluate their joint effects on FPG level. In the sPLS model, negative associations on FPG levels were observed for plasma iron (belta = -0.066), cobalt (belta = -0.075), barium (belta = -0.109), and positive associations for strontium (belta = 0.082), and selenium (belta = 0.057) in men, which overlapped with the results among the overall participants. Among women, plasma copper (belta = 0.112) and antimony (belta = 0.137) were positively associated with elevated FPG level. Plasma magnesium was negatively associated with FPG level in both sexes (belta = -0.071 in men and belta = -0.144 in women). The results of overlapped for plasma magnesium was selected as the significant contributor to decreasing FPG level in the multi-pollutant, single-metal, and multi-metal models. BKMR model showed a significantly negative over-all effect of six metal mixtures (magnesium, iron, cobalt, selenium, strontium and barium) on FPG level among the overall participants from all the metals fixed at 50th percentile. In summary, our findings underline the probable role of metals in glucose homeostasis with potential sex-dependent heterogeneities, and suggest more researches are needed to explore the sex-specific associations of metal exposures with risk of diabetes.