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

Association Between Combined Polymetallic Exposure and Osteoporosis

Combined polymetallic exposure may be an influential factor in osteoporosis. This study aimed to explore the association between polymetallic combined exposure and osteoporosis. A total of 2115 participants were included. Plasma concentrations of 22 metals were determined by inductively coupled plasma mass spectrometry. Osteoporosis was defined as a T ≤  - 2.5. The least absolute shrinkage and selection operator (LASSO) regression, binary logistics regression, and Bayesian kernel machine regression (BKMR) model were used to explore the association between plasma metals and osteoporosis. LASSO regression showed that 10 metals were associated with osteoporosis in the total population (magnesium, calcium, manganese, nickel, cobalt, arsenic, selenium, rubidium, cadmium, aluminum) and women (magnesium, calcium, molybdenum, nickel, cobalt, arsenic, selenium, rubidium, cadmium, aluminum), and four metals associated with men (magnesium, cobalt, aluminum, iron). Logistics regression showed that in total population, magnesium (ORQ3 = 0.653, 95% CI = 0.446-0.954) was negatively correlated with osteoporosis, while aluminum (ORQ2 = 1.569, 95% CI = 1.095-2.248, ORQ4 = 1.616, 95% CI = 1.109-2.354) and cadmium (ORQ4 = 1.989, 95% CI = 1.379-2.870) were positively correlated; in women, magnesium (ORQ3 = 0.579, 95% CI = 0.379-0.883) was negatively correlated with osteoporosis, while aluminum (ORQ2 = 1.563, 95% CI = 1.051-2.326, ORQ4 = 1.543, 95% CI = 1.024-2.326) and cadmium (ORQ3 = 1.482, 95% CI = 1.003-2.191, ORQ4 = 1.740, 95% CI = 1.167-2.596) were positively correlated. BKMR model showed that combined polymetallic exposure had an overall positive effect on osteoporosis, magnesium was negatively associated with osteoporosis, and cadmium, selenium, and aluminum were positively associated with osteoporosis. Metal mixtures in plasma were associated with osteoporosis risk. Magnesium may reduce the risk of osteoporosis, while cadmium, selenium, and aluminum may increase the risk of osteoporosis. Future studies needed to explore correlations and mechanisms.

Association between exposure to plasma mixture of essential and toxic elements and the lipid profile in institutionalized older adults

BACKGROUND

Older adults have a progressive deficiency in the ability to detoxify chemical elements and are susceptible to dyslipidemia and changes in glycemic control. The objective was to evaluate the association of the mixture of essential and toxic elements in the plasma of institutionalized older adults and test the associations with lipid profile variables and glycemic control.

METHODS

Data were obtained from 149 Brazilian older adults aged ≥60 living in nursing homes (NH) in Natal, Brazil. The concentrations of sixteen chemical elements in plasma and lipid profile parameters and glycemic control of 149 institutionalized older adults were measured. Bayesian kernel machine regression was used to estimate the associations of the mixture of chemical elements with total cholesterol (TC), high-density lipoprotein (HDL-c), low-density lipoprotein (LDL-c), triglycerides (TG), fasting glucose, and glycated hemoglobin.

RESULTS

Non-linear responses to exposure were observed for iron (Fe) about TC, LDL-c, and TG, and for barium (Ba) and copper (Cu) about TG. The concentration of the mixture of chemical elements below the 35th percentile was associated with a decrease in TC. Fe was the main element in the effect of the mixture associated with TC.

CONCLUSIONS

The lower concentrations of the mixture of chemical elements in plasma had a protective effect on the increase in TC, with Fe being the main element. Considering the results, the levels of essential and toxic elements in the plasma of older adults require extensive screening, mainly to prevent dyslipidemia and monitor clinical interventions.

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.

Metal mixture exposures and serum lipid levels in childhood: the Rhea mother-child cohort in Greece

BACKGROUND

Growing evidence suggests that cardiovascular disease develops over the lifetime, often beginning in childhood. Metal exposures have been associated with cardiovascular disease and important risk factors, including dyslipidemia, but prior studies have largely focused on adult populations and single metal exposures.

OBJECTIVE

To investigate the individual and joint impacts of multiple metal exposures on lipid levels during childhood.

METHODS

This cross-sectional study included 291 4-year-old children from the Rhea Cohort Study in Heraklion, Greece. Seven metals (manganese, cobalt, selenium, molybdenum, cadmium, mercury, and lead) were measured in whole blood using inductively coupled plasma mass spectrometry. Serum lipid levels included total cholesterol, triglycerides, high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol. To determine the joint and individual impacts of child metal exposures (log2-transformed) on lipid levels, Bayesian kernel machine regression (BKMR) was employed as the primary multi-pollutant approach. Potential effect modification by child sex and childhood environmental tobacco smoke exposure was also evaluated.

RESULTS

BKMR identified a positive association between the metal mixture and both total and LDL cholesterol. Of the seven metals examined, selenium (median 90.6 [IQR = 83.6, 96.5] µg/L) was assigned the highest posterior inclusion probability for both total and LDL cholesterol. A difference in LDL cholesterol of 8.22 mg/dL (95% CI = 1.85, 14.59) was observed when blood selenium was set to its 75th versus 25th percentile, holding all other metals at their median values. In stratified analyses, the positive association between selenium and LDL cholesterol was only observed among boys or among children exposed to environmental tobacco smoke during childhood.

IMPACT STATEMENT

Growing evidence indicates that cardiovascular events in adulthood are the consequence of the lifelong atherosclerotic process that begins in childhood. Therefore, public health interventions targeting childhood cardiovascular risk factors may have a particularly profound impact on reducing the burden of cardiovascular disease. Although growing evidence supports that both essential and nonessential metals contribute to cardiovascular disease and risk factors, such as dyslipidemia, prior studies have mainly focused on single metal exposures in adult populations. To address this research gap, the current study investigated the joint impacts of multiple metal exposures on lipid concentrations in early childhood.

Multimetal exposure: Challenges in diagnostics, prevention, and treatment

Extensive use of heavy metals has posed a serious concern for ecosystem and human too. Heavy metals are toxic in nature and their accumulation in human body causes serious disorders such as neurological disease, cardiac disease, gastrointestinal problems, skin disorders, reproductive disease, lungs diseases, and so on. Furthermore, heavy metals not only affect the human health but also have a negative impact on the economy. In the current review, we have elaborated the impact of heavy metal exposure on human health and socioeconomics. We have discussed the molecular mechanism involved in the heavy metal-induced human disorders such as oxidative stress, neuroinflammation, and protein misfolding. Finally, we discussed the preventive measure and treatment strategy that could counter the negative effects of heavy metal intoxications. In conclusion, there is a substantial correlation between heavy metals and the onset and advancement of several health issues. Chelation treatment could be a useful tactic to lessen the toxic metal load and the difficulties that come with it.

Type 2 diabetes attributable to ambient particulate matter pollution: a global burden study from 1990 to 2019

Background

This study assesses the changes over time and geographical locations in the disease burden of type 2 diabetes (T2D) attributed to ambient particulate matter pollution (APMP) from 1990 to 2019 in 204 countries and regions with different socio-demographic indexes (SDI).

Methods

The Global Burden of Diseases Study 2019 (GBD2019) database was used to analyze the global burden of T2D attributed to APMP. This study evaluated both the age-standardized death rate (ASDR) and disability-adjusted life years (DALYs) related to T2D, comparing data from 1990 to 2019. Estimated Annual Percentage Changes (EAPCs) were also utilized to investigate the trends over the 30-year study period.

Results

The global age-standardized DALY rate and ASDR exhibited an increasing trend, with an EAPC of 2.21 (95% CI: 2.15 to 2.27) and 1.50 (95% CI: 1.43 to 1.58), respectively. This rise was most notable among older adult populations, men, regions in Africa and Asia, as well as low-middle SDI regions. In 2019, the ASDR for T2D caused by APMP was recorded at 2.47 per 100,000 population, while the DALY rate stood at 108.98 per 100,000 population. Males and countries with middle SDI levels displayed significantly high age-standardized death and DALY rates, particularly noticeable in Southern Sub-Saharan Africa. Conversely, regions with high SDI levels like High-income North America demonstrated decreasing trends.

Conclusion

This study reveals a significant increase in T2D worldwide as a result of APMP from 1990 to 2019, with a particular emphasis on its impact on men, the older adult, and regions with low to middle SDI levels. These results underscore the urgent necessity for implementing policies aimed at addressing air pollution in order to reduce the prevalence of T2D, especially in the areas most heavily affected.

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.

Association of multiple serum minerals and vitamins with metabolic dysfunction-associated fatty liver disease in US adults: National Health and Nutrition Examination Survey 2017-2018

Background

Despite the rapid increase in the global prevalence of Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD), there are no approved therapeutic drugs for MAFLD yet. Nutrient supplementation might mitigate the risk of MAFLD. It is more typical for individuals to consume multiple nutrients simultaneously. However, the studies exploring the combined effects of multiple nutrients on MAFLD are limited. This study aimed to investigate the relationship between both individual nutrients and their combined influence on the risk of MAFLD.

Methods

Data were obtained from National Health and Nutrition Examination Survey (NHANES), and 18 types of nutrients were considered in this study. Logistic regression analysis was performed to evaluate the correlation between single nutrients and the risk of MAFLD. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was performed to pinpoint the most relevant nutrient associated with the risk of MAFLD. Subsequently, both Weighted Quantile Sum (WQS) regression and Quantile g-computation (Qgcomp) were used to assess the combined effects of multiple nutrients on the risk of MAFLD.

Results

A total of 3,069 participants were included in this study. LASSO regression analysis showed that Se, α-tocopherol, and γ-tocopherol exhibited a positive association with the risk of MAFLD. In contrast, the serum levels of Co, P, α-cryptoxanthin, LZ, and trans-β-carotene were inversely associated with the prevalence of MAFLD. When Se and two types of vitamin E were excluded, the WQS index showed a significant inverse relationship between the remaining 15 nutrients and the risk of MAFLD; α-cryptoxanthin showed the most substantial contribution. Similarly, Qgcomp suggested that the combined effects of these 15 nutrients were associated with a lower risk of MAFLD, with α-cryptoxanthin possessing the most significant negative weights.

Conclusion

This study suggested that the complex nutrients with either a low proportion of Se, α-tocopherol, and γ-tocopherol or without them should be recommended for patients with MAFLD to reduce its risk.

Maternal cobalt concentration and risk of spontaneous preterm birth: the role of fasting blood glucose and lipid profiles

Introduction

Spontaneous preterm birth (SPB) is a significant cause of neonatal mortality, yet its etiology remains unclear. Cobalt, an essential trace element, might be a risk factor for SPB. This study aims to investigate the relationship between maternal serum cobalt concentration and SPB, and to clarify the role of blood lipids and fasting blood glucose (FBG) in this relationship.

Methods

We conducted a nested case-control study within the Beijing Birth Cohort Study. Serum samples were obtained from 222 pregnant women with SPB and 224 controls during the first (7-13 weeks of pregnancy) and third trimesters (32-42 weeks of pregnancy). Serum cobalt concentration was determined using inductively coupled plasma mass spectrometry (ICP-MS). Fasting blood glucose and lipids levels were detected using a fully automated biochemical immunoassay instrument. Logistic regression models and linear regression models were established to explore the association between serum cobalt concentration and the risk of SPB in pregnant women, and to test the mediating effect of fasting blood glucose (FBG) and lipids.

Results

We found that the serum cobalt concentration in mothers with SPB and controls was similar in the first trimester, with values of 0.79 (0.58-1.10) ng/mL and 0.75 (0.51-1.07) ng/mL, respectively. However, in the third trimester, the cobalt concentration increased to 0.88 (0.59-1.14) ng/mL and 0.84 (0.52-1.19) ng/mL, respectively. In the logistic regression model, when considering the third trimester of pregnancy, after adjusting for ethnicity, pre-pregnancy body mass index (BMI), maternal age, education, income, and parity, it was observed that the medium level of cobalt concentration (0.63-1.07 ng/ml) had a negative correlation with the risk of SPB. The odds ratio (OR) was 0.56, with a 95% confidence interval of 0.34-0.90 ng/mL and a p-value of 0.02. This suggests that cobalt in this concentration range played a protective role against SPB. Additionally, it was found that FBG in the third trimester of pregnancy had a partial intermediary role, accounting for 9.12% of the association. However, no relationship between cobalt and SPB risk was found in the first trimester.

Conclusion

During the third trimester, intermediate levels of maternal cobalt appear to offer protection against SPB, with FBG playing a partial mediating role. To further clarify the optimal cobalt concentrations during pregnancy for different populations, a multi-center study with a larger sample size is necessary. Additionally, exploring the specific mechanism of FBG's mediating role could provide valuable insights for improving the prevention of SPB.

The Associations between Exposure to Multiple Heavy Metals and Total Immunoglobulin E in U.S. Adults

Immunoglobulin E (IgE) is a type of immunoglobulin, and elevated serum total IgE is often present in allergic diseases. Exposure to environmental heavy metals has been markedly linked to allergic diseases, leading to elevated total IgE levels. However, studies concerning the effects of multiple metal exposures on total IgE levels are limited. Therefore, the current study seeks to explore the correlation between heavy-metal co-exposure and total IgE levels based on the National Health and Nutrition Examination Survey (NHANES, 2005-2006). Participants possessed complete data on total IgE levels, 11 urinary metal concentrations and other covariates. The correlations between 11 metals and total IgE levels were analyzed using multiple linear regression, and total IgE levels were a continuous variable. Total IgE levels exceeding 150 kU/L were considered sensitized. Binary logistic regression analyses were employed to assess the correlation between metal exposure and the occurrence of an allergic state. Then, the association between co-exposure to the 11 metals and total IgE levels or the occurrence of sensitization status was further analyzed by Bayesian kernel machine regression (BKMR), a multi-contaminant model. There were 1429 adults with complete data included. Based on the median concentration, molybdenum (Mo) had the highest concentration (46.60 μg/L), followed by cesium (Cs), barium (Ba), lead (Pb), and mercury (Hg). And the median (interquartile range) for total IgE levels was 43.7 (17.3, 126.0) kU/L. Multiple linear regression results showed that Pb was significantly and positively associated with total IgE levels (β = 0.165; 95% CI: 0.046, 0.284). Binary logistic regression showed a significant positive correlation between urinary Pb (OR: 1.258; 95% CI: 1.052, 1.510) and tungsten (W) (OR: 1.251; 95% CI: 1.082, 1.447). Importantly, the BKMR model found a positive correlation between combined-metal exposure and total IgE levels and the occurrence of sensitization status. The mixed heavy-metal exposure was associated with increased total IgE levels, and this association may be driven primarily by the exposure of Pb and W. This study provides new insights into the relationship between heavy-metal exposure and allergic diseases. More research is needed to confirm these findings.

Associations between plasma metal/metalloid mixtures and the risk of central obesity: A prospective cohort study of Chinese adults

Central obesity has increased rapidly over the past decade and posed a substantial disease burden worldwide. Exposure to metals/metalloids has been acknowledged to be involved in the development of central obesity through regulation of cortisol, insulin resistance, and glucocorticoid receptor reduction. Despite the importance, it is lack of prospective study which comprehensively evaluate the relations between multiple metals exposure and central obesity. We explored the prospective associations of plasma metal concentrations with central obesity in a prospective study of the Dongfeng-Tongji cohort. The present study included 2127 participants with a 6.87-year mean follow-up duration. We measured 23 plasma metal/metalloid concentrations at baseline. The associations between metals and incident central obesity were examined utilizing the Cox proportional hazard regression in single and multiple metals models. Additionally, we applied elastic net (ENET), Bayesian kernel machine regression (BKMR), plasma metal score (PMS), and quantile-based g-computation (Qgcomp) models to explore the joint associations of metal mixtures with central obesity. After adjusting potential confounders, we found significant associations of plasma manganese (Mn) and thallium (Tl) concentrations with a higher risk of central obesity, whereas plasma rubidium (Rb) concentration was associated with a lower risk of central obesity both in single and multiple metals models (all FDR <0.05). The ENET and Qqcomp models verified similar metals (Mn, Rb, and Tl) as important predictors for central obesity. The results of both BKMR model and PMS suggested cumulative exposure to metal mixtures was associated with a higher risk of central obesity. Our findings suggested that co-exposure to metals was associated with a higher risk of central obesity. This study expands our knowledge that the management of metals/metalloids exposure may be beneficial for the prevention of new-onset central obesity, which may subsequently alleviate the disease burden of late-life health outcomes.

Associations of 10 trace element levels in the whole blood with risk of three types of obesity in the elderly

BACKGROUND

Currently, over 2 billion people worldwide suffer from obesity, which poses a serious health risk. More and more attention is being given to the effects of trace elements on obesity in recent years. Synergistic or antagonistic interactions among these elements can adversely or positively impact human health. However, epidemiological evidence on the relationship between trace element exposure levels and obesity has been inconclusive.

METHODS

Baseline data of 994 participants from the Cohort of Elderly Health and Environment Controllable Factors were used in the present study. ICP-MS was used to measure the concentrations of 10 trace elements in the whole blood of the older population. Binary logistic regression, restricted cubic splines (RCS) models, and Bayesian kernel machine regression (BKMR) models were employed to assess single, nonlinear, and mixed relationships between 10 trace element levels and three types of obesity based on body mass index (BMI), waist circumference (WC), and body fat percentage (BFP) in the elderly.

RESULTS

Based on BMI, WC and BFP, 51.8% of the included old population were defined as general overweight/obesity, 67.1% as abdominal obesity, and 36.2% as having slightly high/high BFP. After multivariable adjustment, compared with the lowest tertile, the highest tertile of blood selenium (Se) concentration was associated with an increased risk of all three types of obesity. Additionally, compared with the lowest tertile, higher tertiles of strontium (Sr) concentrations were associated with a lower risk of general overweight/obesity and having slightly high/high BFP, and the highest tertile of barium (Ba) was associated with a lower risk of having slightly high BFP, while higher tertiles of arsenic (As) concentrations were associated with an increased risk of having slightly high/high BFP, and the highest tertile of manganese (Mn) was associated with a higher risk of abdominal obesity. BKMR analyses showed a strong linear positive association between Se and three types of obesity. Higher blood levels of trace element mixture were associated with increased obesity risks in a dose-response pattern, with Se having the highest value of the posterior inclusion probability (PIP) within the mixture.

CONCLUSIONS

In this study, we found higher Se levels were associated with an elevated risk of obesity and high levels of Ba, Pb and Cr were associated with a decreased risk of obesity. Studies with larger samples are needed to confirm these findings.

The burden of ischemic heart disease attributable to ambient and household particulate matter pollution, 1990-2019: a global analysis

Elevated risk of ischemic heart disease (IHD) is associated with exposure to fine particulate matter. However, there is limited data on trends and comparisons in the global burden of IHD due to household air pollution from solid fuels (HAP) and ambient particulate matter pollution (APMP), particularly in regions of varying socio-economic levels. Based on the Global Burden of Disease Study 2019 (GBD 2019), we obtained age-standardized mortality rates (ASMR) and age-standardized disability-adjusted life years (ASDR) of IHD due to APMP and HAP from 1990 to 2019. Trends in the burden of IHD attributable to APMP and HAP during the period 1990 to 2019 were calculated by Joinpoint models. We estimated the relationship between ASMR with the socio-demographic indexes (SDI) and the health care accessibility and quality (HAQ) index by the Loess regression model. In 2019, the global burden of IHD ASMR attributed to APMP stabilized, but the most significant increases were observed in low-middle SDI regions. The global IHD ASMR attributed to APMP was 16.60 [95% Uncertainty Interval (UI), 13.61 to 19.44] per 100,000 population, with the highest APMP burden in middle SDI regions. From 1990 to 2019, the global ASMR for HAP-attributable IHD declined. The global ASMR of IHD attributable to HAP in 2019 was 6.30 (95% UI, 4.28 to 8.80) per 100,000 population, with the highest burden observed in the low SDI regions. From 1990 to 2019, the global burden of ASMR and ASDR of IHD attributable to APMP showed stabilization, whereas the HAP burden exhibited a decrease. There are a large burden of APMP particularly in middle SDI countries and a higher burden of HAP in low SDI countries. The burden of IHD due to APMP and HAP in men, the elderly, and populations in low, medium, and low SDI regions should be noticed.

The association between the essential metal mixture and fasting plasma glucose in Chinese community-dwelling elderly people

BACKGROUND

Epidemiological studies about the effect of essential metal mixture on fasting plasma glucose (FPG) levels among elderly people are sparse. The object of this study was to examine the associations of single essential metals and essential metal mixture with FPG levels in Chinese community-dwelling elderly people.

METHODS

The study recruited 2348 community-dwelling elderly people in total. Inductively coupled plasma-mass spectrometry was adopted to detect the levels of vanadium (V), selenium (Se), magnesium (Mg), cobalt (Co), calcium (Ca), and molybdenum (Mo) in urine. The relationships between single essential metals and essential metal mixture and FPG levels were evaluated by linear regression and Bayesian kernel machine regression (BKMR) models, respectively.

RESULTS

In multiple-metal linear regression models, urine V and Mg were negatively related to the FPG levels (β = - 0.016, 95 % CI: - 0.030 to - 0.003 for V; β = - 0.021, 95 % CI: - 0.033 to - 0.009 for Mg), and urine Se was positively related to the FPG levels (β = 0.024, 95 % CI: 0.014-0.034). In BKMR model, the significant relationships of Se and Mg with the FPG levels were also found. The essential metal mixture was negatively associated with FPG levels in a dose-response pattern, and Mg had the maximum posterior inclusion probability (PIP) value (PIP = 1.0000), followed by Se (PIP = 0.9968). Besides, Co showed a significant association with decreased FPG levels in older adults without hyperlipemia and in women.

CONCLUSIONS

Both Mg and Se were associated with FPG levels, individually and as a mixture. The essential metal mixture displayed a linear dose-response relationship with reduced FPG levels, with Mg having the largest contribution to FPG levels, followed by Se. Further prospective investigations are necessary to validate these exploratory findings.

The associations of non-essential metal mixture with fasting plasma glucose among Chinese older adults without diabetes

The evidence about the effect of non-essential metal mixture on fasting plasma glucose (FPG) levels among older adults without diabetes is limited. This study aims to estimate the individual and joint relationship between five non-essential metals and FPG levels in Chinese older adults without diabetes. This study included 2362 older adults without diabetes. Urinary concentrations of five non-essential metals, i.e., cesium (Cs), aluminum (Al), thallium (Tl), cadmium (Cd), and arsenic (As), were detected by inductively coupled plasma mass spectrometry (ICP-MS). The associations of single metals and the metal mixture with FPG levels were assessed using linear regression and Bayesian kernel machine regression (BKMR) models, respectively. Adjusted single-metal linear regression models showed positive associations of urinary Al (β = 0.016, 95%CI: 0.001-0.030) and Cs (β = 0.018, 95%CI: 0.006-0.031) with FPG levels. When comparing the 2th, 3th, and 4th quartiles of urine Cs to its 1th quartile, the significant associations between Cs and FPG levels were found and presented as an "inverted U" trend (βQ2 vs. Q1: 0.034; βQ3 vs. Q1:0.054; βQ4 vs. Q1: 0.040; all P<0.05). BKMR analyses showed urinary level of Cs exhibited an "inverted U" shape association with FPG levels. Moreover, the FPG levels increased linearly with the raised levels of the non-essential metal mixture, and the posterior inclusion probability (PIP) of Cs was the highest (0.92). Potential positive interaction of As and Cs on FPG levels was found in BKMR model. Stratified analysis displayed significant interactions of hyperlipidemia and urine Cs or Tl on FPG levels. An inverse U-shaped association between Cs and FPG was found, individually and as mixture. The FPG levels increased with the raised levels of the non-essential metal mixture, and Cs was the most contributor to FPG levels. Further research is required to confirm the correlation between non-essential metals and FPG levels and to clarify the underlying mechanisms.

Metal mixture exposure and the risk for immunoglobulin A nephropathy: Evidence from weighted quantile sum regression

Immunoglobulin A nephropathy (IgAN) is the most common type of glomerulonephritis in adults worldwide. Environmental metal exposure has been reported to be involved in the pathogenic mechanisms of kidney diseases, yet no further epidemiological study has been conducted to assess the effects of metal mixture exposure on IgAN risk. In this study, we conducted a matched case‒control design with three controls for each patient to investigate the association between metal mixture exposure and IgAN risk. A total of 160 IgAN patients and 480 healthy controls were matched for age and sex. Plasma levels of arsenic, lead, chromium, manganese, cobalt, copper, zinc, and vanadium were measured using inductively coupled plasma mass spectrometry. We used a conditional logistic regression model to assess the association between individual metals and IgAN risk, and a weighted quantile sum (WQS) regression model to analyze the effects of metal mixtures on IgAN risk. Restricted cubic splines were used to evaluate overall associations between plasma metal concentrations and estimated glomerular filtration rate (eGFR) levels. We observed that except for Cu, all the metals analyzed were nonlinearly associated with decreased eGFR, and higher concentrations of arsenic and lead were associated with elevated IgAN risk in both single-metal [3.29 (1.94, 5.57), 6.10 (3.39, 11.0), respectively] and multiple-metal [3.04 (1.66, 5.57), 4.70 (2.47, 8.97), respectively] models. Elevated manganese [1.76 (1.09, 2.83)] levels were associated with increased IgAN risk in the single-metal model. Copper was inversely related to IgAN risk in both single-metal [0.392 (0.238, 0.645)] and multiple-metal [0.357 (0.200, 0.638)] models. The WQS indices in both positive [2.04 (1.68, 2.47)] and negative [0.717 (0.603, 0.852)] directions were associated with IgAN risk. Lead, arsenic, and vanadium contributed significant weights (0.594, 0.195, and 0.191, respectively) in the positive direction; copper, cobalt, and chromium carried significant weights (0.538, 0.253, and 0.209, respectively). In conclusion, metal exposure was related to IgAN risk. Lead, arsenic, and copper were all significantly weighted factors of IgAN development, which may require further investigation.

The mediating role of telomere length in multi-pollutant exposure associated with metabolic syndrome in adults

Metabolic syndrome is a chronic and complex disease characterized by environmental and genetic factors. However, the underlying mechanisms remain unclear. This study assessed the relationship between exposure to a mixture of environmental chemicals and metabolic syndrome (MetS) and further examined whether telomere length (TL) moderated these relationships. A total of 1265 adults aged > 20 years participated in the study. Data on multiple pollutants (polycyclic aromatic hydrocarbons, phthalates, and metals), MetS, leukocyte telomere length (LTL), and confounders were provided in the 2001-2002 National Health and Nutrition Examination Survey. The correlations between multi-pollutant exposure, TL, and MetS in the males and females were separately assessed using principal component analysis (PCA), logistic and extended linear regression models, Bayesian kernel machine regression (BKMR), and mediation analysis. Four factors were generated in PCA that accounted for 76.2% and 77.5% of the total environmental pollutants in males and females, respectively. The highest quantiles of PC2 and PC4 were associated with the risk of TL shortening (P < 0.05). We observed that the relationship between PC2, PC4, and MetS risk was significant in the participants with median TL levels (P for trend = 0.04 for PC2, and P for trend = 0.01 for PC4). Furthermore, mediation analysis revealed that TL could explain 26.1% and 17.1% of the effects of PC2 and PC4 associated with MetS in males, respectively. The results of BKMR model revealed that these associations were mainly driven by 1-PYE (cPIP = 0.65) and Cd (cPIP = 0.29) in PC2. Meanwhile, TL could explain 17.7% of the mediation effects of PC2 associated with MetS in the females. However, the relationships between pollutants and MetS were sparse and inconsistent in the females. Our findings suggest that the effects of the risk of MetS associated with mixed exposure to multiple pollutants are mediated by TL, and this mediating effect in the males is more pronounced than that in the females.

Short-term exposure to antimony induces hepatotoxicity and metabolic remodeling in rats

Antimony (Sb) poses a significant threat to human health due to sharp increases in its exploitation and application globally, but few studies have explored the pathophysiological mechanisms of acute hepatotoxicity induced by Sb exposure. We established an in vivo model to comprehensively explore the endogenous mechanisms underlying liver injury induced by short-term Sb exposure. Adult female and male Sprague-Dawley rats were orally administrated various concentrations of potassium antimony tartrate for 28 days. After exposure, the serum Sb concentration, liver-to-body weight ratio, and serum glucose levels significantly increased in a dose-dependent manner. Body weight gain and serum concentrations of biomarkers of hepatic injury (e.g., total cholesterol, total protein, alkaline phosphatase, and the aspartate aminotransferase/alanine aminotransferase ratio) decreased with increasing Sb exposure. Through integrative non-targeted metabolome and lipidome analyses, alanine, aspartate, and glutamate metabolism; phosphatidylcholines; sphingomyelins; and phosphatidylinositols were the most significantly affected pathways in female and male rats exposed to Sb. Additionally, correlation analysis showed that the concentrations of certain metabolites and lipids (e.g., deoxycholic acid, N-methylproline, palmitoylcarnitine, glycerophospholipids, sphingomyelins, and glycerol) were significantly associated with hepatic injury biomarkers, indicating that metabolic remodeling may be involved in apical hepatotoxicity. Our study demonstrated that short-term exposure to Sb induces hepatotoxicity, possibly through a glycolipid metabolism disorder, providing an important reference for the health risks of Sb pollution.

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.

Longitudinal plasma magnesium status during pregnancy and the risk of gestational diabetes mellitus: a prospective cohort study

Emerging evidence has shown that magnesium (Mg) was associated with type 2 diabetes while few focused on abnormal glucose metabolism during pregnancy. The study is aimed at investigating the association between longitudinal changes in plasma Mg during pregnancy and subsequent risk of gestational diabetes (GDM) and exploring the possible influence of iron supplementation on the changes of plasma Mg levels. One thousand seven hundred fifty-six pregnant women from Tongji Maternal and Child Health Cohort (TMCHC) were involved. Blood samples were collected at gestational weeks 17.0 ± 0.9 and later 26.2 ± 1.4. Plasma Mg was measured by inductively coupled plasma mass spectrometry (ICP-MS) with decline rates calculated. Information on general characteristics and iron supplementation was collected by questionnaires. Oral glucose tolerance test (OGTT) was conducted at 24-28 gestational weeks to diagnose GDM. Poisson regression with robust error variance was used to estimate relative risks (RR) of GDM. Median concentrations of plasma Mg were 0.69 mmol/L and 0.63 mmol/L respectively at two collections. The prevalence of hypomagnesemia at the first collection was 73% and associated with a 1.59 (95%CI: 1.07, 2.37) fold risk of GDM. Adjusted RRs were 1.74 (95%CI: 1.06, 2.83) and 2.44 (95%CI: 1.54, 3.85) for women with hypomagnesemia and followed more tertile (T2 and T3 vs. T1) of Mg decrement. Iron supplementation above 30 mg/day was found associated with more Mg decrement (25.5% and 27.5% in T2 and T3 vs. 19.5% in T1). In conclusion, hypomagnesemia during pregnancy is prevalent and associated with increased GDM risk, especially in women followed by more plasma Mg decrement during pregnancy. High-dose iron supplementation may involve more plasma Mg decrement.

Cardiovascular Effects of Environmental Metal Antimony: Redox Dyshomeostasis as the Key Pathogenic Driver

Significance: Cardiovascular diseases (CVDs) are the leading cause of death worldwide, which may be due to sedentary lifestyles with less physical activity and over nutrition as well as an increase in the aging population; however, the contribution of pollutants, environmental chemicals, and nonessential metals to the increased and persistent CVDs needs more attention and investigation. Among environmental contaminant nonessential metals, antimony has been less addressed. Recent Advances: Among environmental contaminant nonessential metals, several metals such as lead, arsenic, and cadmium have been associated with the increased risk of CVDs. Antimony has been less addressed, but its potential link to CVDs is being gradually recognized. Critical Issues: Several epidemiological studies have revealed the significant deleterious effects of antimony on the cardiovascular system in the absence or presence of other nonessential metals. There has been less focus on whether antimony alone can contribute to the pathogenesis of CVDs and the proposed mechanisms of such possible effects. This review addresses this gap in knowledge by presenting the current available evidence that highlights the potential role of antimony in the pathogenesis of CVDs, most likely via antimony-mediated redox dyshomeostasis. Future Directions: More direct evidence from preclinical and mechanistic studies is urgently needed to evaluate the possible roles of antimony in mitochondrial dysfunction and epigenetic regulation in CVDs. Antioxid. Redox Signal. 38, 803-823.

Joint effects of per- and polyfluoroalkyl substance alternatives and heavy metals on renal health: A community-based population study in China

BACKGROUND

Previous studies have indicated that chlorinated polyfluorinated ether sulfonic acids (Cl-PFESAs), when used as an alternative to per- and polyfluoroalkyl substances (PFASs), result in kidney toxicity. However, their co-exposure with heavy metals, has not yet been described.

OBJECTIVES

To explore the joint effects of Cl-PFESAs and heavy metal exposure on renal health in Chinese adults, and identify specific pollutants driving the associations.

METHODS

Our sample consists of 1312 adults from a cross-sectional survey of general communities in Guangzhou, China. We measured Cl-PFESAs, legacy PFASs (perfluorooctanoic acid [PFOA] and perfluorooctane sulfonated [PFOS]), and heavy metals (arsenic, cadmium, and lead). The relationship between single pollutant and glomerular filtration rate (eGFR) and the odds ratio (OR) of chronic kidney disease (CKD) was studied using Generalized additive models (GAMs). Bayesian Kernel Machine Regression (BKMR) models were applied to assess joint effects of Cl-PFESAs and heavy metals. Additionally, we conducted a sex-specific analysis to determine the modification effect of this variable.

RESULTS

In single pollutant models, CI-PFESAs, PFOA, PFOS and arsenic were negatively associated with eGFR. Additionally, PFOA and heavy metals were positively correlated with the OR of CKD. For example, the estimated change with 95% confidence intervals (CI) of eGFR at from the highest quantile of 6:2 Cl-PFESA versus the lowest quantile was -5.65 ng/mL (95% CI: -8.21, -3.10). Sex played a role in modifying the association between 8:2 Cl-PFESA, PFOS and eGFR. In BKMR models, pollutant mixtures had a negative joint association with eGFR and a positive joint effect on CKD, especially in women. Arsenic appeared to be the primary contributing pollutant.

CONCLUSION

We provide epidemiological evidence that Cl-PFESAs independently and jointly with heavy metals impaired kidney health. More population-based human and animal studies are needed to confirm our results.

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.

Association of Dietary and Plasma Magnesium with Glycaemic Markers in a Chinese Population

Certain metals play a role in the pathogenesis of diabetes. This study aimed to investigate the potential association of plasma magnesium (Mg) and dietary intake of Mg with glycaemic markers. A cross-sectional study was conducted on 2373 subjects in Guangxi, China. Dietary Mg was obtained through a food frequency questionnaire containing 109 common foods. Plasma Mg concentration was determined by inductively coupled plasma mass spectrometry. Multiple linear regression combined with multivariable restricted cubic spline (RCS) functions was applied to evaluate the association of plasma Mg and dietary Mg with haemoglobin A1c (HbA1c) and fasting plasma glucose (FPG). In linear regression, dietary Mg was significantly associated with FPG in the overall population (β =  - 0.087, P < 0.05) and in women (β =  - 0.098, P < 0.05). Plasma Mg was significantly associated with FPG in the overall population (β =  - 0.096, P < 0.05) and in men (β =  - 0.110, P < 0.05) and women (β =  - 0.088, P < 0.05). In the RCS model, no non-linear association was found between dietary and plasma Mg and HbA1c levels. Dietary and plasma Mg are significantly negatively associated with fasting glucose.

Relationship of multiple metals mixture and osteoporosis in older Chinese women: An aging and longevity study

Osteoporosis has become a major health problem in older women. Previous studies have linked individual metals exposure with osteoporosis, but combined effects remain inconclusive. We aimed to explore the individual and combined association between multiple metals mixture and osteoporosis risk in older Chinese women. A total of 2297 older women (aged ≥60) from the Hongshuihe region of Guangxi, southern China included. We measured 22 blood metal levels through inductively coupled plasma mass spectrometry. And osteoporosis was defined as a T score ≤ -2.5. The least absolute shrinkage and selection operator (LASSO) penalized regression, and Bayesian kernel machine regression (BKMR) models were performed to explore the association between blood metals and osteoporosis risk. Of 2297 older women, there were 829 osteoporosis and 1468 non-osteoporosis participants. The median age was 71 and 68 years old in the osteoporosis and the non-osteoporosis group, respectively. In the single-metal model, rubidium and vanadium were negatively associated with osteoporosis (P for trend = 0.02 and 0.002, respectively), and lead presented the reverse trend (P for trend = 0.01). The LASSO penalized regression model selected nine metals (calcium, cadmium, cobalt, lead, magnesium, rubidium, strontium, vanadium and zinc), which were included in the subsequent analysis. And the multiple-metal model presented a consistent trend with the single-metal model using the selected metals. Furthermore, we performed BKMR to explore the combined effect, and found an overall negative effect between metals mixture and osteoporosis risk when all the metals were fixed at 50th, and rubidium and vanadium were the main contributors. In addition, blood Rb and V were significantly negatively related to OP risk with other metals at different levels (25th, 50th and 75th percentiles). The study suggests metal mixture exposure and osteoporosis risk in older Chinese women, and further studies need to be conducted.

Associations between prenatal multiple plasma metal exposure and newborn telomere length: Effect modification by maternal age and infant sex

Exposure to metals during pregnancy may affect maternal and infant health. However, studies on the combined effects of metals on the telomere length (TL) of newborns are limited. A prospective cohort study was conducted among 1313 mother-newborn pairs in the Guangxi Zhuang Birth Cohort. The concentrations of metals in maternal plasma during the first trimester were measured using inductively coupled plasma-mass spectrometry. We explored the associations between nine plasma metals and newborn TL using generalized linear models (GLMs), principal component analysis (PCA), quantile g-computation (qgcomp), and Bayesian kernel machine regression (BKMR). The GLMs revealed the inverse association between plasma arsenic (percent change, -5.56%; 95% CI: -7.69%, -3.38%) and barium concentrations (-9.84%; 95% CI: -13.81%, -5.68%) and newborn TL. Lead levels were related to significant decreases in newborn TL only in females. The PCA revealed a negative association between the PC3 and newborn TL (-4.52%; 95% CI: -6.34%, -2.68%). In the BKMR, the joint effect of metals was negatively associated with newborn TL. Qgcomp indicated that each one-tertile increase in metal mixture levels was associated with shorter newborn TL (-9.39%; 95% CI: -14.32%, -4.18%). The single and joint effects of multiple metals were more pronounced among pregnant women carrying female fetuses and among pregnant women <28 years of age. The finding suggests that prenatal exposure to arsenic, barium, antimony, and lead and mixed metals may shorten newborn TLs. The relationship between metal exposures and newborn TL may exhibit heterogeneities according to infant sex and maternal age.

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.

Sex-Specific Association between Fasting Plasma Glucose and Serum Selenium Levels in Adults from Southern Mexico

Selenium (Se) is an essential trace element that by its antioxidant properties has been studied to elucidate its participation in the development of obesity and type 2 diabetes. We evaluated the association between cardiometabolic traits and serum Se levels in a sample of adults from southern Mexico. In 96 nondiabetic individuals, anthropometric data and clinical biochemistry measurements were analyzed. Serum total Se levels were measured with inductively coupled plasma mass spectrometry (ICP-MS). Serum Se level in the whole sample was 10.309 ± 3.031 μg mL-1 and no difference between the women and men was observed (p = 0.09). Additionally, fasting plasma glucose (FPG) was significantly associated with serum Se level (β = -0.07 ± 0.03, p = 0.02, analysis adjusted for age, sex and BMI). Furthermore, sex shows significant interaction with FPG on the serum Se levels (p = 0.01). A follow-up analysis revealed the particular association between FPG and Se levels in women (β = -0.10 ± 0.04, p = 0.01). In conclusion, our data evidenced a women-specific association between FPG and serum Se levels in a sample of adults from southern Mexico.

Effects of multi-metal exposure on the risk of diabetes mellitus among people aged 40-75 years in rural areas in southwest China

AIMS/INTRODUCTION

Metals play an important role in diabetes mellitus. This cross-sectional study aimed to evaluate the overall, individual and interactive effects of multi-metal exposure on the prevalence of diabetes mellitus, impaired fasting glucose (IFG) rate and fasting blood glucose (FBG) levels.

MATERIALS AND METHODS

The FBG levels of a study population from a cadmium (Cd)-polluted area (n = 250) and an unpolluted area (n = 204), and the metal levels, including magnesium, calcium (Ca), iron (Fe), zinc (Zn), arsenic (As), Cd, copper and lead (Pb) in blood and urine were detected. The study population was divided into a normal fasting glucose group, an IFG group and a diabetes mellitus group on the basis of FBG levels.

RESULTS

The IFG rate and diabetes mellitus prevalence were negatively associated with blood Cd and urine Zn levels (IFG rate: odds ratio [OR] 0.780, 95% confidence interval [CI] 0.655-0.928; OR 0.622, 95% CI 0.465-0.831. Diabetes mellitus prevalence: OR 0.506, 95% CI 0.288-0.888; OR 0.609, 95% CI 0.395-0.939), the IFG rate was positively associated with urine Fe levels (OR 1.876, 95% CI 1.290-2.778), and diabetes mellitus prevalence was positively associated with urine Pb and blood Fe levels (OR 1.185, 95% CI 1.022-1.376; OR 1.008, 95% CI 1.001-1.014). A linear negative correlation was observed between FBG levels and blood Cd, and non-linear inverted U-shaped associations were found between FBG levels and Zn, Pb and copper in urine.

CONCLUSIONS

This research suggests that multi-metal exposure, especially Cd, Fe, Zn, copper and Pb, is linked to diabetes mellitus, and the interactive effects of multiple metals require further exploration.

Associations of multiple metals with lung function in welders by four statistical models

BACKGROUND

Exposure to heavy metals has been related to decreased lung function in workers. However, due to limitations in statistical methods for mixtures, previous studies mainly focused on single or several toxic metals, with few studies involving metal exposome and lung function.

OBJECTIVES

The study aimed to evaluate the effects of co-exposure to the metal mixtures on multiple parameters of pulmonary function tests and to identify the elements that play an essential role in elastic-net regression (ENET), multivariate linear regression, bayesian kernel machine regression (BKMR), and quantile g-computation (QG-C) models.

METHODS

We have recruited 186 welders from Anhui (China) in 2019. And their end-of-shift urine and lung function measure data were collected with informed consent. The urinary concentrations of 23 metals were measured by inductively coupled urinary mass spectrometry. The lung function measures including forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1) and peak expiratory flow (PEF) were also detected as outcome indicators. Four statistical methods, ENET, multivariate linear regression, BKMR, and QG-C models were used to evaluate the associations of element mixtures on lung function comprehensively.

RESULTS

Lead and cadmium were negatively associated with FVC and FEV1, nickel and chromium were inversely associated with PEF, and strontium showed significant positive effects in linear regression models, which were consistent with the results in BKMR and QG-C models. Both BKMR and QG-C models showed a significantly negative overall effect of metal mixtures on lung function parameters (FVC, FEV1, and PEF). Meanwhile, BKMR showed the non-linear relationships of cadmium with FVC.

CONCLUSION

Multi-pollutant mixtures of metals were negatively associated with lung function. Lead, cadmium, nickel, and strontium might be crucial elements. Our findings highlight a need to prioritize workers' environmental health, and guide future research into the toxic mechanisms of metal-mediated lung function injury.

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.

The association between urine elements and fasting glucose levels in a community-based elderly people in Beijing

Epidemiological studies have demonstrated that various kinds of urinary element concentrations were different between healthy, prediabetes, and diabetes patients. Meanwhile, many studies have explored the relationship between element concentration and fasting blood glucose (FBG), but the association between joint exposure to co-existing elements and FBG level has not been well understood. The study explored the associations of joint exposure to co-existing urinary elements with FBG level in a cross-sectional design. 275 retired elderly people were recruited from Beijing, China. The questionnaire survey was conducted, and biological samples were collected. The generalized linear model (GLM) and two-phase Bayesian kernel machine regression (BKMR) model were used to perform in-depth association analysis between urinary elements and FBG. The GLM analysis showed that Zn, Sr, and Cd were significantly correlated with the FBG level, under control potential confounding factors. The BKMR analysis demonstrated 8 elements (Zn, Se, Fe, Cr, Ni, Cd, Mn, and Al) had a higher influence on FBG (posterior inclusion probabilities > 0.1). Further intensive analyses result of the BKMR model indicated that the overall estimated exposure of 8 elements was positively correlated with the FBG level and was statistically significant when all creatinine-adjusted element concentrations were at their 65th percentile. Meanwhile, the BKMR analysis showed that Cd and Zn had a statistically significant association with FBG levels when other co-existing elements were controlled at different levels (25th, 50th, or 75th percentile), respectively. The results of the GLM and BKMR model were inconsistent. The BKMR model could flexibly calculate the joint exposure to co-existing elements, evaluate the possible interaction effects and nonlinear correlations. The meaningful conclusions were found that it was difficult to get by traditional methods. This study will provide methodological reference and experimental evidence for the association between joint exposure to co-existing elements and FBG in elderly people.

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.

Correlation between urinary contents of some metals and fasting plasma glucose levels: A cross-sectional study in China

Many metals are involved in the pathogenesis of diabetes, but most of existing studies focused on single metals. The study of mixtures represents real-life exposure scenarios and deserves attention. This study aimed to explore the potential relationship of urinary copper (Cu), zinc (Zn), arsenic (As), selenium (Se), and strontium (Sr) contents with fasting plasma glucose (FPG) levels in 2766 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 FPG levels. In the multiple metals linear regression, Zn (β = 0.434), Se (β = 0.172), and Sr (β = -0.143) showed significant association with FPG levels (all P < 0.05). The BKMR model analysis showed that the results of single metal association were consistent with the multiple metals linear regression. The mixture of five metals had a positive over-all effect on FPG levels, and Zn (PIP = 1.000) contributed the most to the FPG levels. Cu and As were negatively correlated with FPG levels in women. The potential interaction effect between Cu and Sr was observed in participants aged ≥ 60 years old (Pinteraction = 0.035). In summary, our results suggested that multiple metals in urine are associated with FPG levels. Further studies are needed to confirm these findings and clarify the underlying mechanisms.

Associations of multiple metals with bone mineral density: A population-based study in US adults

Epidemiologic studies focus on combined effects of multiple metals on bone mineral density (BMD) are scarce. Therefore, this study was conducted to examine associations of multiple metals exposure with BMD. Data of adults aged ≥20 years (n = 2545) from the US National Health and Nutrition Examination Survey (NHANES, 2011-2016) were collected and analyzed. Concentrations of metals were measured in blood (cadmium [Cd], lead [Pb], mercury [Hg], and manganese [Mn]) and serum (copper [Cu], selenium [Se], and zinc [Zn]) using inductively coupled plasma mass spectrometry and inductively coupled plasma dynamic reaction cell mass spectrometry, respectively. The weighted quantile sum (WQS) and Bayesian kernel machine regression (BKMR) models were performed to determine the joint effects of multiple metals exposure on lumbar and total BMD. The linear regression analyses showed Pb was negatively associated with BMDs. The WQS regression analyses revealed that the WQS index was inversely related to lumbar (β = -0.022, 95% CI: -0.036, -0.008) and total BMD (β = -0.015, 95% CI: -0.024, -0.006), and Se, Mn, and Pb were the main contributors for the combined effects. Additionally, nonlinear dose-response relationships between Pb, Mn, and Se and BMD, as well as a synergistic interaction of Pb and Mn, were found in the BKMR analyses. Our findings suggested co-exposure to Cd, Pb, Hg, Mn, Cu, Se, and Zn (above their 50th percentiles) was associated with reduced BMD, and Pb, Mn, and Se were the main contributors driving the overall effects.

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.