Exposure to heavy metals from point pollution sources and risk of incident type 2 diabetes among women: a prospective cohort analysis

Associations of heavy metal exposure with diabetic retinopathy in the U.S. diabetic population: a cross-sectional study

Background

Mounting evidence suggests a correlation between heavy metals exposure and diabetes. Diabetic retinopathy (DR) is a prevalent and irreversible complication of diabetes that can result in blindness. However, studies focusing on the effects of exposure to heavy metals on DR remain scarce. Thus, this study aimed to investigate the potential correlation between heavy metals exposure and DR.

Methods

A total of 1,146 diabetics from the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2018 were included in this study. Heavy metal levels were measured via urine testing. Weighted logistic regression, Bayesian kernel machine regression (BKMR), weighted quantile sum (WQS) regression, and restricted cubic spline (RCS) were utilized to investigate the potential relationships between exposure to 10 heavy metals and DR. Finally, subgroup analysis was conducted based on the glycemic control status.

Results

Among the 1,146 participants, 239 (20.86%) were diagnosed with DR. Those with DR had worse glycemic control and a higher prevalence of chronic kidney disease compared to those without DR. Moreover, both the WQS regression and BKMR models demonstrated a positive relationship between exposure to mixed heavy metals and the risk of DR. The results of weighted logistic regression revealed a positive correlation between cobalt (Co) and antimony (Sb) exposure and the risk of DR (OR = 1.489, 95%CI: 1.064-2.082, p = 0.021; OR = 1.475, 95% CI: 1.084-2.008, p = 0.014), while mercury (Hg) exposure was found to promote DR exclusively in the group with good glycemic control (OR = 1.509, 95% CI: 1.157-1.967, p = 0.003). These findings were corroborated by the results of the RCS analysis.

Conclusion

Heavy metal exposure is associated with an increased risk of DR, especially Sb, Co, and Hg exposure. Nevertheless, well-designed prospective studies are warranted to validate these findings.

Association of Water Arsenic With Incident Diabetes in U.S. Adults: The Multi-Ethnic Study of Atherosclerosis and the Strong Heart Study

OBJECTIVE

We examined the association of arsenic in federally regulated community water systems (CWS) and unregulated private wells with type 2 diabetes (T2D) incidence in the Strong Heart Family Study (SHFS), a prospective study of American Indian communities, and the Multi-Ethnic Study of Atherosclerosis (MESA), a prospective study of racially and ethnically diverse urban U.S. communities.

RESEARCH DESIGN AND METHODS

We evaluated 1,791 participants from SHFS and 5,777 participants from MESA who had water arsenic estimates available and were free of T2D at baseline (2001-2003 and 2000-2002, respectively). Participants were followed for incident T2D until 2010 (SHFS cohort) or 2019 (MESA cohort). We used Cox proportional hazards mixed-effects models to account for clustering by family and residential zip code, with adjustment for sex, baseline age, BMI, smoking status, and education.

RESULTS

T2D incidence was 24.4 cases per 1,000 person-years (mean follow-up, 5.6 years) in SHFS and 11.2 per 1,000 person-years (mean follow-up, 14.0 years) in MESA. In a meta-analysis across the SHFS and MESA cohorts, the hazard ratio (95% CI) per doubling in CWS arsenic was 1.10 (1.02, 1.18). The corresponding hazard ratio was 1.09 (0.95, 1.26) in the SHFS group and 1.10 (1.01, 1.20) in the MESA group. The corresponding hazard ratio (95% CI) for arsenic in private wells and incident T2D in SHFS was 1.05 (0.95, 1.16). We observed statistical interaction and larger magnitude hazard ratios for participants with BMI <25 kg/m2 and female participants.

CONCLUSIONS

Low to moderate water arsenic levels (<10 µg/L) were associated with T2D incidence in the SHFS and MESA cohorts.

Association Between Arsenic Toxicity, AS3MT Gene Polymorphism and Onset of Type 2 Diabetes

Arsenic (As) exposure in drinking water has become a serious public health issue. AS3MT gene is involved in the metabolism of arsenic, so a single nucleotide polymorphism in this gene may lead to the development of type 2 diabetes in arsenic-exposed areas. This study aimed to evaluate the association of the AS3MT gene with the development of type 2 diabetes in highly arsenic-exposed areas of Punjab, Pakistan. Total 200 samples equal in number from high arsenic exposed-areas of Lahore (Nishtar) and Kasur (Mustafa Abad) were collected. rs11191439 was utilized as an influential variable to evaluate the association between arsenic metabolism and diabetes status to find a single nucleotide polymorphism in the AS3MT gene. We observed the arsenic level in drinking water of the arsenic-exposed selected areas 115.54 ± 1.23 µg/L and 96.88 ± 0.48 µg/L, respectively. The As level in the urine of diabetics (98.54 ± 2.63 µg/L and 56.38 ± 12.66 µg/L) was higher as compared to non-diabetics (77.58 ± 1.8 µg/L and 46.9 ± 8.95 µg/L) of both affected areas, respectively. Correspondingly, the As level in the blood of diabetics (6.48 ± 0.08 µg/L and 5.49 ± 1.43 µg/L) and non-diabetics (6.22 ± 0.12 µg/L and 5.26 ± 0.24 µg/L) in the affected areas. Genotyping showed significant differences in the frequencies of alleles among cases and controls. Nevertheless, notable disparities in genotype distribution were observed in SNPs rs11191439 (T/C) (P < 0.05) and when comparing T2D patients and non-diabetic control subjects. The AS3MT gene and clinical parameters show a significant association with the affected people with diabetes living in arsenic-exposed areas.

Environmental exposure to lead and cadmium are associated with triglyceride glucose index

The triglyceride glucose (TyG) index was suggested as a novel reliable surrogate marker for insulin resistance and related cardiovascular-metabolic diseases. We aimed to evaluate the association between the TyG index and environmental exposure to lead (Pb), mercury (Hg), and cadmium (Cd). A total of 9645 adults who enrolled in the Korea National Health and Nutrition Examination Survey in 2005, 2008-2013, and 2016 were included. Fasting plasma glucose and triglyceride levels were used to calculate the TyG index. Multivariate logistic regression model was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). We noted an increasing trend in the TyG index with increment of blood Pb and Cd concentrations. Participants in the highest quartile of blood Pb and Cd concentrations had higher TyG index values than those in the lowest quartile, with ORs (95% CIs) of 1.32 (1.07-1.63) and 1.29 (1.04-1.59) for Pb and Cd, respectively. Strong associations between blood Pb and Cd concentrations and the TyG index were found in men. Blood Hg concentrations did not show a significant association with the TyG index. Our study suggests that public health strategies for cardiovascular-metabolic disorder prevention should be directed toward individuals exposed to priority heavy metals.

Electrochemical and Colorimetric Nanosensors for Detection of Heavy Metal Ions: A Review

Human exposure to acute and chronic levels of heavy metal ions are linked with various health issues, including reduced children's intelligence quotients, developmental challenges, cancers, hypertension, immune system compromises, cytotoxicity, oxidative cellular damage, and neurological disorders, among other health challenges. The potential environmental HMI contaminations, the biomagnification of heavy metal ions along food chains, and the associated risk factors of heavy metal ions on public health safety are a global concern of top priority. Hence, developing low-cost analytical protocols capable of rapid, selective, sensitive, and accurate detection of heavy metal ions in environmental samples and consumable products is of global public health interest. Conventional flame atomic absorption spectroscopy, graphite furnace atomic absorption spectroscopy, atomic emission spectroscopy, inductively coupled plasma-optical emission spectroscopy, inductively coupled plasma-mass spectroscopy, X-ray diffractometry, and X-ray fluorescence have been well-developed for HMIs and trace element analysis with excellent but varying degrees of sensitivity, selectivity, and accuracy. In addition to high instrumental running and maintenance costs and specialized personnel training, these instruments are not portable, limiting their practicality for on-demand, in situ, field study, or point-of-need HMI detection. Increases in the use of electrochemical and colorimetric techniques for heavy metal ion detections arise because of portable instrumentation, high sensitivity and selectivity, cost-effectiveness, small size requirements, rapidity, and visual detection of colorimetric nanosensors that facilitate on-demand, in situ, and field heavy metal ion detections. This review highlights the new approach to low-cost, rapid, selective, sensitive, and accurate detection of heavy metal ions in ecosystems (soil, water, air) and consumable products. Specifically, the review highlights low-cost, portable, and recent advances in smartphone-operated screen-printed electrodes (SPEs), plastic chip SPES, and carbon fiber paper-based nanosensors for environmental heavy metal ion detection. In addition, the review highlights recent advances in colorimetric nanosensors for heavy metal ion detection requirements. The review provides the advantages of electrochemical and optical nanosensors over the conventional methods of HMI analyses. The review further provides in-depth coverage of the detection of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), manganese (Mn), nickel (Ni), lead (Pb), and zinc (Zn) ions in the ecosystem, with emphasis on environmental and biological samples. In addition, the review discusses the advantages and challenges of the current electrochemical and colorimetric nanosensors protocol for heavy metal ion detection. It provides insight into the future directions in the use of the electrochemical and colorimetric nanosensors protocol for heavy metal ion detection.

An updated systematic review and dose-response meta-analysis on the relation between exposure to arsenic and risk of type 2 diabetes

Arsenic is among the most critical environmental toxicants associated with many human disorders. However, its effect on type 2 diabetes mellitus (T2DM) is contradictory. This systematic review and dose-response meta-analysis aim to update information on the association between arsenic exposure and the risk of T2DM. The sample type (drinking water, urine, blood, and nails) conducted the subgroup analysis. Evaluation of the high vs. low arsenic concentrations showed a significant association between drinking water arsenic (OR: 1.58, 95% CI: 1.20-2.08) and urinary arsenic (OR: 1.37, 95% CI: 1.24-1.51) with the risk of T2DM. The linear dose-response meta-analysis showed that each 1 μg/L increase in levels of drinking water arsenic (OR: 1.01, 95% CI: 1.00-1.01) and urinary arsenic (OR: 1.01, 95% CI: 1.00-1.02) was associated with a 1% increased risk of T2DM. The non-linear dose-response analysis indicated that arsenic in urine was associated with the risk of T2DM (Pnon-linearity<0.001). However, this effect was not statistically significant for arsenic in drinking water (Pnon-linearity=0.941). Our findings suggest that blood arsenic was not significantly linked to the increased risk of T2DM in high vs. low (OR: 1.21, 95% CI: 0.85-1.71), linear (OR: 1.04, 95% CI: 0.99-1.09), and non-linear (Pnon-linearity=0.365) analysis. Also, nail arsenic was not associated with the risk of T2DM in this meta-analysis (OR: 1.33, 95% CI: 0.69-2.59). This updated dose-response meta-analysis indicated that arsenic exposure was significantly correlated with the risk of T2DM.

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.

Environmental risk factors of type 2 diabetes-an exposome approach

Type 2 diabetes is one of the major chronic diseases accounting for a substantial proportion of disease burden in Western countries. The majority of the burden of type 2 diabetes is attributed to environmental risks and modifiable risk factors such as lifestyle. The environment we live in, and changes to it, can thus contribute substantially to the prevention of type 2 diabetes at a population level. The 'exposome' represents the (measurable) totality of environmental, i.e. nongenetic, drivers of health and disease. The external exposome comprises aspects of the built environment, the social environment, the physico-chemical environment and the lifestyle/food environment. The internal exposome comprises measurements at the epigenetic, transcript, proteome, microbiome or metabolome level to study either the exposures directly, the imprints these exposures leave in the biological system, the potential of the body to combat environmental insults and/or the biology itself. In this review, we describe the evidence for environmental risk factors of type 2 diabetes, focusing on both the general external exposome and imprints of this on the internal exposome. Studies provided established associations of air pollution, residential noise and area-level socioeconomic deprivation with an increased risk of type 2 diabetes, while neighbourhood walkability and green space are consistently associated with a reduced risk of type 2 diabetes. There is little or inconsistent evidence on the contribution of the food environment, other aspects of the social environment and outdoor temperature. These environmental factors are thought to affect type 2 diabetes risk mainly through mechanisms incorporating lifestyle factors such as physical activity or diet, the microbiome, inflammation or chronic stress. To further assess causality of these associations, future studies should focus on investigating the longitudinal effects of our environment (and changes to it) in relation to type 2 diabetes risk and whether these associations are explained by these proposed mechanisms.

Environmental pollution and diabetes mellitus

Diabetes mellitus (DM) is a chromic metabolic disease that affects a large segment of the population worldwide. Physical inactivity, poor nutrition, and genetic predisposition are main risk factors for disease development. In the last decade, it was clear to the scientific community that DM development is linked to a novel disease inducer that was later defined as diabetogenic factors of pollution and endocrine disrupting agents. Environmental pollution is exponentially increasing in uncontrolled manner in several countries. Environmental pollutants are of diverse nature and toxicities, including polyaromatic hydrocarbons (PAHs), pesticides, and heavy metals. In the current review, we shed light on the impact of each class of these pollutants and the underlined molecular mechanism of diabetes induction and biological toxicities. Finally, a brief overview about the connection between coronavirus disease 2019 and diabetes pandemics is presented.

Is Environmental and Occupational Particulate Air Pollution Exposure Related to Type-2 Diabetes and Dementia? A Cross-Sectional Analysis of the UK Biobank

Human exposure to particulate air pollution (e.g., PM_2.5) can lead to adverse health effects, with compelling evidence that it can increase morbidity and mortality from respiratory and cardiovascular disease. More recently, there has also been evidence that long-term environmental exposure to particulate air pollution is associated with type-2 diabetes mellitus (T2DM) and dementia. There are many occupations that may expose workers to airborne particles and that some exposures in the workplace are very similar to environmental particulate pollution. We conducted a cross-sectional analysis of the UK Biobank cohort to verify the association between environmental particulate air pollution (PM_2.5) exposure and T2DM and dementia, and to investigate if occupational exposure to particulates that are similar to those found in environmental air pollution could increase the odds of developing these diseases. The UK Biobank dataset comprises of over 500,000 participants from all over the UK. Environmental exposure variables were used from the UK Biobank. To estimate occupational exposure both the UK Biobank’s data and information from a job exposure matrix, specifically developed for UK Biobank (Airborne Chemical Exposure–Job Exposure Matrix (ACE JEM)), were used. The outcome measures were participants with T2DM and dementia. In appropriately adjusted models, environmental exposure to PM_2.5 was associated with an odds ratio (OR) of 1.02 (95% CI 1.00 to 1.03) per unit exposure for developing T2DM, while PM_2.5 was associated with an odds ratio of 1.06 (95% CI 0.96 to 1.16) per unit exposure for developing dementia. These environmental results align with existing findings in the published literature. Five occupational exposures (dust, fumes, diesel, mineral, and biological dust in the most recent job estimated with the ACE JEM) were investigated and the risks for most exposures for T2DM and for all the exposures for dementia were not significantly increased in the adjusted models. This was confirmed in a subgroup of participants where a full occupational history was available allowed an estimate of workplace exposures. However, when not adjusting for gender, some of the associations become significant, which suggests that there might be a bias between the occupational assessments for men and women. The results of the present study do not provide clear evidence of an association between occupational exposure to particulate matter and T2DM or dementia.

Association of twenty-three plasma elements with fasting serum glucose among Chinese population from four areas with different pollution level

BACKGROUND

Association between fasting serum glucose (FSG) and certain mineral elements has been extensively reported. Investigation regarding multi-element exposure among subjects with different exposure level is warranted to confirm the association and further explore dose-dependent relationship.

METHODS

A total of 3488 participants were recruited from four counties of Hunan province, South China. Basic characteristics were collected by face to face interview and 23 elements in plasma were determined by inductively coupled plasma mass spectrometry. We applied fully adjusted generalized linear regression model and multivariable restricted cubic spline function to test the association and dose-response relationship of FSG with 23 elements.

RESULTS

The results indicated that FSG was positively associated with plasma78selenium level [regression coefficient (β), 0.001; 95 % confidence interval (CI), 0.001, 0.001] in a dose-dependent manner, robust to the adjustment for suspected covariates and stratification by age, gender, BMI and smoking status. A negative association was found between FSG and plasma 208lead (β, -0.004; 95 % CI, -0.016, -0.002), 52chromium (β, -0.002; 95 % CI, -0.004, -0.001) and 47titanium (β, -0.001; 95 % CI, -0.002, -0.001).

CONCLUSION

78selenium was positively while 208lead, 52chromium and 47titanium were negatively associated with FSG in the present study. However, prospective studies are needed to confirm the results.

The chemical exposome of type 2 diabetes mellitus: Opportunities and challenges in the omics era

Type 2 diabetes mellitus (T2DM) is a global silent killer, with > 450 million affected adults worldwide. A diverse array of non-modifiable risk factors such as family history, age (> 45 yrs), race/ethnicity, genetics, and history of gestational diabetes and modifiable risk factors such as physical inactivity, high body fat, body weight, high blood pressure, and high cholesterol for progression of prediabetes to T2DM. Given, that the modern world human population is constantly exposed to multiple stressors in the form of physical (i.e., sound, weather etc.) and chemical environment (i.e., diet, pollutants etc.), industrialization, and modernization has led to form a basis for exposomal correlation with T2DM incidence. Over the past decade, there have been emerging reports on association of levels of persistent organic pollutants (POPs), phthalates, antibiotics, drugs, air pollution, pesticides, and heavy metals with T2DM. In this review, we discuss the well known chemical exposome that has been associated with T2DM; the tools and approaches to capture this chemical exposome, and future opportunities and challenges in this exciting area of research. We further provide a window of thoughts, whether omics technologies can help fill in the gaps to help provide high throughput exposomics datasets in an unbiased manner to help understand T2DM pathophysiology in the context of industrialization, drastic lifestyle changes, urbanization, and pollution. We also discuss and provide guidelines/call to action for future exposomics studies investigating the association of T2DM with exposomes in the context of both epidemiological and experimental approaches.