Significant association between blood lead (Pb) level and haemoglobin A1c in non-diabetic population

Association between glycosylated hemoglobin and blood lead: A cross-sectional study

BACKGROUND

Diabetes is the most common chronic metabolic disease, affecting many people's health. Previous studies have shown a close relationship between trace elements and metabolic diseases. This study investigated the interrelationship between glycosylated hemoglobin (HbA1c) and blood lead (BPb) in adults.

METHOD

This research was carried out involving 12,049 eligible individuals aged 20 years or above from the National Health and Nutrition Examination Survey (NHANES) spanning from 2011 to 2020. Weighted linear regression models and smoothed curve fitting were employed to investigate the association between HbA1c and blood lead. Analyses were stratified based on age, sex, race, and body mass index, and threshold effects were explored using two-stage segmented linear regression models.

RESULT

Among all 12049 participants, through comprehensive adjustment of the model, this study discovered a negative association between HbA1c and blood lead. In addition, when stratified by sex, age, race, and BMI status in subgroup analysis in this study, this correlation still had specific statistical significance. In performing subgroup analyses, we found that the relationship between HbA1c and blood lead may yield distinct outcomes arise from gender disparities. In women, a significant U-shaped association exists between HbA1c and BPb. At approximately 6.6% of HbA1c value, the relationship between the two shifts from negative to positive.

CONCLUSION

This investigation proposes a "U" form association between HbA1c and BPb in American adults.

Assessing the impact of arsenic, lead, mercury, and cadmium exposure on glycemic and lipid profile markers: A systematic review and meta-analysis protocol

The toxicity of metals presents a significant threat to human health due to the metabolic changes they induce. Thus, it is crucial to understand the impact of exposure to toxic elements on glycemic and lipid profiles. To this end, we developed a systematic review protocol registered in PROSPERO (CRD42023393681), following PRISMA-P guidelines. This review aims to assess environmental exposure to arsenic, cadmium, mercury, and lead in individuals aged over ten years and elucidate their association with glycemic markers such as fasting plasma glucose, glycated hemoglobin, as well as lipid parameters including total cholesterol, triglycerides, high-density lipoprotein, and low-density lipoprotein cholesterol. Articles published in the MEDLINE (PubMed), EMBASE, Web of Science, LILACS, and Google Scholar databases until March 2024 will be included without language restrictions. The modified Newcastle-Ottawa scale will be employed to assess the quality of the included studies, and the results will be presented through narrative synthesis. If adequate data are available, a meta-analysis will be conducted. This review can help understand the metabolic responses to exposure to toxic elements and the associated health risks.

Mediating Role of Liver Dysfunction in the Association between Arsenic Exposure and Diabetes in Chinese Adults: A Nationwide Cross-Sectional Study of China National Human Biomonitoring (CNHBM) 2017-2018

Inconsistent results have been reported regarding the association between low-to-moderate arsenic (As) exposure and diabetes. The effect of liver dysfunction on As-induced diabetes remains unclear. The cross-sectional study included 10,574 adults from 2017-2018 China National Human Biomonitoring. Urinary total As (TAs) levels were analyzed as markers of As exposure. Generalized linear mixed models and restricted cubic splines models were used to examine the relationships among TAs levels, serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) concentrations, and diabetes prevalence. Mediating analysis was performed to assess whether liver dysfunction mediated the association between TAs and diabetes. Overall, the OR (95% CI) of diabetes in participants in the second, third, and fourth quartiles of TAs were 1.08 (0.88, 1.33), 1.17 (0.94, 1.45), and 1.52 (1.22, 1.90), respectively, in the fully adjusted models compared with those in the lowest quartile. Serum ALT was positively associated with TAs and diabetes. Additionally, mediation analyses showed that ALT mediated 4.32% of the association between TAs and diabetes in the overall population and 8.86% in the population without alcohol consumption in the past year. This study suggested that alleviating the hepatotoxicity of As could have implications for both diabetes and liver disease.

An evaluation of the effects of mixed heavy metals on prediabetes and type 2 diabetes: epidemiological and toxicogenomic analysis

The link between mixed heavy metals (mercury, lead, and cadmium), prediabetes, and type 2 diabetes mellitus (T2DM), especially molecular mechanisms, is poorly understood. Thus, we aimed to identify the association between mixed heavy metals and T2DM and its components using a data set from the Korean National Health and Nutrition Examination Survey. We further analyzed the main molecular mechanisms implicated in T2DM development induced by mixed heavy metals using in-silico analysis. Our findings observed that serum mercury was associated with prediabetes, elevated glucose, and ln2-transformed glucose when using different statistical methods. "AGE-RAGE signaling pathway in diabetic complications", "non-alcoholic fatty liver disease", "metabolic Syndrome X", and three miRNAs (hsa-miR-98-5p, hsa-let-7a-5p, and hsa-miR-34a-5p) were listed as the most important molecular mechanisms related to T2DM development caused by mixed heavy metals. These miRNA sponge structures were created and examined, and they may be beneficial in the treatment of T2DM. The predicted cutoff values for three heavy metal levels linked to T2DM and its components were specifically identified. Our results imply that chronic exposure to heavy metals, particularly mercury, may contribute to the development of T2DM. To understand the changes in the pathophysiology of T2DM brought on by a combination of heavy metals, more research is required.

Relationship between Metal Exposures, Dietary Macronutrient Intake, and Blood Glucose Levels of Informal Electronic Waste Recyclers in Ghana

While metal exposures are generally high among informal electronic waste (e-waste) recyclers, the joint effect of metals and dietary macronutrients on their metabolic health is unknown. Therefore, we investigated the relationship between metal exposures, dietary macronutrients intake, and blood glucose levels of e-waste recyclers at Agbogbloshie using dietary information (48-h recall survey), blood metals (Pb & Cd), and HbA1C levels of 151 participants (100 e-waste recyclers and 51 controls from the Accra, Ghana) in March 2017. A linear regression model was used to estimate the joint relationship between metal exposures, dietary macronutrient intake, and blood glucose levels. Except for dietary proteins, both groups had macronutrient deficiencies. Diabetes prevalence was significantly higher among controls. Saturated fat, OMEGA-3, and cholesterol intake were associated with significant increases in blood glucose levels of recyclers. In a joint model, while 1 mg of cholesterol consumed was associated with a 0.7% increase in blood glucose, 1 g/L of Pb was found to significantly increase blood glucose levels by 0.9% among recyclers. Although the dietary consumption of cholesterol and fat was not high, it is still possible that exposure to Pb and Cd may still increase the risk of diabetes among both e-waste recyclers and the general population.

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.

Determinants of Longitudinal Change of Glycated Hemoglobin in a Large Non-Diabetic Population

Although many cross-section studies have assessed the determinants of glycated hemoglobin (HbA_1c), there have been limited studies designed to evaluate the temporal correlates of HbA_1c in non-diabetic patients. This study aimed to identify the major determinants of longitudinal change of HbA_1c in non-diabetic patients. This study included subjects from the 104,451 participants enrolled between 2012 and 2018 in the Taiwan Biobank. We only included participants with complete data at baseline and follow-up (n = 27,209). Patients with diabetes at baseline or follow-up (n = 3983) were excluded. Finally, 23,226 participants without diabetes at baseline and follow-up were selected in this study. △Parameters was defined as the difference between the measurement baseline and follow-up. Multivariable linear regression analysis was used to identify the major determinants of HbA_1c longitudinal change (△HbA_1c). During a mean 3.8 year follow-up, after multivariable analysis, new-onset hypertension (coefficient β: 0.014, p < 0.001), high △heart rate (coefficient β: 0.020, p = 0.002), high △BMI (coefficient β: 0.171, p = 0.028), high △fasting glucose (coefficient β: 0.107, p < 0.001), low △creatinine (coefficient β: −0.042, p < 0.001), high △total cholesterol (coefficient β: 0.040, p < 0.001), high △hemoglobin (coefficient β: 0.062, p < 0.001), high △GPT (coefficient β: 0.041, p = 0.001), and low △albumin (coefficient β: −0.070, p < 0.001) were significantly associated with high △HbA_1c. In non-diabetic population, strategies to decrease the development of new-onset hypertension, resting heart rate, body mass index, fasting glucose, total cholesterol, and GPT and increase serum albumin level might be helpful in slowing the longitudinal change of HbA_1c. In addition, increased hemoglobin and decreased serum creatinine over time also had an impact on the HbA_1c elevation over time in non-diabetic population.