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

Interaction between depression and non-essential heavy metals (Cd, Pb, and Hg) on metabolic diseases

OBJECTIVES

Metal exposure and depression have each been associated with adverse metabolic diseases, but no study has examined the potential interaction between them. We examined the interaction of depression on the association between metals and metabolic diseases among adults.

STUDY DESIGN

The interaction of depression in the relationship between metal and metabolic disease in adults was investigated using NHANES, a cross-sectional survey design.

METHODS

By employing data from the NHANES database spanning the years 2007-2018, regression models were employed to investigate the independent impacts of heavy metals (cadmium, lead, and mercury) and depression on metabolic diseases (type 2 diabetes, hypertension, hyperlipidemia, metabolic syndrome). Subsequently, the association between metals and metabolic diseases was explored stratified by depression, and the interaction between heavy metals and depression was explored. Because of the complex NHANES design, statistical evaluations were adjusted through weighting to represent the populace of the United States.

RESULTS

We found log transformed-urinary lead was significantly associated with type 2 diabetes (OR: 2.33; 95 % CI: 1.23, 4.41) in adults with depression. Log transformed-urinary lead was not associated with type 2 diabetes (OR: 0.84; 95 % CI: 0.56, 1.27) in adults without depression. The interaction between Pb and depression in type 2 diabetes was significant (P for interaction = 0.033). Log transformed-urinary lead * depression was significantly associated with type 2 diabetes (OR: 1.82; 95 % CI: 1.01, 3.34) in adults. There was no significant interaction between cadmium and mercury exposure and depression in patients with type 2 diabetes, hypertension, hyperlipidemia, and metabolic syndrome (P for interaction > 0.05).

CONCLUSIONS

The presence of depression positively modified the adverse associations between urinary lead and type 2 diabetes.

Urinary cadmium levels in China (1982-2021): Regional trends and influential factors

Despite the significant threat of cadmium exposure in China, a national-level assessment has been conspicuously absent. This study bridges this critical gap by collecting, geospatial analyzing and multivariable regression analyzing published studies on urinary cadmium levels in Chinese from 1982 to 2021. Our research reveals a notable decline trend in cadmium exposure among Chinese populations. However, this trend varies by region, age and gender group, higher levels are seen in the South (1.04 μg/g cr) compared to the North (0.48 μg/g cr), and in adults (1.08 μg/g cr) relative to children (0.33 μg/g cr), with higher levels being more pronounced in females (6.17 μg/g cr). Urinary cadmium is significantly correlated with rice consumption (P < 0.001), while mining activities have been identified as the dominant factor for cadmium exposure in most regions of China, a trend that is evident both in past decades and is expected to continue into the next decade. These findings underscore the need for region-specific environmental and public health strategies, designed to effectively address the distinct cadmium exposure risks in various regions and among different population groups, thus enhancing protection against the adverse effects of cadmium.

Relationship between blood cadmium levels and bone mineral density in adults: a cross-sectional study

Introduction

Osteoporosis, a disease of reduced bone mass and microstructural deterioration leading to fragility fractures, is becoming more prevalent as aging progresses, significantly increasing the socioeconomic burden. In past studies, there has been a growing awareness of the harmful effects of heavy metals on bone, with cadmium being a significant exposure factor. The purpose of this study was to look into the association between adult bone mineral density(BMD) and blood cadmium levels.

Methods

Based on information from the 2013-2014, 2017-2018 NHANES, weighted multiple regression, generalized weighted modeling, and smoothed curve fitting were utilized to investigate the association between blood cadmium and femur BMD. Furthermore, subgroup analyses were conducted to investigate any differences in the associations between age, sex, race, chronic kidney disease, and diabetes.

Results

In 2,146 participants, blood cadmium levels and total femur [-0.02 (-0.03, -0.01), 0.0027], femoral neck [-0.01 (-0.02, -0.00), 0.0240], femoral trochanter [-0.01 (-0.02, -0.00), 0.0042], and intertrochanteric femoral trochanter [-0.02 (-0.03, -0.00), 0.0101] BMD were negatively correlated. Subgroup analyses showed that this association was more pronounced in women, non-Hispanic white people and other Hispanics, and those with chronic kidney disease and diabetes. Our results pointed to a negative relationship between femoral BMD and blood cadmium. This negative association varied by age, sex, race, diabetes, and chronic kidney disease. In particular, bone mineral density was more significantly negatively affected by blood cadmium levels in groups with diabetes and chronic kidney disease.

Conclusion

Our findings demonstrated a significant negative association between blood cadmium levels and bone mineral density in a population of U.S. adults.

Exposure to cadmium and lead is associated with diabetic kidney disease in diabetic patients

BACKGROUND

Cadmium (Cd) and lead (Pb) exhibit nephrotoxic activity and may accelerate kidney disease complications in diabetic patients, but studies investigating the relation to diabetic kidney disease (DKD) have been limited. We aimed to examine the associations of Cd and Pb with DKD in diabetic patients.

METHODS

3763 adults with blood metal measurements and 1604 adults with urinary ones who were diabetic from National Health and Nutrition Examination Survey (NHANES) 2007-2016 were involved. Multivariate logistic regression models were used to analyze the associations of blood Cd (BCd), blood Pb (BPb), urinary Cd (UCd), and urinary Pb (UPb) with DKD.

RESULTS

BPb, BCd, and UCd levels were higher among participants with DKD than diabetics without nephropathy, but UPb performed the opposite result. BPb and UCd were significantly associated with DKD in the adjusted models (aOR, 1.17 (1.06, 1.29);1.52 (1.06, 2.02)). Participants in the 2nd and 3rd tertiles of BPb and BCd levels had higher odds of DKD, with a significant trend across tertiles, respectively (all P-trend < 0.005). Multiplication interaction was also identified for BPb and BCd (P for interaction = 0.044).

CONCLUSION

BPb, BCd, and UCd were positively associated with the risk of DKD among diabetic patients. Furthermore, there were the dose-response relationship and multiplication interaction in the associations of BPb, BCd with DKD.

Associations of blood cadmium and lead concentrations with all-cause mortality in US adults with chronic obstructive pulmonary disease

BACKGROUND

Some literature indicates an association between exposure to cadmium and lead and the presence of emphysema and chronic bronchitis, which are the two primary components of COPD. Understanding whether there is a potential association between cadmium and lead exposure and higher mortality rates in individuals with COPD could provide profound insights into the long-term effects of these two metal exposures on human health.

METHODS

This study included 2024 patients with COPD in the US from the NHANES from 1999 through 2016 who were followed up to 2019. Multivariable Cox regression models were used to calculate HRs and 95 % CIs for all-cause mortality in relation to blood cadmium and lead concentrations. Plotting Kaplan-Meier curves and Restricted cubic spline curves to visualize results. Furthermore, stratified and sensitivity analyses were conducted.

RESULTS

After multivariate adjustment, blood cadmium and blood lead concentrations were independently associated with an increased risk of all-cause mortality. Compared with the first tertile, the HRs of all-cause mortality associated with the blood cadmium concentration were 1.74 (95 % CI, 1.22-2.49) in the second tertile and 1.89 (95 % CI, 1.31-2.72) in the third tertile. The HRs of all-cause mortality associated with the blood lead concentration were 1.13 (95 % CI, 0.84-1.51) in the second tertile and 1.43 (95 % CI, 1.05-1.93) in the third tertile.

CONCLUSION

This study found that increased blood cadmium and blood lead concentrations were associated with increased all-cause mortality in COPD patients. Reducing cadmium and lead exposure could potentially mitigate mortality risk in these individuals. More prospective studies are needed in the future to demonstrate our findings.

Occurrence and potential release of heavy metals in female underwear manufactured in China: Implication for women's health

Underwear is a potential source of women's exposure to heavy metals owing to its direct contact with the skin, especially the skin of the vagina and vulva, which has a strong absorptive capacity. However, information regarding the prevalence of metals in female underwear, and its potential hazards, remains scarce. In the present study, we examined the concentrations and potential release of Cr, Co, Ni, Cu, As, Cd, Sb, and Pb in brassieres and briefs manufactured in China. We detected higher levels of Pb and moderate levels of other metals, relative to the metal levels reported for other textiles in the literature. Cu, As, Ni and Cd, had higher migration rates (MRs) from the underwear, with medians of 100%, 100%, 30.1%, and 20.7%, respectively. The median MRs of the other metals were in the range 1.07%-15.7%. On the whole, the total and extractable concentrations of these metals differed by item and fabric type. The pollution of raw materials and the use of chemical additives containing metals commonly contributed to the metals in the underwear. On the basis of the exposure estimation, the non-carcinogenic risks posed by the underwear metals were acceptable, but the carcinogenic risks from the metals in 5.18% of brassiere samples exceeded the acceptable level.

Human exposure to heavy metals and related cancer development: a bibliometric analysis

As notifications on carcinogenicity of heavy metals increase, more and more attention is paid recently to heavy metals exposure. In our study, the human exposure to heavy metals and cancer knowledge epistemology was investigated using bibliometric analysis. The bibliometric data of the research articles were retrieved using following keywords: "heavy metal," "trace element", "cancer", "carcinogen", and "tumor" in the Scopus database. Specifically, 2118 articles published between 1972 and 2023 were found, covering a total of 1473 authors, 252 sources, and 2797 keywords. Retrospective data obtained from 251 documents and 145 journals were further analyzed by performance analysis and techniques of science mapping. The number of studies conducted in this field increased from one article published in 1972 to 18 articles published in 2022 in the study of Michael P Waalkes. The most impactful author regarding the number of published papers was Masoudreza Sohrabi with 7 publications. In the majority of the published papers, the most popular keywords were "cadmium" and "carcinogenicity". However, in recent 4 years, the emphasis has been placed more on epidemiology studies. Our study provides general knowledge about the trend of publication on the role of heavy metals in causing cancer. The leading researchers in the field of the effects of heavy metals on the development of cancer were identified in our studies. Our results might also create a better understanding of new and emerging issues and can be used as a comprehensive road map for future researchers.

Emerging micropollutants in aquatic ecosystems and nanotechnology-based removal alternatives: A review

There is a significant concern about the accessibility of uncontaminated and safe drinking water, a fundamental necessity for human beings. This concern is attributed to the toxic micropollutants from several emission sources, including industrial toxins, agricultural runoff, wastewater discharges, sewer overflows, landfills, algal blooms and microbiota. Emerging micropollutants (EMs) encompass a broad spectrum of compounds, including pharmaceutically active chemicals, personal care products, pesticides, industrial chemicals, steroid hormones, toxic nanomaterials, microplastics, heavy metals, and microorganisms. The pervasive and enduring nature of EMs has resulted in a detrimental impact on global urban water systems. Of late, these contaminants are receiving more attention due to their inherent potential to generate environmental toxicity and adverse health effects on humans and aquatic life. Although little progress has been made in discovering removal methodologies for EMs, a basic categorization procedure is required to identify and restrict the EMs to tackle the problem of these emerging contaminants. The present review paper provides a crude classification of EMs and their associated negative impact on aquatic life. Furthermore, it delves into various nanotechnology-based approaches as effective solutions to address the challenge of removing EMs from water, thereby ensuring potable drinking water. To conclude, this review paper addresses the challenges associated with the commercialization of nanomaterial, such as toxicity, high cost, inadequate government policies, and incompatibility with the present water purification system and recommends crucial directions for further research that should be pursued.

Exploring the association of metal mixture in blood to the kidney function and tumor necrosis factor alpha using machine learning methods

This research aimed to approach relationships between metal mixture in blood and kidney function, tumor necrosis factor alpha (TNF-α) by machine learning. Metals levels were measured by Inductively Couple Plasma Mass Spectrometry in blood from 421 participants. We applied K Nearest Neighbor (KNN), Naive Bayes classifier (NB), Support Vector Machines (SVM), random forest (RF), Gradient Boosting Decision Tree (GBDT), Categorical boosting (CatBoost), eXtreme Gradient Boosting (XGBoost), Whale Optimization-based XGBoost (WXGBoost) to identify the effect of plasma metals, TNF-α, and estimated glomerular filtration rate (eGFR by CKD-EPI equation). We conducted not only toxic metals, lead (Pb), arsenic (As), cadmium (Cd) but also included trace essential metals, selenium (Se), copper (Cu), zinc (Zn), cobalt (Co), to predict the interaction of TNF-α, TNF-α/white blood count, and eGFR. The high average TNF-α level group was observed among subjects with higher Pb, As, Cd, Cu, and Zn levels in blood. No associations were shown between the low and high TNF-α level group in blood Se and Co levels. Those with lower eGFR group had high Pb, As, Cd, Co, Cu, and Zn levels. The crucial predictor of TNF-α level in metals was blood Pb, and then Cd, As, Cu, Se, Zn and Co. The machine learning revealed that As was the major role among predictors of eGFR after feature selection. The levels of kidney function and TNF-α were modified by co-exposure metals. We were able to acquire highest accuracy of over 85% in the multi-metals exposure model. The higher Pb and Zn levels had strongest interaction with declined eGFR. In addition, As and Cd had synergistic with prediction model of TNF-α. We explored the potential of machine learning approaches for predicting health outcomes with multi-metal exposure. XGBoost model added SHAP could give an explicit explanation of individualized and precision risk prediction and insight of the interaction of key features in the multi-metal exposure.

Effects of heavy metal exposure on hypertension: A machine learning modeling approach

Heavy metal exposure is a common risk factor for hypertension. To develop an interpretable predictive machine learning (ML) model for hypertension based on levels of heavy metal exposure, data from the NHANES (2003-2016) were employed. Random forest (RF), support vector machine (SVM), decision tree (DT), multilayer perceptron (MLP), ridge regression (RR), AdaBoost (AB), gradient boosting decision tree (GBDT), voting classifier (VC), and K-nearest neighbour (KNN) algorithms were utilized to generate an optimal predictive model for hypertension. Three interpretable methods, the permutation feature importance analysis, partial dependence plot (PDP), and Shapley additive explanations (SHAP) methods, were integrated into a pipeline and embedded in ML for model interpretation. A total of 9005 eligible individuals were randomly allocated into two distinct sets for predictive model training and validation. The results showed that among the predictive models, the RF model demonstrated the highest performance, achieving an accuracy rate of 77.40% in the validation set. The AUC and F1 score for the model were 0.84 and 0.76, respectively. Blood Pb, urinary Cd, urinary Tl, and urinary Co levels were identified as the main influencers of hypertension, and their contribution weights were 0.0504 ± 0.0482, 0.0389 ± 0.0256, 0.0307 ± 0.0179, and 0.0296 ± 0.0162, respectively. Blood Pb (0.55-2.93 μg/dL) and urinary Cd (0.06-0.15 μg/L) levels exhibited the most pronounced upwards trend with the risk of hypertension within a specific value range, while urinary Tl (0.06-0.26 μg/L) and urinary Co (0.02-0.32 μg/L) levels demonstrated a declining trend with hypertension. The findings on the synergistic effects indicated that Pb and Cd were the primary determinants of hypertension. Our findings underscore the predictive value of heavy metals for hypertension. By utilizing interpretable methods, we discerned that Pb, Cd, Tl, and Co emerged as noteworthy contributors within the predictive model.

Associations of urinary and blood cadmium concentrations with all-cause mortality in US adults with chronic kidney disease: a prospective cohort study

Epidemiological evidence for the relationship between cadmium exposure and mortality in specific chronic kidney disease (CKD) populations remains scarce. We aimed to explore the relationships between cadmium concentrations in urine and blood and all-cause mortality among CKD patients in the USA. This cohort study was composed of 1825 CKD participants from the National Health and Nutrition Examination Survey (NHANES) (1999-2014) who were followed up to December 31, 2015. All-cause mortality was ascertained by matching the National Death Index (NDI) records. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause mortality in relation to urinary and blood cadmium concentrations by Cox regression models. During an average follow-up period of 82 months, 576 CKD participants died. Compared with the lowest quartiles, HRs (95% CIs) for all-cause mortality associated with the fourth weighted quartiles of urinary and blood cadmium concentrations were 1.75 (1.28 to 2.39) and 1.59 (1.17 to 2.15), respectively. Furthermore, the HRs (95% CIs) for all-cause mortality per ln-transformed IQR increment in cadmium concentrations in urine (1.15 μg/g U_Cr) and blood (0.95 μg/L) were 1.40 (1.21 to 1.63) and 1.22 (1.07 to 1.40), respectively. Linear concentration-response relationships between urinary and blood cadmium concentrations and all-cause mortality were also found. Our findings suggested that increased cadmium concentrations in both urine and blood significantly contributed to enhanced mortality risk in CKD patients, thus highlighting that efforts to reduce cadmium exposure may reduce mortality risk in high-risk populations with CKD.

Association of Urinary Lead and Cadmium Levels, and Serum Lipids with Subclinical Arteriosclerosis: Evidence from Taiwan

BACKGROUND

Exposure to lead and cadmium has been linked to changes in lipid metabolism and the development of arteriosclerosis, but the role of lipoprotein profiles in this relationship is not well understood, including the potential role of novel lipid biomarkers.

METHODS

In this study, we enrolled 736 young Taiwanese subjects aged 12 to 30 years to assess the correlation between urine levels of lead and cadmium, lipoprotein profiles, and carotid intima-media thickness (CIMT).

RESULTS

Higher levels of lead and cadmium were significantly associated with higher levels of low-density lipoprotein cholesterol (LDL-C), small dense LDL-C (sdLDL-C), LDL-triglyceride (LDL-TG), and CIMT. Participants with higher levels of lead and cadmium had the highest mean values of CIMT, LDL-C, sdLDL-C, and LDL-TG. In a structural equation model, lead had a direct and indirect association with CIMT through LDL-C and sdLDL-C, whereas cadmium had a direct association with CIMT and an indirect association through LDL-C.

CONCLUSION

Our results suggest higher levels of lead and cadmium are associated with abnormal lipid profiles and increased CIMT. These heavy metals could have additive effects on lipids and CIMT, and the relationship between them may be mediated by lipoprotein levels. Further research is needed to determine the causal relationship.