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Kuang HX, Li MY, Zeng XW, Chen D, Zhou Y, Zheng T, Xiang MD, Wu QZ, Chen XC, Dong GH, Yu YJ. Human molybdenum exposure risk in industrial regions of China: New critical effect indicators and reference dose. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 278:116400. [PMID: 38718725 DOI: 10.1016/j.ecoenv.2024.116400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 04/21/2024] [Accepted: 04/24/2024] [Indexed: 05/26/2024]
Abstract
Evidence increasingly suggests molybdenum exposure at environmental levels is still associated with adverse human health, emphasizing the necessity to establish a more protective reference dose (RfD). Herein, we conducted a study measuring 15 urinary metals and 30 clinical health indicators in 2267 participants residing near chemical enterprises across 11 Chinese provinces to investigate their relationships. The kidney and cystatin-C emerged as the most sensitive organ and critical effect indicator of molybdenum exposure, respectively. Odds of cystatin-C-defined chronic kidney disease (CKD) in the highest quantile of molybdenum exposure significantly increased by 133.5% (odds ratio [OR]: 2.34, 95% CI: 1.78, 3.11) and 75.8% (OR: 1.76, 95% CI: 1.24, 2.49) before and after adjusting for urinary 14 metals, respectively. Intriguingly, cystatin-C significantly mediated 15.9-89.5% of molybdenum's impacts on liver and lung function, suggesting nephrotoxicity from molybdenum exposure may trigger hepatotoxicity and pulmonary toxicity. We derived a new RfD for molybdenum exposure (0.87 μg/kg-day) based on cystatin-C-defined estimated glomerular filtration rate by employing Bayesian Benchmark Dose modeling analysis. This RfD is significantly lower than current exposure guidance values (5-30 μg/kg-day). Remarkably, >90% of participants exceeded the new RfD, underscoring the significant health impacts of environmental molybdenum exposure on populations in industrial regions of China.
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Affiliation(s)
- Hong-Xuan Kuang
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China
| | - Meng-Yang Li
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China
| | - Xiao-Wen Zeng
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, PR China
| | - Da Chen
- School of Environment, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 510080, PR China
| | - Yang Zhou
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China
| | - Tong Zheng
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China
| | - Ming-Deng Xiang
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China
| | - Qi-Zhen Wu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, PR China
| | - Xi-Chao Chen
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China
| | - Guang-Hui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, PR China.
| | - Yun-Jiang Yu
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China.
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Qin L, Liu Q, Zhang T, Tang X, Mo X, Liang Y, Wang X, Cao J, Huang C, Lu Y, Zhang Z, Qin J, Cai J. Association Between Combined Polymetallic Exposure and Osteoporosis. Biol Trace Elem Res 2023:10.1007/s12011-023-04002-6. [PMID: 38109003 DOI: 10.1007/s12011-023-04002-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 12/05/2023] [Indexed: 12/19/2023]
Abstract
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.
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Affiliation(s)
- Lidong Qin
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Qiumei Liu
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Tiantian Zhang
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Xu Tang
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Xiaoting Mo
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Yujian Liang
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Xuexiu Wang
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Jiejing Cao
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Chuwu Huang
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Yufu Lu
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Zhiyong Zhang
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
- Department of Environmental Health and Occupational Medicine, School of Public Health, Guilin Medical University, Guilin, China
- Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guilin, China
| | - Jian Qin
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning, China.
- Guangxi Key Laboratory of Environment and Health Research, Guangxi Medical University, Nanning, China.
- Key Laboratory of Longevity and Aging-Related Diseases of Chinese Ministry of Education, Guangxi Medical University, Nanning, China.
| | - Jiansheng Cai
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China.
- Key Laboratory of Tumor Immunology and Microenvironmental Regulation, Guilin Medical University, Huan Cheng North 2Nd Road 109, Guilin, 541004, Guangxi, China.
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Tang P, He W, Shao Y, Liu B, Huang H, Liang J, Liao Q, Tang Y, Mo M, Zhou Y, Li H, Huang D, Liu S, Zeng X, Qiu X. Associations between prenatal multiple plasma metal exposure and newborn telomere length: Effect modification by maternal age and infant sex. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 315:120451. [PMID: 36270567 DOI: 10.1016/j.envpol.2022.120451] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 09/14/2022] [Accepted: 10/14/2022] [Indexed: 06/16/2023]
Abstract
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.
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Affiliation(s)
- Peng Tang
- Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China
| | - Wanting He
- Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China
| | - Yantao Shao
- The Third Affiliated Hospital of Guangxi Medical University, Nanning, 530031, Guangxi, China
| | - Bihu Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China
| | - Huishen Huang
- Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China
| | - Jun Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China
| | - Qian Liao
- Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China
| | - Ying Tang
- Department of Sanitary Chemistry, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China
| | - Meile Mo
- Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China
| | - Yong Zhou
- School of Public Health, Xiangnan University, Chenzhou, 423000, China
| | - Han Li
- Department of Sanitary Chemistry, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China
| | - Dongping Huang
- Department of Sanitary Chemistry, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China
| | - Shun Liu
- Department of Maternal, Child and Adolescent Health, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China
| | - Xiaoyun Zeng
- Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China
| | - Xiaoqiang Qiu
- Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, 530021, Guangxi, China.
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Single and Combined Associations of Plasma and Urine Essential Trace Elements (Zn, Cu, Se, and Mn) with Cardiovascular Risk Factors in a Mediterranean Population. Antioxidants (Basel) 2022; 11:antiox11101991. [PMID: 36290714 PMCID: PMC9598127 DOI: 10.3390/antiox11101991] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 10/01/2022] [Accepted: 10/04/2022] [Indexed: 11/17/2022] Open
Abstract
Trace elements are micronutrients that are required in very small quantities through diet but are crucial for the prevention of acute and chronic diseases. Despite the fact that initial studies demonstrated inverse associations between some of the most important essential trace elements (Zn, Cu, Se, and Mn) and cardiovascular disease, several recent studies have reported a direct association with cardiovascular risk factors due to the fact that these elements can act as both antioxidants and pro-oxidants, depending on several factors. This study aims to investigate the association between plasma and urine concentrations of trace elements and cardiovascular risk factors in a general population from the Mediterranean region, including 484 men and women aged 18−80 years and considering trace elements individually and as joint exposure. Zn, Cu, Se, and Mn were determined in plasma and urine using an inductively coupled plasma mass spectrometer (ICP-MS). Single and combined analysis of trace elements with plasma lipid, blood pressure, diabetes, and anthropometric variables was undertaken. Principal component analysis, quantile-based g-computation, and calculation of trace element risk scores (TERS) were used for the combined analyses. Models were adjusted for covariates. In single trace element models, we found statistically significant associations between plasma Se and increased total cholesterol and systolic blood pressure; plasma Cu and increased triglycerides and body mass index; and urine Zn and increased glucose. Moreover, in the joint exposure analysis using quantile g-computation and TERS, the combined plasma levels of Zn, Cu, Se (directly), and Mn (inversely) were strongly associated with hypercholesterolemia (OR: 2.03; 95%CI: 1.37−2.99; p < 0.001 per quartile increase in the g-computation approach). The analysis of urine mixtures revealed a significant relationship with both fasting glucose and diabetes (OR: 1.91; 95%CI: 1.01−3.04; p = 0.046). In conclusion, in this Mediterranean population, the combined effect of higher plasma trace element levels (primarily Se, Cu, and Zn) was directly associated with elevated plasma lipids, whereas the mixture effect in urine was primarily associated with plasma glucose. Both parameters are relevant cardiovascular risk factors, and increased trace element exposures should be considered with caution.
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