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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 2024; 202:3945-3958. [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] [MESH Headings] [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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Pacheco DA, de Sousa Campêlo AL, de Sousa SES, Sales MC, Sena-Evangelista KCM, Barbosa F, Lima KC, Ferreira MRP, Reis BZ, Pedrosa LFC. Association between exposure to plasma mixture of essential and toxic elements and the lipid profile in institutionalized older adults. J Trace Elem Med Biol 2024; 85:127490. [PMID: 38954873 DOI: 10.1016/j.jtemb.2024.127490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 05/17/2024] [Accepted: 06/19/2024] [Indexed: 07/04/2024]
Abstract
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.
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Affiliation(s)
- Daniela Antunes Pacheco
- Graduate Program in Nutrition, Federal University of Rio Grande do Norte, Av. Senador Salgado Filho, 3000 - Lagoa Nova, Natal, RN CEP: 59078900, Brazil
| | - Angélica Lopes de Sousa Campêlo
- Graduate Program in Nutrition, Federal University of Rio Grande do Norte, Av. Senador Salgado Filho, 3000 - Lagoa Nova, Natal, RN CEP: 59078900, Brazil
| | - Sara Estéfani Soares de Sousa
- Graduate Program in Health Sciences, Federal University of Rio Grande do Norte, Avenida Gustavo Cordeiro de Farias, s/n, Petrópolis, Natal, RN CEP: 59012570, Brazil
| | - Márcia Cristina Sales
- School of Medicine, State University of Roraima, Rua Sete de Setembro, 231, Canarinho, Boa Vista, RR CEP: 69306530, Brazil
| | - Karine Cavalcanti Maurício Sena-Evangelista
- Graduate Program in Nutrition, Federal University of Rio Grande do Norte, Av. Senador Salgado Filho, 3000 - Lagoa Nova, Natal, RN CEP: 59078900, Brazil; Department of Nutrition, Federal University of Rio Grande do Norte, Av. Senador, Salgado Filho, 3000 - Lagoa Nova, Natal, RN CEP: 59078900, Brazil
| | - Fernando Barbosa
- Laboratory of Clinical, Toxicological and Bromatological Analysis, Faculty of Pharmaceutical Sciences, University of São Paulo, Ribeirão Preto, Ribeirão Preto, SP CEP 14040-903, Brazil
| | - Kenio Costa Lima
- Department of Dentistry, Federal University of Rio Grande do Norte, Av. Senador Salgado Filho, 1787 - Lagoa Nova, Natal, RN CEP: 59056000, Brazil
| | - Marcelo Rodrigo Portela Ferreira
- Department of Statistics, Federal University of Paraíba, João Pessoa, Conj. Pres, Castelo Branco III, João Pessoa, PB 58050-585, Brazil
| | - Bruna Zavarize Reis
- Graduate Program in Nutrition, Federal University of Rio Grande do Norte, Av. Senador Salgado Filho, 3000 - Lagoa Nova, Natal, RN CEP: 59078900, Brazil; Department of Nutrition, Federal University of Rio Grande do Norte, Av. Senador, Salgado Filho, 3000 - Lagoa Nova, Natal, RN CEP: 59078900, Brazil
| | - Lucia Fatima Campos Pedrosa
- Graduate Program in Nutrition, Federal University of Rio Grande do Norte, Av. Senador Salgado Filho, 3000 - Lagoa Nova, Natal, RN CEP: 59078900, Brazil; Graduate Program in Health Sciences, Federal University of Rio Grande do Norte, Avenida Gustavo Cordeiro de Farias, s/n, Petrópolis, Natal, RN CEP: 59012570, Brazil; Department of Nutrition, Federal University of Rio Grande do Norte, Av. Senador, Salgado Filho, 3000 - Lagoa Nova, Natal, RN CEP: 59078900, Brazil.
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Zhong J, Yang T, Wang Z, Zhang Y, Shen Y, Hu Y, Hong F. Associations between individual and mixed urinary metal exposure and dyslipidemia among Chinese adults: Data from the China Multi-Ethnic Cohort Study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 282:116696. [PMID: 38986334 DOI: 10.1016/j.ecoenv.2024.116696] [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: 04/07/2024] [Revised: 07/03/2024] [Accepted: 07/04/2024] [Indexed: 07/12/2024]
Abstract
The prevalence of dyslipidemia is increasing, and it has become a significant global public health concern. Some studies have demonstrated contradictory relationships between urinary metals and dyslipidemia, and the combined effects of mixed urinary metal exposure on dyslipidemia remain ambiguous. In this study, we examined how individual and combined urinary metal exposure are associated with the occurrence of dyslipidemia. According to the data from the 2018-2019 baseline survey database of the China Multi-Ethnic Cohort (CMEC) Study, a population of 9348 individuals was studied. Inductively coupled plasmamass spectrometry (ICP-MS) was used to measure 21 urinary metal concentrations in the collected adult urinary samples. The associations between urinary metals and dyslipidemia were analyzed by logistic regression, weighted quantile sum regression (WQS), and quantile-based g-computation (qgcomp), controlled for potential confounders to examine single and combined effects. Dyslipidemia was detected in 3231 individuals, which represented approximately 34.6 % of the total population. According to the single-exposure model, Al and Na were inversely associated with the risk of dyslipidemia (OR = 0.95, 95 % CI: 0.93, 0.98; OR = 0.89, 95 % CI: 0.83, 0.95, respectively), whereas Zn, Ca, and P were positively associated (OR = 1.69, 95 % CI: 1.42, 2.01; OR = 1.12, 95 % CI: 1.06, 1.18; OR = 1.21, 95 % CI: 1.09, 1.34, respectively). Moreover, Zn and P were significantly positively associated even after adjusting for these metals, whereas Al and Cr were negatively associated with the risk of dyslipidemia. The results of the WQS and qgcomp analyses showed that urinary metal mixtures were positively associated with the risk of dyslipidemia (OR = 1.26, 95 % CI: 1.15, 1.38; OR = 1.09, 95 % CI: 1.01, 1.19). This positive association was primarily driven by Zn, P, and Ca. In the sensitivity analyses with collinearity diagnosis, interaction, and stratified analysis, the results remained, confirming the reliability of the study findings. In this study, the individual and combined effects of urinary Zn, P, and Ca on dyslipidemia were determined, which provided novel insights into the link between exposure to metals and dyslipidemia.
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Affiliation(s)
- Jianqin Zhong
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou 561113, China
| | - Tingting Yang
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou 561113, China
| | - Ziyun Wang
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou 561113, China
| | - Yuxin Zhang
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou 561113, China
| | - Yili Shen
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou 561113, China
| | - Yuxin Hu
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou 561113, China
| | - Feng Hong
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou 561113, China.
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4
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Du G, Song X, Zhou F, Ouyang L, Li Q, Ruan S, Su R, Rao S, Zhu Y, Xie J, Feng C, Fan G. Association Between Multiple Metal(loid)s Exposure and Blood Lipid Levels: Evidence from a Cross-Sectional Study of Southeastern China. Biol Trace Elem Res 2024; 202:3483-3495. [PMID: 37991670 DOI: 10.1007/s12011-023-03951-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 11/01/2023] [Indexed: 11/23/2023]
Abstract
Exposure to essential and toxic metals occurs simultaneously as a mixture in real-life. However, there is no consensus regarding the effects of co-exposure to multiple metal(loid)s (designated hereafter metals) on blood lipid levels. Thus, blood concentrations of six human essential metals and five toxic metals in 720 general populations from southeastern China were simultaneously determined as a measure of exposure. In addition, quantile g-computation, Bayesian kernel machine regression, elastic net regression, and generalized linear model were used to investigate both the joint and individual effects of exposure to this metal mixture on human blood lipid levels. The significant positive joint effect of exposure to this metal mixture on serum total cholesterol (TC) levels, rather than on serum triglycerides, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, Castelli risk index I, Castelli risk index II, atherogenic coefficient, and non-HDL-C levels, was found. In addition, the positive effect may be primarily driven by selenium (Se), lead (Pb), and mercury (Hg) exposure. In addition, on the effect of TC levels, the synergistic effect between Pb and Hg and the antagonistic effect between Se and Pb were identified. Our finding suggests that combined exposure to this metal mixture may affect human blood lipid levels. Therefore, reducing exposure to heavy metals, such as Pb and Hg, should be a priority for the general population. In addition, Se supplementation should also be considered with caution.
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Affiliation(s)
- Guihua Du
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang, 330006, People's Republic of China
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, People's Republic of China
| | - Xiaoguang Song
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang, 330006, People's Republic of China
- Institute of Environmental Health, Jiangxi Province Center for Disease Control and Prevention, Nanchang, 330046, People's Republic of China
| | - Fankun Zhou
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang, 330006, People's Republic of China
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, People's Republic of China
| | - Lu Ouyang
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang, 330006, People's Republic of China
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, People's Republic of China
| | - Qi Li
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang, 330006, People's Republic of China
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, People's Republic of China
| | - Shiying Ruan
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang, 330006, People's Republic of China
- The First Affiliated Hospital of Nanchang University, Nanchang, 330006, People's Republic of China
| | - Rui Su
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang, 330006, People's Republic of China
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, People's Republic of China
| | - Shaoqi Rao
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang, 330006, People's Republic of China
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, People's Republic of China
| | - Yanhui Zhu
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang, 330006, People's Republic of China
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, People's Republic of China
| | - Jie Xie
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang, 330006, People's Republic of China
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, People's Republic of China
| | - Chang Feng
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang, 330006, People's Republic of China
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, People's Republic of China
| | - Guangqin Fan
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang, 330006, People's Republic of China.
- Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, People's Republic of China.
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Yim G, Margetaki K, Romano ME, Kippler M, Vafeiadi M, Roumeliotaki T, Bempi V, Farzan SF, Chatzi L, Howe CG. Metal mixture exposures and serum lipid levels in childhood: the Rhea mother-child cohort in Greece. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2024; 34:688-698. [PMID: 38698271 DOI: 10.1038/s41370-024-00674-x] [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: 09/19/2023] [Revised: 04/09/2024] [Accepted: 04/10/2024] [Indexed: 05/05/2024]
Abstract
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.
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Affiliation(s)
- Gyeyoon Yim
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Dartmouth College, Lebanon, NH, USA.
| | - Katerina Margetaki
- Clinic of Preventive Medicine and Nutrition, Faculty of Medicine, University of Crete, Heraklion, Greece
| | - Megan E Romano
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Dartmouth College, Lebanon, NH, USA
| | - Maria Kippler
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Marina Vafeiadi
- Department of Social Medicine, Faculty of Medicine, University of Crete, Heraklion, Greece
| | - Theano Roumeliotaki
- Department of Social Medicine, Faculty of Medicine, University of Crete, Heraklion, Greece
| | - Vicky Bempi
- Department of Social Medicine, Faculty of Medicine, University of Crete, Heraklion, Greece
| | - Shohreh F Farzan
- Department of Population and Public Health Sciences, Division of Environmental Health, University of Southern California, Los Angeles, CA, USA
| | - Leda Chatzi
- Department of Population and Public Health Sciences, Division of Environmental Health, University of Southern California, Los Angeles, CA, USA
| | - Caitlin G Howe
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Dartmouth College, Lebanon, NH, USA
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Zhao L, Wei Y, Liu Q, Cai J, Mo X, Tang X, Wang X, Qin L, Liang Y, Cao J, Huang C, Lu Y, Zhang T, Luo L, Rong J, Wu S, Jin W, Guan Q, Teng K, Li Y, Qin J, Zhang Z. Association between multiple-heavy-metal exposures and systemic immune inflammation in a middle-aged and elderly Chinese general population. BMC Public Health 2024; 24:1192. [PMID: 38679723 PMCID: PMC11057124 DOI: 10.1186/s12889-024-18638-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 04/17/2024] [Indexed: 05/01/2024] Open
Abstract
BACKGROUND Exposure to heavy metals alone or in combination can promote systemic inflammation. The aim of this study was to investigate potential associations between multiple plasma heavy metals and markers of systemic immune inflammation. METHODS Using a cross-sectional study, routine blood tests were performed on 3355 participants in Guangxi, China. Eight heavy metal elements in plasma were determined by inductively coupled plasma mass spectrometry. Immunoinflammatory markers were calculated based on peripheral blood WBC and its subtype counts. A generalised linear regression model was used to analyse the association of each metal with the immunoinflammatory markers, and the association of the metal mixtures with the immunoinflammatory markers was further assessed using weighted quantile sum (WQS) regression. RESULTS In the single-metal model, plasma metal Fe (log10) was significantly negatively correlated with the levels of immune-inflammatory markers SII, NLR and PLR, and plasma metal Cu (log10) was significantly positively correlated with the levels of immune-inflammatory markers SII and PLR. In addition, plasma metal Mn (log10 conversion) was positively correlated with the levels of immune inflammatory markers NLR and PLR. The above associations remained after multiple corrections. In the mixed-metal model, after WQS regression analysis, plasma metal Cu was found to have the greatest weight in the positive effects of metal mixtures on SII and PLR, while plasma metals Mn and Fe had the greatest weight in the positive effects of metal mixtures on NLR and LMR, respectively. In addition, blood Fe had the greatest weight in the negative effects of the metal mixtures for SII, PLR and NLR. CONCLUSION Plasma metals Cu and Mn were positively correlated with immunoinflammatory markers SII, NLR and PLR. While plasma metal Fe was negatively correlated with immunoinflammatory markers SII, NLR, and PLR.
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Affiliation(s)
- Linhai Zhao
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Yanfei Wei
- Department of Epidemiology, School of Public Health (Guangdong Provincial Key Laboratory of Tropical Disease Research), Southern Medical University, Guangzhou, Guangdong, China
| | - Qiumei Liu
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Jiansheng Cai
- School of Public Health, Guilin Medical University, Guilin, Guangxi Zhuang Autonomous Region, China
- Guangxi Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guilin, Guangxi Zhuang Autonomous Region, China
| | - Xiaoting Mo
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Xu Tang
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Xuexiu Wang
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Lidong Qin
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Yujian Liang
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Jiejing Cao
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Chuwu Huang
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Yufu Lu
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Tiantian Zhang
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Lei Luo
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Jiahui Rong
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Songju Wu
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Wenjia Jin
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Qinyi Guan
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Kaisheng Teng
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China
| | - You Li
- School of Public Health, Guilin Medical University, Guilin, Guangxi Zhuang Autonomous Region, China
| | - Jian Qin
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China.
- Guangxi Key Laboratory of Environment and Health Research, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China.
- Key Laboratory of Longevity and Aging-related Diseases of Chinese Ministry of Education, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China.
| | - Zhiyong Zhang
- Department of Occupational and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China.
- School of Public Health, Guilin Medical University, Guilin, Guangxi Zhuang Autonomous Region, China.
- Guangxi Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guilin, Guangxi Zhuang Autonomous Region, China.
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Yu Y, Chen R, Li Z, Luo K, Taylor MP, Hao C, Chen Q, Zhou Y, Kuang H, Hu G, Chen X, Li H, Dong C, Dong GH. Associations of urinary zinc exposure with blood lipid profiles and dyslipidemia: Mediating effect of serum uric acid. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168951. [PMID: 38042193 DOI: 10.1016/j.scitotenv.2023.168951] [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: 09/16/2023] [Revised: 11/25/2023] [Accepted: 11/25/2023] [Indexed: 12/04/2023]
Abstract
The relationship between zinc (Zn) exposure and abnormal blood lipids including dyslipidemia is contentious. Serum uric acid (SUA) has been reported to be correlated to both Zn exposure and dyslipidemia. The underlying mechanisms of Zn exposure associated with blood lipids and the mediating effects of SUA remain unclear. Therefore, this study analyzed the data from Chinese 2110 adults (mean age: 59.0 years old) in rural areas across China to explore the associations of Zn exposure with blood lipid profiles and dyslipidemia, and to further estimate the mediating effects of SUA in these relationships. The study data showed that urinary Zn was associated with increased levels of blood lipid components triglyceride (TG) and low-density lipoprotein cholesterol (LDL-C). Moreover, an increased risk of dyslipidemia was observed in the study participants who had higher urinary Zn levels. Compared with the first quartile, the fourth quartile of urinary Zn concentration corresponded to the increase of TG (β = 0.20, 95 % CI: 0.12, 0.28), LDL-C (β = 0.06, 95 % CI: 0.01, 0.10) and dyslipidemia risk (OR = 2.16, 95 % CI: 1.50, 3.10), respectively. Elevated urinary Zn was also associated with higher levels of SUA and hyperuricemia risk. The SUA levels were positively related to total cholesterol (TC), TG, LDL-C levels and dyslipidemia risk. Mediation analyses revealed that SUA mediated 31.75 %, 46.16 % and 19.25 % of the associations of urinary Zn with TG, LDL-C levels and dyslipidemia risk, respectively. The subgroup and sensitivity analyses confirmed the positive associations between urinary Zn and blood lipid profiles and the mediating effect of SUA. The national population-based study further enhanced our understanding of the associations between Zn exposure and blood lipid profiles and mediating effect of SUA among generally healthy, middle-aged, and elderly individuals.
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Affiliation(s)
- Yunjiang 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, China.
| | - Runan 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, China
| | - Zhenchi 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, China
| | - Kai Luo
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, New York 10461, USA
| | - Mark Patrick Taylor
- Environment Protection Authority Victoria, Centre for Applied Sciences, Melbourne, Victoria 3085, Australia
| | - Chaojie Hao
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China
| | - Qian Chen
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xin Hua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, 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, China
| | - Hongxuan 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, China
| | - Guocheng Hu
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China
| | - Xichao 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, China
| | - Hongyan 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, China
| | - Chenyin Dong
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, 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, China.
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Wang F, Chang L, Zhang X, Jia T, Wang Y, Wang Y, Liu G. Effects of Polycyclic Aromatic Hydrocarbon Exposure and Telomere Length and their Interaction on Blood Lipids in Coal Miners. J Occup Environ Med 2024; 66:111-117. [PMID: 37903596 DOI: 10.1097/jom.0000000000003002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2023]
Abstract
OBJECTIVE This study aimed to investigate the effects of polycyclic aromatic hydrocarbon (PAH) exposure and telomere length on lipids in coal miners. METHODS Basic personal information of 637 coal miners was collected by questionnaire survey. Logistic regression, the Bayesian kernel machine regression model, and weighted quantile sum regression were used to analyze the effects of PAH metabolites and telomere length and their interactions on blood lipids. RESULTS High exposure to 9-hydroxyphenanthrene (OR = 1.586, 95% CI: 1.011-2.487) and telomere shortening (OR = 1.413, 95% CI: 1.005-1.985) were associated with dyslipidemia. Weighted quantile sum results showed that 9-hydroxyphenanthrene accounted for the largest proportion of dyslipidemia (weight = 0.66). The interaction results showed that high 9-hydroxyphenanthrene exposure and short telomeres were risk factors for dyslipidemia in coal miners (OR = 2.085, 95% CI: 1.121-3.879). Conclusions: Our findings suggest that 9-hydroxyphenanthrene and shorter telomeres are risk factors for dyslipidemia, and their interaction increases the risk of dyslipidemia.
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Affiliation(s)
- Fang Wang
- From the Key Laboratory of Coal Environmental Pathogenicity and Prevention (Shanxi Medical University), Ministry of Education, Taiyuan, China (F.W., L.C., X.Z., T.J., Y.W., Y.W.); Department of Epidemiology and Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, China (F.W., L.C., X.Z., T.J., Y.W., Y.W.); and Xishan Coal and Electricity (Group) Co, Ltd, Occupational Disease Prevention and Control Center, Taiyuan, China (G.L.)
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Zhang Z, Wang R, He P, Dai Y, Duan S, Li M, Shen Z, Li X, Sun J. Study on the correlation and interaction between metals and dyslipidemia: a case-control study in Chinese community-dwelling elderly. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:105756-105769. [PMID: 37715907 DOI: 10.1007/s11356-023-29695-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 08/31/2023] [Indexed: 09/18/2023]
Abstract
Previous studies on the association between metals and dyslipidemia are not completely consistent. There are few studies investigating the relationship between mixed metal exposure and dyslipidemia as well as the effects of metals on dyslipidemia in community-dwelling elderly. To evaluate the correlations and interaction effect between the urinary concentrations of metals and the risk of dyslipidemia in community-dwelling elderly. We designed a case-control study to assess the correlation between urine metals and dyslipidemia in elderly people in the Yinchuan. The urinary levels of 13 metals, including calcium, vanadium, iron, cobalt, zinc, copper, arsenic, selenium, molybdenum, cadmium, tellurium, and thallium, were measured by inductively coupled plasma-mass spectrometry (ICP-MS), and the blood biochemical analyzer was used to measure the blood lipid levels of 3384 senior individuals from four different areas of Yinchuan city. Logistic regression and restricted cubic splines (RCS) were used to explore the correlation and dose-response relationship between urinary metals and the risk of dyslipidemia. Least absolute shrinkage and selection operator (LASSO) regression was used to select metals, and then weighted quantile sum (WQS) regression was used to explore the weight of each metal in mixed metals. Bayesian kernel machine regression (BKMR) was used to explore the interactions between metals on dyslipidemia risk. (1) After selection by LASSO regression, in the multi-metal model, compared with the lowest quartile, the adjusted ORs (95%CI) of the highest quartiles were 0.47 (0.37-0.60) for Fe, 1.43 (1.13-1.83) for Zn, 1.46 (1.11-1.92) for As, 0.59 (0.44-0.80) for Se, 1.53 (1.18-2.00) for Mo, and 1.36 (1.07-1.73) for Te. (2) In the WQS regression model, Fe and Mo accounted for the largest weight in the negative and positive effects of dyslipidemia, respectively. (3) In the BKMR model, there may be a positive interaction between Te and Se on dyslipidemia. Among the mixed metals, Fe, As, Se, Mo, and Te were associated with the prevalence of dyslipidemia, with Fe and Mo contributing the most. There may be certain interactions between Te and Se.
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Affiliation(s)
- Zhongyuan Zhang
- School of Public Health, Ningxia Medical University, No.1160, Shengli Street, Xingqing District, Yinchuan, 750004, People's Republic of China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan Ningxia, 750004, People's Republic of China
| | - Rui Wang
- School of Public Health, Ningxia Medical University, No.1160, Shengli Street, Xingqing District, Yinchuan, 750004, People's Republic of China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan Ningxia, 750004, People's Republic of China
| | - Pei He
- School of Public Health, Ningxia Medical University, No.1160, Shengli Street, Xingqing District, Yinchuan, 750004, People's Republic of China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan Ningxia, 750004, People's Republic of China
| | - Yuqing Dai
- School of Public Health, Ningxia Medical University, No.1160, Shengli Street, Xingqing District, Yinchuan, 750004, People's Republic of China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan Ningxia, 750004, People's Republic of China
| | - Siyu Duan
- School of Public Health, Ningxia Medical University, No.1160, Shengli Street, Xingqing District, Yinchuan, 750004, People's Republic of China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan Ningxia, 750004, People's Republic of China
| | - Meiyan Li
- School of Public Health, Ningxia Medical University, No.1160, Shengli Street, Xingqing District, Yinchuan, 750004, People's Republic of China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan Ningxia, 750004, People's Republic of China
| | - Zhuoheng Shen
- School of Public Health, Ningxia Medical University, No.1160, Shengli Street, Xingqing District, Yinchuan, 750004, People's Republic of China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan Ningxia, 750004, People's Republic of China
| | - Xiaoyu Li
- School of Public Health, Ningxia Medical University, No.1160, Shengli Street, Xingqing District, Yinchuan, 750004, People's Republic of China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan Ningxia, 750004, People's Republic of China
| | - Jian Sun
- School of Public Health, Ningxia Medical University, No.1160, Shengli Street, Xingqing District, Yinchuan, 750004, People's Republic of China.
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan Ningxia, 750004, People's Republic of China.
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Liang JH, Pu YQ, Liu ML, Hu LX, Bao WW, Zhang YS, Kakaer A, Zhao Y, Chen YC, Pu XY, Huang SY, Jiang N, Huang S, Dong GH, Chen YJ. Joint effect of whole blood metals exposure with dyslipidemia in representative US adults in NHANES 2011-2020. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:96604-96616. [PMID: 37578581 DOI: 10.1007/s11356-023-28903-0] [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: 03/07/2023] [Accepted: 07/17/2023] [Indexed: 08/15/2023]
Abstract
With little knowledge on the joint effects of metal exposure on dyslipidemia, we aimed to investigate the relationship between exposure to metal and dyslipidemia among US adults based on the National Health and Nutrition Examination Survey (NHANES). Based on the five NHANES waves (2011-2020), we selected five metals in blood as exposure, namely, cadmium (Cd), lead (Pb), total mercury (Hg), manganese (Mn), and selenium (Se), which were detected by inductively coupled plasma mass spectrometry. Survey-multivariable logistic regression, generalized weighted quantile sum (WQS), and Bayesian kernel machine regression (BKMR) were performed to determine whether dyslipidemia was associated with single metals or mixed metals. Our study included 12,526 participants aged from 20 to 80, representing 577.1 million non-institutionalized US adults. We found a positive association between several metals including Pb [adjusted odds ratio (AOR) = 1.332, 95%CI: 1.165, 1.522], total Hg (AOR = 1.264, 95%CI: 1.120, 1.427), Mn (AOR = 1.181, 95%CI: 1.046, 1.334), and Se (AOR = 1.771, 95%CI: 1.576, 1.992) and dyslipidemia. According to the WQS approach, metal mixtures were positively associated with dyslipidemia (AOR: 1.310, 95%CI: 1.216, 1.411) after a full-model adjustment. As is shown in the BKMR model, mixed metals tended to be positively associated with dyslipidemia ratios in a significant manner. Females, non-Hispanic White populations, people aged over 60, and those who did a little physical activity had a greater risk for dyslipidemia. Our findings suggest metals including Cd, Pb, Hg, Mn, and Se and their combinations may adversely affect dyslipidemia among US adults. Due to the cross-sectional nature of the study, it is possible that reverse causation may exist.
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Affiliation(s)
- Jing-Hong Liang
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Ying-Qi Pu
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Mei-Ling Liu
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Li-Xin Hu
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Wen-Wen Bao
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Yu-Shan Zhang
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Aerziguli Kakaer
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Yu Zhao
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Yi-Can Chen
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Xue-Ya Pu
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Shao-Yi Huang
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Nan Jiang
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Shan Huang
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Guang-Hui Dong
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Ya-Jun Chen
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080.
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Choi JE, Bae MJ, Kim MJ, Oh SS, Park KS, Lee CJ, Park S, Koh SB, Cho J, Kim C. Heavy metal exposure linked to metabolic syndrome in Korean male firefighters: FRESH cohort cross-sectional analysis. Sci Rep 2023; 13:14016. [PMID: 37640773 PMCID: PMC10462650 DOI: 10.1038/s41598-023-41158-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 08/22/2023] [Indexed: 08/31/2023] Open
Abstract
This study aimed to identify the relationship between blood lead and Cadmium (Cd) concentrations and metabolic syndromes (MetS), including its components (central obesity, hypertriglyceridemia, low high-density lioioritein, hypertension, and hyperglycemia) among Korean firefighters. A total of 965 firefighters of the Enhancement of Safety and Health cohort were analyzed in this study. MetS was defined according to the 2005 revised National Cholesterol Education Program-Adult Treatment Panel III criteria and the Korean Society for the Study of Obesity criteria for waist circumference. The collected data were analyzed using a logistic regression model. Of the 965 participants, 190 (19.7%) had MetS. After adjusting for age, body mass index, smoking, drinking, exercise, shift duty, and main duty position, the Cd level was significantly associated with an increased risk of MetS in the Korean firefighter population (odds ratio [OR] = 1.62, 95% confidence interval [CI] 1.07, 2.46). This association was significant among non-smokers and ex-smokers (OR = 1.58, 95% CI 1.03, 2.43), non-drinkers and ex-drinkers (OR = 1.77, 95% CI 1.06, 2.94), firefighters aged 40 year or older (OR = 1.77, 95% CI 1.10, 2.86), and office administrators (OR = 3.85, 95% CI 1.42, 10.39). This outcome suggests that exposure to Cd is likely to increase risk of MetS among firefighters.
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Affiliation(s)
- Jee Eun Choi
- Department of Public Health, Yonsei University College of Medicine, Seoul, Korea
- Institute of Human Complexity and Systems Science, Yonsei University, Incheon, Korea
- Institute of East West Studies, Yonsei University, Seoul, Korea
| | - Mun-Joo Bae
- Department of Occupational and Environmental Health, Yonsei University Graduate School, Seoul, Korea
| | - Mi-Ji Kim
- Department of Preventive Medicine and Institute of Health Science, Gyeongsang National University College of Medicine, Jinju, Korea
| | - Sung Soo Oh
- Department of Occupational and Environmental Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea
| | - Ki Soo Park
- Department of Preventive Medicine and Institute of Health Science, Gyeongsang National University College of Medicine, Jinju, Korea
| | - Chan Joo Lee
- Division of Cardiology, Yonsei Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Sungha Park
- Division of Cardiology, Yonsei Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Sang-Baek Koh
- Department of Preventive Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea
| | - Jaelim Cho
- Institute of Human Complexity and Systems Science, Yonsei University, Incheon, Korea.
- Department of Preventive Medicine, Yonsei University College of Medicine, 50-1 Yonsei-Ro, Seodaemun-Gu, Seoul, Republic of Korea.
- Institute for Environmental Research, Yonsei University College of Medicine, Seoul, Korea.
- Department of Public Health, Yonsei University Graduate School, Seoul, Korea.
| | - Changsoo Kim
- Institute of Human Complexity and Systems Science, Yonsei University, Incheon, Korea.
- Department of Preventive Medicine, Yonsei University College of Medicine, 50-1 Yonsei-Ro, Seodaemun-Gu, Seoul, Republic of Korea.
- Institute for Environmental Research, Yonsei University College of Medicine, Seoul, Korea.
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Martins AC, Ferrer B, Tinkov AA, Caito S, Deza-Ponzio R, Skalny AV, Bowman AB, Aschner M. Association between Heavy Metals, Metalloids and Metabolic Syndrome: New Insights and Approaches. TOXICS 2023; 11:670. [PMID: 37624175 PMCID: PMC10459190 DOI: 10.3390/toxics11080670] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 07/26/2023] [Accepted: 07/31/2023] [Indexed: 08/26/2023]
Abstract
Metabolic syndrome (MetS) is an important public health issue that affects millions of people around the world and is growing to pandemic-like proportions. This syndrome is defined by the World Health Organization (WHO) as a pathologic condition characterized by abdominal obesity, insulin resistance, hypertension, and hyperlipidemia. Moreover, the etiology of MetS is multifactorial, involving many environmental factors, including toxicant exposures. Several studies have associated MetS with heavy metals exposure, which is the focus of this review. Environmental and/or occupational exposure to heavy metals are a major risk, contributing to the development of chronic diseases. Of particular note, toxic metals such as mercury, lead, and cadmium may contribute to the development of MetS by altering oxidative stress, IL-6 signaling, apoptosis, altered lipoprotein metabolism, fluid shear stress and atherosclerosis, and other mechanisms. In this review, we discuss the known and potential roles of heavy metals in MetS etiology as well as potential targeted pathways that are associated with MetS. Furthermore, we describe how new approaches involving proteomic and transcriptome analysis, as well as bioinformatic tools, may help bring about an understanding of the involvement of heavy metals and metalloids in MetS.
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Affiliation(s)
- Airton C. Martins
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, New York, NY 10461, USA; (A.C.M.)
| | - Beatriz Ferrer
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, New York, NY 10461, USA; (A.C.M.)
| | - Alexey A. Tinkov
- Laboratory of Ecobiomonitoring and Quality Control, Yaroslavl State University, 150003 Yaroslavl, Russia; (A.A.T.)
- IM Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia
| | - Samuel Caito
- School of Pharmacy, Husson University, Bangor, ME 04401, USA
| | - Romina Deza-Ponzio
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, New York, NY 10461, USA; (A.C.M.)
| | - Anatoly V. Skalny
- Laboratory of Ecobiomonitoring and Quality Control, Yaroslavl State University, 150003 Yaroslavl, Russia; (A.A.T.)
- IM Sechenov First Moscow State Medical University (Sechenov University), 119435 Moscow, Russia
| | - Aaron B. Bowman
- School of Health Sciences, Purdue University, West Lafayette, IN 47907-2051, USA;
| | - Michael Aschner
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, New York, NY 10461, USA; (A.C.M.)
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Chen S, Zhang M, Duan L, Chen M, Du Y, Cao Y, Huang Z, Zhao J, Duan Y. Dose-response relationship of elements with blood lipids and the potential interaction: A cross-sectional study from four areas with different pollution levels in China. J Trace Elem Med Biol 2023; 79:127206. [PMID: 37224743 DOI: 10.1016/j.jtemb.2023.127206] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 04/28/2023] [Accepted: 05/15/2023] [Indexed: 05/26/2023]
Abstract
BACKGROUND A growing number of researches indicated the association between plasma trace elements and blood lipids. However, the potential interaction and dose-response relationship were less frequently reported. METHODS In this study, a total of 3548 participants were recruited from four counties in Hunan Province, South China. Demographic characteristics were collected by face-to-face interviews and inductively coupled plasma mass spectrometry (ICPMS) was used to determine the levels of 23 trace elements in plasma. We applied a fully adjusted generalized linear regression model (GLM) and a multivariate restricted cubic spline (RCS) to estimate the correlation, dose-response relationship and possible interaction between 23 trace elements and four blood lipid markers. RESULTS The results indicated positive dose-response relationships of plasma 66zinc with triglycerides (TG) and low density lipoprotein cholesterol (LDL-C), plasma 78selenium with LDL-C and total cholesterol (TCH), and plasma 59cobalt with high-density lipoprotein cholesterol (HDL-C). There was a negative dose-response relationship between 59cobalt and LDL-C. Further analysis found that 66zinc and 59cobalt had an antagonistic effect on the risk of increased LDL-C level. CONCLUSIONS This study added new evidence for the potential adverse effects of 66Zn and 78Se on blood lipids, and provided new insight into the threshold value setting for metals as well as the intervention strategy for dyslipidemia.
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Affiliation(s)
- Shaoyi Chen
- Department of Occupational and Environmental Health, Xiangya School of Public Health, Central South University, Changsha 410078, China
| | - Muyang Zhang
- Department of Occupational and Environmental Health, Xiangya School of Public Health, Central South University, Changsha 410078, China
| | - Lidan Duan
- Department of Occupational and Environmental Health, Xiangya School of Public Health, Central South University, Changsha 410078, China
| | - Meiling Chen
- Department of Occupational and Environmental Health, Xiangya School of Public Health, Central South University, Changsha 410078, China
| | - Yuwei Du
- Department of Occupational and Environmental Health, Xiangya School of Public Health, Central South University, Changsha 410078, China
| | - Yuhan Cao
- Department of Occupational and Environmental Health, Xiangya School of Public Health, Central South University, Changsha 410078, China
| | - Zhijun Huang
- Center of Clinical Pharmacology, the Third Xiangya Hospital, Central South University, Changsha 410013, China
| | - Jia Zhao
- Environmental Science and Engineering, College of Resource and Environment, Hunan Agricultural University, Changsha 410128, China
| | - Yanying Duan
- Department of Occupational and Environmental Health, Xiangya School of Public Health, Central South University, Changsha 410078, China.
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