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Stanek LW, Grokhowsky N, George BJ, Thomas KW. Assessing lead exposure in U.S. pregnant women using biological and residential measurements. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 905:167135. [PMID: 37739076 PMCID: PMC11351066 DOI: 10.1016/j.scitotenv.2023.167135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 09/14/2023] [Accepted: 09/14/2023] [Indexed: 09/24/2023]
Abstract
There is strong scientific evidence for multiple pathways of human exposure to lead (Pb) in residential settings, particularly for young children; however, less is known about maternal exposure during pregnancy and children's exposure during early lifestages. A robust, multi-faceted secondary analysis was conducted using data collected by the National Institute of Child Health and Human Development in the 2009-2014 National Children's Study Vanguard Studies. Descriptive statistics summarized Pb concentrations of maternal blood, maternal urine, and house dust vacuum samples collected during pregnancy and residence surface wipes collected both during pregnancy and six months post-partum. The maternal blood Pb level geometric mean was 0.44 μg/dL (n = 426), with no women having values ≥ 5 μg/dL; creatinine-adjusted maternal urinary Pb geometric mean was 0.43 μg/g (n = 366). These blood and urine concentrations are similar to those observed for females in the general U.S. population in the National Health and Nutrition Examination Survey 2010-2011 cycle. A modest correlation between maternal blood Pb and surface wipe measurements during pregnancy was observed (Spearman r = 0.35, p < 0.0001). Surface wipe Pb loadings obtained in mother's homes during pregnancy (n = 640) and from areas where children spent the most time at roughly 6 months of age (n = 99) ranged from 0.02 to 71.8 ng/cm2, with geometric means of 0.47 and 0.49 ng/cm2, respectively, which were relatively low compared to other national studies. Survey responses of demographic, lifestyle, and residence characteristics were assessed for associations with blood concentration and surface wipe loading. Demographic (e.g., race/ethnicity, income, education, marital status) and housing characteristics (e.g., year home built, paint condition, own or rent home, attached garage) were associated with both maternal blood and surface wipe loadings during pregnancy. The availability of residential environmental media and extensive survey data provided enhanced understanding of Pb exposure during pregnancy and early life.
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Affiliation(s)
- Lindsay W Stanek
- U.S. Environmental Protection Agency (EPA), Office of Research and Development (ORD), Research Triangle Park, NC, USA.
| | - Nicholas Grokhowsky
- Formerly of Oak Ridge Institute for Science and Education, Research Triangle Park, NC, USA
| | - Barbara J George
- U.S. Environmental Protection Agency (EPA), Office of Research and Development (ORD), Research Triangle Park, NC, USA
| | - Kent W Thomas
- U.S. Environmental Protection Agency (EPA), Office of Research and Development (ORD), Research Triangle Park, NC, USA
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Li Y, Zhang L, Liu J, Wu M, Li C, Yang J, Wang L. Environmental concentrations of cadmium and zinc and associating metabolomics profile alternations in urine of pregnant women in the first trimester: A prospective cohort study in Taiyuan, North China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 267:115611. [PMID: 37897977 DOI: 10.1016/j.ecoenv.2023.115611] [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: 07/10/2023] [Revised: 10/13/2023] [Accepted: 10/15/2023] [Indexed: 10/30/2023]
Abstract
especially to pregnant women. In recent years, zinc (Zn) supplementation has attracted increasing attention among pregnant women. Thus, understanding the effects and interactions of Cd and Zn in pregnant women is critical. This study aimed to assess the urinary levels of Cd and Zn in pregnant women during early pregnancy, examine associated alterations in urine metabolomics, and identify potential metabolic biomarkers among distinct Cd and Zn groups. Urine samples from 185 pregnant women were collected, and inductively coupled plasma mass spectrometry (ICP-MS) was used to detect Cd and Zn contents. The women were then divided into four groups according to median contents of Cd and Zn. Alterations in the metabolite profile were assessed using a liquid chromatograph mass spectrometer (LC-MS). The results showed that the gravidity of pregnant women was closely related to urinary Cd levels and that the urinary Zn contents of pregnant women with morning sickness in the first trimester were lower than that of non-morning-sick pregnant women. A total of 51 metabolites exhibited significant differential expression in the high level of Cd and Zn (HCdHZn) compared with low level of Cd and Zn (LCdLZn), the diagnostic performance of these 51 metabolites were assessed using receiver operating characteristic curve analysis and revealed that octadecylamine was a promising diagnostic indicator for evaluating the combined effects of Zn and Cd. Metabolomics analysis showed that the arginine and proline pathways were upregulated in HCdHZn compared with that in LCdLZn, suggesting a potential risk of obesity. Although higer levels of bovinic acid in HCdHZn vs. HCdLZn (high level of Cd and low level of Zn) indicated that Zn has antioxidant and anti-inflammatory properties, excessive Zn may still cause harmful effect to the human health and should be supplemented with caution. The study findings may be valuable for potential risk ahissessment of the combined effects of Cd-Zn and their interactions in pregnant women.
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Affiliation(s)
- Yingjun Li
- Department of Child and Adolescent Health, School of Public Health, Shanxi Medical University, Taiyuan 030001, China
| | - Liuyuan Zhang
- Department of Child and Adolescent Health, School of Public Health, Shanxi Medical University, Taiyuan 030001, China
| | - Jin Liu
- Department of Child and Adolescent Health, School of Public Health, Shanxi Medical University, Taiyuan 030001, China
| | - Meiqiong Wu
- Department of Child and Adolescent Health, School of Public Health, Shanxi Medical University, Taiyuan 030001, China
| | - Changqing Li
- Taiyuan Center for Disease Control and Prevention, Taiyuan 030000, China
| | - Jia Yang
- Department of prevention and health care, Shanxi Provincial Children's Hospital, Taiyuan 030013, China
| | - Li Wang
- Department of Child and Adolescent Health, School of Public Health, Shanxi Medical University, Taiyuan 030001, China.
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3
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Wang Z, Dou Y, Guo W, Lin Y, Jiang Y, Jiang T, Qin R, Lv H, Lu Q, Jin G, Ma H, Hu Z, Liu H, Du J. Association between prenatal exposure to trace elements mixture and visual acuity in infants: A prospective birth cohort study. CHEMOSPHERE 2023; 333:138905. [PMID: 37187369 DOI: 10.1016/j.chemosphere.2023.138905] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 05/06/2023] [Accepted: 05/08/2023] [Indexed: 05/17/2023]
Abstract
BACKGROUND Prenatal environmental factors may affect the development of the offspring and can bring long lasting consequences to the offspring's health. To date, only few studies have reported inconclusive association between prenatal single trace element exposure and visual acuity, and no studies have investigated the association between prenatal exposure to trace elements mixture and visual acuity in infants. METHODS In the prospective cohort study, grating acuity in infants (12 ± 1 months) was measured by Teller Acuity Cards II. Concentrations of 20 trace elements in maternal urine samples collected in early-trimester were measured by Inductively Coupled Plasma Mass Spectrometry. Elastic net regression (ENET) was applied to select important trace elements. Nonlinear associations of the trace elements levels with abnormal grating were explored using the restricted cubic spline (RCS) method. The associations between selected individual elements and abnormal grating acuity were further appraised using the logistic regression model. Then Bayesian Kernel Machine Regression (BKMR) was used to estimate the joint effects of mixture and interactions between trace elements combining with NLinteraction. RESULTS Of 932 mother-infant pairs, 70 infants had abnormal grating acuity. The ENET model produced 8 trace elements with non-zero coefficients, including cadmium, manganese, molybdenum, nickel, rubidium, antimony, tin and titanium. RCS analyses identified no nonlinear associations of the 8 elements with abnormal grating acuity. The single-exposure analyses using logistic regression revealed that prenatal molybdenum exposure possessed a significantly positive association with abnormal grating acuity (odds ratio [OR]: 1.44 per IQR increase, 95% confidence interval [CI]: 1.05, 1.96; P = 0.023), while prenatal nickel exposure presented with a significantly inverse association with abnormal grating acuity (OR: 0.64 per IQR increase, 95% CI: 0.45, 0.89; P = 0.009). Similar effects were also observed in BKMR models. Moreover, the BKMR models and NLinteraction method identified potential interaction between molybdenum and nickel. CONCLUSIONS We established that prenatal exposure to high concentration of molybdenum and low concentration of nickel was associated with the increased risk of abnormal visual acuity. Potential interaction may exist between molybdenum and nickel on abnormal visual acuity.
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Affiliation(s)
- Zijin Wang
- Department of Ophthalmology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, China; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Yuanyan Dou
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Wenhui Guo
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Yuan Lin
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Maternal, Child and Adolescent Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, Jiangsu, China
| | - Yangqian Jiang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Maternal, Child and Adolescent Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Tao Jiang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Rui Qin
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Hong Lv
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, Jiangsu, China
| | - Qun Lu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Maternal, Child and Adolescent Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Guangfu Jin
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, Jiangsu, China
| | - Hongxia Ma
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, Jiangsu, China
| | - Zhibin Hu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, Jiangsu, China.
| | - Hu Liu
- Department of Ophthalmology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, China.
| | - Jiangbo Du
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, Jiangsu, China.
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Frndak S, Yan F, Edelson M, Immergluck LC, Kordas K, Idris MY, Dickinson-Copeland CM. Predicting Low-Level Childhood Lead Exposure in Metro Atlanta Using Ensemble Machine Learning of High-Resolution Raster Cells. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:4477. [PMID: 36901487 PMCID: PMC10002062 DOI: 10.3390/ijerph20054477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 02/24/2023] [Accepted: 02/27/2023] [Indexed: 06/18/2023]
Abstract
Low-level lead exposure in children is a major public health issue. Higher-resolution spatial targeting would significantly improve county and state-wide policies and programs for lead exposure prevention that generally intervene across large geographic areas. We use stack-ensemble machine learning, including an elastic net generalized linear model, gradient-boosted machine, and deep neural network, to predict the number of children with venous blood lead levels (BLLs) ≥2 to <5 µg/dL and ≥5 µg/dL in ~1 km2 raster cells in the metro Atlanta region using a sample of 92,792 children ≤5 years old screened between 2010 and 2018. Permutation-based predictor importance and partial dependence plots were used for interpretation. Maps of predicted vs. observed values were generated to compare model performance. According to the EPA Toxic Release Inventory for air-based toxic release facility density, the percentage of the population below the poverty threshold, crime, and road network density was positively associated with the number of children with low-level lead exposure, whereas the percentage of the white population was inversely associated. While predictions generally matched observed values, cells with high counts of lead exposure were underestimated. High-resolution geographic prediction of lead-exposed children using ensemble machine learning is a promising approach to enhance lead prevention efforts.
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Affiliation(s)
- Seth Frndak
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY 14260, USA
| | - Fengxia Yan
- Department of Community Health and Preventive Medicine, Morehouse School of Medicine, Atlanta, GA 30310, USA
| | - Mike Edelson
- Geographic Information Systems, InterDev, Roswell, GA 30076, USA
| | - Lilly Cheng Immergluck
- Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, Atlanta, GA 30310, USA
| | - Katarzyna Kordas
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY 14260, USA
| | - Muhammed Y. Idris
- Department of Medicine, Morehouse School of Medicine, Atlanta, GA 30310, USA
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Zhang X, Chiu YHM, Kannan S, Cowell W, Deng W, Coull BA, Wright RO, Wright RJ. Joint associations among prenatal metal mixtures and nutritional factors on birth weight z-score: Evidence from an urban U.S. population. ENVIRONMENTAL RESEARCH 2022; 208:112675. [PMID: 34995543 PMCID: PMC8916990 DOI: 10.1016/j.envres.2022.112675] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 12/16/2021] [Accepted: 01/03/2022] [Indexed: 05/17/2023]
Abstract
The benefits of nutritional factors on birth outcomes have been recognized, however, limited studies have examined the role of nutritional factors in mitigating the detrimental effects of metals exposure during gestation. We used data collected from 526 mother-infant dyads enrolled in the Programming of Intergenerational Stress Mechanisms longitudinal pregnancy cohort to examine the joint effects of prenatal exposure to metals and maternal nutrition on birth weight for gestational age (BWGA) z-scores. We measured concentrations of twelve metals and trace elements in urine samples collected during pregnancy. Maternal nutritional intake was measured using the Block98 Food Frequency Questionnaire and converted into energy-adjusted consumption of individual nutrients. Using multivariable linear regression and Bayesian Kernel Machine Regression, we found that three metals [cobalt (Co), nickel (Ni), and lead (Pb)] and five metals [barium (Ba), caesium (Cs), copper (Cu), Ni, and zinc (Zn)] were associated with BWGA z-score in male and female infants, respectively. When examining the sex-specific interactions between these metals and nutrient groups [macro nutrients, minerals, A vitamins, B vitamins, anti-oxidant, methyl-donor nutrients, and inflammatory (pro- and anti-)] using a Cross-validated Kernel Ensemble model, we identified significant interactions between the macro nutrients and Co (p = 0.05), minerals and Pb (p = 0.04), and A vitamins and Ni (p = 0.001) in males. No significant interactions were found in females. Furthermore, three minerals (phosphorus, iron, potassium) and vitamin A were found to be more crucial than other nutrients in modifying the association between each respective metal and BWGA z-score in males. A better understanding of the sex-specific interactions between nutrients and metals on birth weight can guide pregnant women to protect their neonates from the adverse health impacts of metal exposures by optimizing nutrient intakes accordingly.
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Affiliation(s)
- Xueying Zhang
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Yueh-Hsiu Mathilda Chiu
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Srimathi Kannan
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Whitney Cowell
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Wenying Deng
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Brent A Coull
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Robert O Wright
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rosalind J Wright
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Geron M, Cowell W, Amarasiriwardena C, Andra SS, Carroll K, Kloog I, Wright RO, Wright RJ. Racial/ethnic and neighborhood disparities in metals exposure during pregnancy in the Northeastern United States. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 820:153249. [PMID: 35065119 PMCID: PMC8930522 DOI: 10.1016/j.scitotenv.2022.153249] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 01/13/2022] [Accepted: 01/14/2022] [Indexed: 05/12/2023]
Abstract
Despite the unequal burden of environmental exposures borne by racially minoritized communities, these groups are often underrepresented in public health research. Here, we examined racial/ethnic disparities in exposure to metals among a multi-ethnic sample of pregnant women. The sample included women enrolled in the PRogramming of Intergenerational Stress Mechanisms (PRISM) pregnancy cohort (N = 382). Urinary metal concentrations (arsenic [As], barium [Ba], cadmium [Cd], cesium [Cs], chromium [Cr], lead [Pb], antimony [Sb]) were measured during mid-pregnancy and information on individual- and neighborhood-level characteristics was ascertained during an in-person interview and from publicly available databases, respectively. Linear regression was used to examine individual and neighborhood characteristics in relation to metal concentrations. Black/Black-Hispanic women had Cd, Cr, Pb, and Sb levels that were 142.0%, 10.9%, 35.0%, and 32.1% higher than White, non-Hispanic women, respectively. Likewise, White-Hispanic women had corresponding levels that were 141.5%, 108.2%, 59.9%, and 38.3% higher. These same metals were also higher among women residing in areas with higher crime, higher diversity, lower educational attainment, lower household income, and higher poverty. Significant disparities in exposure to metals exist and may be driven by neighborhood-level factors. Exposure to metals for pregnant women can be especially harmful. Understanding exposure inequalities and identifying factors that increase risk can help inform targeted public health interventions.
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Affiliation(s)
- Mariel Geron
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Whitney Cowell
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Chitra Amarasiriwardena
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Syam S Andra
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kecia Carroll
- Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Kravis Children's Hospital, Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Itai Kloog
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert O Wright
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rosalind J Wright
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Kravis Children's Hospital, Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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Liu J, Ruan F, Cao S, Li Y, Xu S, Xia W. Associations between prenatal multiple metal exposure and preterm birth: Comparison of four statistical models. CHEMOSPHERE 2022; 289:133015. [PMID: 34822868 DOI: 10.1016/j.chemosphere.2021.133015] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Revised: 10/19/2021] [Accepted: 11/18/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Exposure to some heavy metals has been demonstrated to be related to the risk of preterm birth (PTB). However, the effects of multi-metal mixture are seldom assessed. Thus, we aimed to investigate the associations of maternal exposure to metal mixture with PTB, and to identify the main contributors to PTB from the mixture. METHODS The population in the nested case-control study was from a prospective cohort enrolled in Wuhan, China between 2012 and 2014. Eighteen metals were measured in maternal urine collected before delivery. Logistic regression, elastic net regularization (ENET), weighted quantile sum regression (WQSR), and Bayesian kernel machine regression (BKMR) were used to estimate the overall effect and identify important mixture components that drive the associations with PTB. RESULTS Logistic regression found naturally log-transformed concentrations of 13 metals were positively associated with PTB after adjusting for the covariates, and only V, Zn, and Cr remained the significantly positive associations when additionally adjusting for the 13 metals together. ENET identified 11 important metals for PTB, and V (β = 0.23) had the strongest association. WQSR determined the positive combined effect of metal mixture on PTB (OR: 1.44, 95%CI: 1.32, 1.57), and selected Cr and V (weighted 0.41 and 0.32, respectively) as the most weighted metals. BKMR analysis confirmed the overall mixture was positively associated with PTB, and the independent effect of V was the most significant. Besides, BKMR showed the non-linear relationships of V and Cu with PTB, and the potential interaction between Zn and Cu. CONCLUSION Applying different statistical models, the study found that exposure to the metal mixture was associated with a higher risk of PTB, and V was identified as the most important risk factor among co-exposed metals for PTB.
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Affiliation(s)
- Juan Liu
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, 430030, Hubei, PR China.
| | - Fengyu Ruan
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, 430030, Hubei, PR China.
| | - Shuting Cao
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, 430030, Hubei, PR China.
| | - Yuanyuan Li
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, 430030, Hubei, PR China.
| | - Shunqing Xu
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, 430030, Hubei, PR China.
| | - Wei Xia
- State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, 430030, Hubei, PR China.
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Wang X, Zhou M, Xiao L, Xu T, Yang S, Nie X, Xie L, Yu L, Mu G, Ma J, Chen W. Systemic inflammation mediates the association of heavy metal exposures with liver injury: A study in general Chinese urban adults. JOURNAL OF HAZARDOUS MATERIALS 2021; 419:126497. [PMID: 34323735 DOI: 10.1016/j.jhazmat.2021.126497] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 05/31/2021] [Accepted: 06/17/2021] [Indexed: 06/13/2023]
Abstract
Heavy metal exposures have been reported to be associated with increased risk for liver injury. However, the potential mechanisms of the association remain unclear. A repeated-measure study of 9367 observations was conducted to quantify the associations of urinary heavy metals with serum alanine aminotransferase (ALT), a biomarker for liver injury, and assess the mediating role of systemic inflammation in such associations among general Chinese adults. In single-metal models, positive dose-response relationships between urinary vanadium (V), chromium (Cr), copper (Cu), arsenic (As), cadmium (Cd), tungsten (W), and lead (Pb) and serum ALT were observed. In the multiple-metal model containing the seven metals mentioned above, V and Cu remained positively associated with ALT. In longitudinal analyses of 3-6 years, each 1-unit increase in log-transformed levels of V and Cu was associated with an additional rate of annual ALT increase (95% CI) for 1.3% (0.7-1.8%) and 1.3% (0.7-2.0%), respectively. Plasma CRP concentrations were not only positively associated with urinary Cu and Cd, but also positively related with ALT. Furthermore, mediation analyses showed that CRP mediated 4.70% and 7.03% of urinary Cu- and Cd-associated ALT elevations. Our study provides clues for the prevention of heavy metal-induced liver injury.
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Affiliation(s)
- Xing Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Min Zhou
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Lili Xiao
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Tao Xu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Shijie Yang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Xiuquan Nie
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Li Xie
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Linling Yu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Ge Mu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Jixuan Ma
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
| | - Weihong Chen
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
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9
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Li C, Wu C, Zhang J, Li Y, Zhang B, Zhou A, Liu W, Chen Z, Li R, Cao Z, Xia W, Xu S. Associations of prenatal exposure to vanadium with early-childhood growth: A prospective prenatal cohort study. JOURNAL OF HAZARDOUS MATERIALS 2021; 411:125102. [PMID: 33461012 DOI: 10.1016/j.jhazmat.2021.125102] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 01/05/2021] [Accepted: 01/07/2021] [Indexed: 06/12/2023]
Abstract
Prenatal vanadium exposure is reported to be associated with restricted fetal growth and adverse birth outcomes. However, trimester-specific vanadium exposure in relation to early-childhood growth still remains unclear. A total of 1873 Chinese mother-infant pairs from whom a complete series of maternal urinary samples were collected over three stages of pregnancy were included from 2014 to 2016. The urinary concentrations of vanadium were analyzed. Children's anthropometric parameters were measured at birth, 6, 12 and 24 months. In boys, each doubling increase in vanadium concentrations at middle pregnancy was inversely associated with weight-for-length [- 9.07% (-17.21%, -0.93%)] and BMI z-score [- 9.66% (-18.05%, -1.28%)] at 24 months. Moreover, vanadium exposure at late pregnancy was negatively associated with weight [- 9.85% (-16.42%, -3.28%)], weight-for-length [- 11.00% (-18.40%, -3.60%)], and BMI z-scores [- 11.05% (-18.67%, -3.42%)] at 24 months in boys. However, the negative associations were not observed in girls, and we found evidence for sex difference (FDR p for interaction=0.01, 0.01 and 0.03 for weight, weight-for-length and BMI z-scores, respectively). Prenatal vanadium exposure may have an adverse effect on early-childhood growth, and the middle and late pregnancy could be windows of vulnerability for the adverse effects of vanadium exposure on growth development.
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Affiliation(s)
- Chunhui Li
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China
| | - Chuansha Wu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China
| | - Jingjing Zhang
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China
| | - Yuanyuan Li
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China
| | - Bin Zhang
- Wuhan Children's Hospital, Wuhan, Hubei, People's Republic of China
| | - Aifen Zhou
- Wuhan Children's Hospital, Wuhan, Hubei, People's Republic of China
| | - Wenyu Liu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China; Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center and Department of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, People's Republic of China
| | - Zhong Chen
- Wuhan Children's Hospital, Wuhan, Hubei, People's Republic of China
| | - Ruizhen Li
- Wuhan Children's Hospital, Wuhan, Hubei, People's Republic of China
| | - Zhongqiang Cao
- Wuhan Children's Hospital, Wuhan, Hubei, People's Republic of China
| | - Wei Xia
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
| | - Shunqing Xu
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
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