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Ji S, Qu Y, Sun Q, Zhao F, Qiu Y, Li Z, Li Y, Song H, Zhang M, Zhang W, Fu H, Cai J, Zhang Z, Zhu Y, Cao Z, Lv Y, Shi X. Mediating Role of Liver Dysfunction in the Association between Arsenic Exposure and Diabetes in Chinese Adults: A Nationwide Cross-Sectional Study of China National Human Biomonitoring (CNHBM) 2017-2018. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:2693-2703. [PMID: 38285630 DOI: 10.1021/acs.est.3c08718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
Inconsistent results have been reported regarding the association between low-to-moderate arsenic (As) exposure and diabetes. The effect of liver dysfunction on As-induced diabetes remains unclear. The cross-sectional study included 10,574 adults from 2017-2018 China National Human Biomonitoring. Urinary total As (TAs) levels were analyzed as markers of As exposure. Generalized linear mixed models and restricted cubic splines models were used to examine the relationships among TAs levels, serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) concentrations, and diabetes prevalence. Mediating analysis was performed to assess whether liver dysfunction mediated the association between TAs and diabetes. Overall, the OR (95% CI) of diabetes in participants in the second, third, and fourth quartiles of TAs were 1.08 (0.88, 1.33), 1.17 (0.94, 1.45), and 1.52 (1.22, 1.90), respectively, in the fully adjusted models compared with those in the lowest quartile. Serum ALT was positively associated with TAs and diabetes. Additionally, mediation analyses showed that ALT mediated 4.32% of the association between TAs and diabetes in the overall population and 8.86% in the population without alcohol consumption in the past year. This study suggested that alleviating the hepatotoxicity of As could have implications for both diabetes and liver disease.
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Affiliation(s)
- Saisai Ji
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yingli Qu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Qi Sun
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Feng Zhao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yidan Qiu
- Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou 310058, China
| | - Zheng Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yawei Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Haocan Song
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Miao Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Wenli Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Hui Fu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jiayi Cai
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Zhuona Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Ying Zhu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Zhaojin Cao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yuebin Lv
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
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Schrenk D, Bignami M, Bodin L, Chipman JK, del Mazo J, Grasl‐Kraupp B, Hogstrand C, Hoogenboom L(R, Leblanc J, Nebbia CS, Nielsen E, Ntzani E, Petersen A, Sand S, Vleminckx C, Wallace H, Barregård L, Benford D, Broberg K, Dogliotti E, Fletcher T, Rylander L, Abrahantes JC, Gómez Ruiz JÁ, Steinkellner H, Tauriainen T, Schwerdtle T. Update of the risk assessment of inorganic arsenic in food. EFSA J 2024; 22:e8488. [PMID: 38239496 PMCID: PMC10794945 DOI: 10.2903/j.efsa.2024.8488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2024] Open
Abstract
The European Commission asked EFSA to update its 2009 risk assessment on arsenic in food carrying out a hazard assessment of inorganic arsenic (iAs) and using the revised exposure assessment issued by EFSA in 2021. Epidemiological studies show that the chronic intake of iAs via diet and/or drinking water is associated with increased risk of several adverse outcomes including cancers of the skin, bladder and lung. The CONTAM Panel used the benchmark dose lower confidence limit based on a benchmark response (BMR) of 5% (relative increase of the background incidence after adjustment for confounders, BMDL05) of 0.06 μg iAs/kg bw per day obtained from a study on skin cancer as a Reference Point (RP). Inorganic As is a genotoxic carcinogen with additional epigenetic effects and the CONTAM Panel applied a margin of exposure (MOE) approach for the risk characterisation. In adults, the MOEs are low (range between 2 and 0.4 for mean consumers and between 0.9 and 0.2 at the 95th percentile exposure, respectively) and as such raise a health concern despite the uncertainties.
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Rahimi Kakavandi N, Mousavi T, Asadi T, Moradi A, Esmaeili M, Habibian Sezavar A, Nikfar S, Abdollahi M. An updated systematic review and dose-response meta-analysis on the relation between exposure to arsenic and risk of type 2 diabetes. Toxicol Lett 2023; 384:115-127. [PMID: 37562716 DOI: 10.1016/j.toxlet.2023.08.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/20/2023] [Accepted: 08/07/2023] [Indexed: 08/12/2023]
Abstract
Arsenic is among the most critical environmental toxicants associated with many human disorders. However, its effect on type 2 diabetes mellitus (T2DM) is contradictory. This systematic review and dose-response meta-analysis aim to update information on the association between arsenic exposure and the risk of T2DM. The sample type (drinking water, urine, blood, and nails) conducted the subgroup analysis. Evaluation of the high vs. low arsenic concentrations showed a significant association between drinking water arsenic (OR: 1.58, 95% CI: 1.20-2.08) and urinary arsenic (OR: 1.37, 95% CI: 1.24-1.51) with the risk of T2DM. The linear dose-response meta-analysis showed that each 1 μg/L increase in levels of drinking water arsenic (OR: 1.01, 95% CI: 1.00-1.01) and urinary arsenic (OR: 1.01, 95% CI: 1.00-1.02) was associated with a 1% increased risk of T2DM. The non-linear dose-response analysis indicated that arsenic in urine was associated with the risk of T2DM (Pnon-linearity<0.001). However, this effect was not statistically significant for arsenic in drinking water (Pnon-linearity=0.941). Our findings suggest that blood arsenic was not significantly linked to the increased risk of T2DM in high vs. low (OR: 1.21, 95% CI: 0.85-1.71), linear (OR: 1.04, 95% CI: 0.99-1.09), and non-linear (Pnon-linearity=0.365) analysis. Also, nail arsenic was not associated with the risk of T2DM in this meta-analysis (OR: 1.33, 95% CI: 0.69-2.59). This updated dose-response meta-analysis indicated that arsenic exposure was significantly correlated with the risk of T2DM.
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Affiliation(s)
- Nader Rahimi Kakavandi
- Department of Toxicology & Pharmacology, Faculty of Pharmacy, Tehran University of Medical Sciences (TUMS), Tehran, Iran; Health and Environment Research Center, Ilam University of Medical Sciences, Ilam, Iran
| | - Taraneh Mousavi
- Department of Toxicology & Pharmacology, Faculty of Pharmacy, Tehran University of Medical Sciences (TUMS), Tehran, Iran; Toxicology and Diseases Group (TDG), Pharmaceutical Sciences Research Center (PSRC), Tehran University of Medical Sciences, Tehran, Iran
| | - Tayebeh Asadi
- Health and Environment Research Center, Ilam University of Medical Sciences, Ilam, Iran
| | - Ayda Moradi
- Department of Pharmaceutical Nanotechnology, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahta Esmaeili
- Department of Pharmaceutical Nanotechnology, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Ahmad Habibian Sezavar
- Department of Toxicology & Pharmacology, Faculty of Pharmacy, Tehran University of Medical Sciences (TUMS), Tehran, Iran; Toxicology and Diseases Group (TDG), Pharmaceutical Sciences Research Center (PSRC), Tehran University of Medical Sciences, Tehran, Iran
| | - Shekoufeh Nikfar
- Department of Pharmacoeconomics and Pharmaceutical Administration, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Abdollahi
- Department of Toxicology & Pharmacology, Faculty of Pharmacy, Tehran University of Medical Sciences (TUMS), Tehran, Iran; Toxicology and Diseases Group (TDG), Pharmaceutical Sciences Research Center (PSRC), Tehran University of Medical Sciences, Tehran, Iran.
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Neufcourt L, Castagné R, Mabile L, Khalatbari-Soltani S, Delpierre C, Kelly-Irving M. Assessing How Social Exposures Are Integrated in Exposome Research: A Scoping Review. ENVIRONMENTAL HEALTH PERSPECTIVES 2022; 130:116001. [PMID: 36350665 PMCID: PMC9645433 DOI: 10.1289/ehp11015] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
BACKGROUND Exposome research aims to describe and understand the extent to which all the exposures in human environments may affect our health over the lifetime. However, the way in which humans interact with their environment is socially patterned. Failing to account for social factors in research exploring the exposome may underestimate the magnitude of the effect of exposures or mask inequalities in the distribution of both exposures and outcomes. OBJECTIVES We aimed to describe the extent to which social factors appear in the exposome literature, the manner in which they are used in empirical analyses and statistical modeling, and the way in which they are considered in the overall scientific approach. METHODS We conducted a scoping review of the literature using three databases (PubMed, Embase, and Web of Science) up to January 2022. We grouped studies based on the way in which the social variables were used in the analyses and quantified the type and frequency of social variables mentioned in the articles. We also qualitatively described the scientific approach used by authors to integrate social variables. RESULTS We screened 1,001 records, and 73 studies were included in the analysis. Fifty-five (∼75%) used social variables as exposures or confounders or both, and a wide array of social variables were represented in the articles. Individual-level social variables were more often found, especially education and race/ethnicity, as well as neighborhood-level deprivation indices. Half of the studies used a hypothesis-free approach and the other half, a hypothesis-driven approach. However, in the latter group, of 35 studies, only 8 reported and discussed at least one possible social mechanism underlying the relationship observed between the social variable and the outcome. DISCUSSION Social factors in exposome research should be considered in a more systematic way, considering their role in structuring both the specific external and the internal exposome. Doing so could help to understand the mechanisms of construction and, potentially, alleviate social inequalities in health and mitigate the emergence of new ones. https://doi.org/10.1289/EHP11015.
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Affiliation(s)
- Lola Neufcourt
- Equity Research Team, Centre d’Epidémiologie et de Recherche en santé des POPulations CERPOP-UMR1295, Inserm–Université Toulouse III Paul Sabatier, Toulouse, France
| | - Raphaële Castagné
- Equity Research Team, Centre d’Epidémiologie et de Recherche en santé des POPulations CERPOP-UMR1295, Inserm–Université Toulouse III Paul Sabatier, Toulouse, France
| | - Laurence Mabile
- Equity Research Team, Centre d’Epidémiologie et de Recherche en santé des POPulations CERPOP-UMR1295, Inserm–Université Toulouse III Paul Sabatier, Toulouse, France
| | - Saman Khalatbari-Soltani
- Faculty of Medicine and Health, University of Sydney School of Public Health, Sydney, New South Wales, Australia
- ARC Centre of Excellence in Population Aging Research, University of Sydney, Sydney, New South Wales, Australia
| | - Cyrille Delpierre
- Equity Research Team, Centre d’Epidémiologie et de Recherche en santé des POPulations CERPOP-UMR1295, Inserm–Université Toulouse III Paul Sabatier, Toulouse, France
| | - Michelle Kelly-Irving
- Equity Research Team, Centre d’Epidémiologie et de Recherche en santé des POPulations CERPOP-UMR1295, Inserm–Université Toulouse III Paul Sabatier, Toulouse, France
- Interdisciplinary Federal Research Institute on Health and Society (IFERISS-Fed 4241), Université Toulouse III Paul Sabatier, Toulouse, France
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Ozturk M, Metin M, Altay V, Bhat RA, Ejaz M, Gul A, Unal BT, Hasanuzzaman M, Nibir L, Nahar K, Bukhari A, Dervash MA, Kawano T. Arsenic and Human Health: Genotoxicity, Epigenomic Effects, and Cancer Signaling. Biol Trace Elem Res 2022; 200:988-1001. [PMID: 33864199 DOI: 10.1007/s12011-021-02719-w] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 04/11/2021] [Indexed: 02/06/2023]
Abstract
Arsenic is a well-known element because of its toxicity. Humans as well as plants and animals are negatively affected by its exposure. Some countries suffer from high levels of arsenic in their tap water and soils, which is considered a primary arsenic-linked risk factor for living beings. Humans generally get exposed to arsenic by contaminated drinking waters, resulting in many health problems, ranging from cancer to skin diseases. On the other hand, the FDA-certified drug arsenic trioxide provides solutions for various diseases, including several types of cancers. This issue emphasizes the importance of speciation of the metalloid elements in terms of impacts on health. When species get exposed to arsenic, it affects the cells altering their involvement. It can lead to abnormalities in inflammatory mechanisms and the immune system which contribute to the negative impacts generated on the body. The poisoning originating from arsenic gives rise to various biological signs on the body which can be useful for the diagnosis. It is important to find true biomarkers for the detection of arsenic poisoning. In view of its application in medicine and biology, studies on understanding the biological activity of arsenic have increased. In this review, we aim at summarizing the current state of knowledge of arsenic and the mechanism behind its toxicity including genotoxicity, oxidative insults, epigenomic changes, and alterations in cellular signaling.
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Affiliation(s)
- Munir Ozturk
- Department of Botany and Centre for Environmental Studies, Ege University, Izmir, Turkey.
| | - Mert Metin
- Graduate School of Environmental Engineering, The University of Kitakyushu, 1-1 Hibikino, Wakamatsu-ku, Kitakyushu, Fukuoka, 808-0135, Japan
| | - Volkan Altay
- Department of Biology, Faculty of Science and Arts, Hatay Mustafa Kemal University, Hatay, Turkey
| | - Rouf Ahmad Bhat
- Department of Environmental Science, Sri Pratap College, Cluster University Srinagar, Srinagar, Kashmir, India
| | - Mahnoor Ejaz
- Atta-ur-Rahman School of Applied Biosciences, Nat. University of Sciences & Technology, Islamabad, Pakistan
| | - Alvina Gul
- Atta-ur-Rahman School of Applied Biosciences, Nat. University of Sciences & Technology, Islamabad, Pakistan
| | - Bengu Turkyilmaz Unal
- Faculty of Science and Arts, Dept. of Biotechnology, Nigde Omer Halisdemir University, Nigde, Turkey
| | - Mirza Hasanuzzaman
- Department of Agronomy, Faculty of Agriculture, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh
| | - Lutfunnahar Nibir
- Upazilla Health Complex, Ministry of Health, Government of the People's, Homna, Comilla, Bangladesh
| | - Kamuran Nahar
- Dept. of Agricultural Botany, Faculty of Agriculture, Sher-e-Bangla Agricul. University, Dhaka, Bangladesh
| | - Andleep Bukhari
- Medical Pharmacology, Cerrahpasa Medical Faculty, Istanbul University, Istanbul, Turkey
| | - Moonisa Aslam Dervash
- Sher-e-Kashmir University of Agricultural Sciences and Technology, Srinagar, Kashmir, India
| | - Tomonori Kawano
- Graduate School of Environmental Engineering, The University of Kitakyushu, 1-1 Hibikino, Wakamatsu-ku, Kitakyushu, Fukuoka, 808-0135, Japan
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Ghaedrahmat Z, Cheraghian B, Jaafarzadeh N, Takdastan A, Shahbazian HB, Ahmadi M. Relationship between urinary heavy metals with metabolic syndrome and its components in population from Hoveyzeh cohort study: A case-control study in Iran. J Trace Elem Med Biol 2021; 66:126757. [PMID: 33839459 DOI: 10.1016/j.jtemb.2021.126757] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 03/28/2021] [Accepted: 04/01/2021] [Indexed: 01/10/2023]
Abstract
BACKGROUND The incidence of Metabolic Syndrome (MetS) has been growing rapidly and is rising to pandemic proportions. Although obesity is a primary risk factor for the enhancement of these conditions, not all obese individuals develop metabolic syndrome, indicating that the risk for developing MetS is impacted by other genetic and/or environmental factors such as heavy metals. Therefore, the present study focused on the association between exposures to heavy metal and MetS. METHODS Urine samples were collected from 150 participants (75 patients with MetS and 75 healthy participants), which were used from Hoveyzeh Cohort center. To make a quantitative comparison between the two groups, Man-Whitney nonparametric test was used. The logistic regression was performed adjusted for age, demographic, lifestyle factor, physical activity, occupational history and urine creatinine. RESULTS The results of logistic regression showed that OR and 95 % CI for Cd, Pb, Sr, As and Fe concentration were still significant after adjusting for urine creatinine. Moreover, there was a relationship between Cd and Pb levels and waist circumstance (WC). After adjusting for urine creatinine, age, sex, occupation, smoking status, education and place of residence, only Pb concentration was showed a significant association with systolic blood pressure (SBP). The subjects with high urine level of Cd had the high odds (OR: 6.273; 95 % Cl: 1.783-22.070) of MetS and low high-density lipoprotein (HDL-C). The relationship between As concentration and high fasting blood sugars confirmed the previous evidence suggesting that high As level can cause diabetes. CONCLUSION These results indicated that outbreak of MetS and its component are associated with heavy metal concentrations in urine.
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Affiliation(s)
- Zeinab Ghaedrahmat
- Student Research Committee, Department of Environmental Health Engineering, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Bahman Cheraghian
- Department of Biostatistics and Epidemiology, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Neamat Jaafarzadeh
- Environmental Technologies Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran; Department of Environmental Health Engineering, Ahvaz Jundishapur University of Medical Science, Ahvaz, Iran
| | - Afshin Takdastan
- Environmental Technologies Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran; Department of Environmental Health Engineering, Ahvaz Jundishapur University of Medical Science, Ahvaz, Iran
| | | | - Mehdi Ahmadi
- Environmental Technologies Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran; Department of Environmental Health Engineering, Ahvaz Jundishapur University of Medical Science, Ahvaz, Iran.
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Zhang Q, Hou Y, Wang D, Xu Y, Wang H, Liu J, Xia L, Li Y, Tang N, Zheng Q, Sun G. Interactions of arsenic metabolism with arsenic exposure and individual factors on diabetes occurrence: Baseline findings from Arsenic and Non-Communicable disease cohort (AsNCD) in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 265:114968. [PMID: 32806398 DOI: 10.1016/j.envpol.2020.114968] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 06/03/2020] [Accepted: 06/03/2020] [Indexed: 06/11/2023]
Abstract
The interaction between arsenic metabolism and potential modifiers on the risk of diabetes is unclear. This research aimed to investigate arsenic metabolism and diabetes prevalence and to identify the interactive effects of arsenic metabolism with some risk factors on diabetes in a Chinese population. A baseline cross-sectional survey was performed in two areas with groundwater arsenic contamination in China. Arsenic levels in water and arsenic metabolites in urine were analyzed. The proportions of each arsenic metabolite (inorganic arsenic [iAs%], monomethylarsonic acid [MMA%], and dimethylarsinic acid [DMA%]) were computed to evaluate arsenic metabolism. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the association between arsenic and diabetes. Interaction on the additive scale between arsenic methylation index and effect modifier was evaluated by calculating the relative excess risk due to interaction (RERI). Compared with participants in the lower tertile of MMA%, participants in the middle and upper tertiles of MMA% were less prone to diabetes (OR: 0.47 and 0.31, respectively). However, participants in the upper tertiles of urinary DMA% (OR: 3.18) were more likely to have diabetes than those participants in the lower tertiles. The stratified analyses revealed that a one-unit increase in DMA% was associated with higher odds of diabetes in females (OR: 1.06, 95% CI: 1.01, 1.11), older people (OR: 1.05, 95% CI: 1.00, 1.10), and subjects with body mass index (BMI) under 25 kg/m2 (OR: 1.07, 95% CI: 1.01, 1.14). The additive interactions between DMA% and female gender (RERI: 0.40, 95% CI: 0.01, 11.88), DMA% and age (RERI: 0.02, 95% CI: 0.01, 8.85), as well as DMA% and BMI (RERI: 0.49, 95% CI: 0.01, 9.62), were statistically significant. In conclusion, efficient arsenic metabolism is associated with higher odds of diabetes. Urinary DMA% and individual factors interact to synergistically influence diabetes occurrence in the Chinese population.
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Affiliation(s)
- Qiang Zhang
- Department of Occupational and Environmental Health, Tianjin Key Laboratory of Environment, Nutrition and Public Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China
| | - Yaxing Hou
- Department of Occupational and Environmental Health, Tianjin Key Laboratory of Environment, Nutrition and Public Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China
| | - Da Wang
- Environment and Non-Communicable Disease Research Center, Key Laboratory of Arsenic-related Biological Effects and Prevention and Treatment in Liaoning Province, School of Public Health, China Medical University, Shenyang, 110122, China
| | - Yuanyuan Xu
- Group of Chronic Disease and Environmental Genomics, School of Public Health, China Medical University, Shenyang, 110122, China
| | - Huihui Wang
- Group of Chronic Disease and Environmental Genomics, School of Public Health, China Medical University, Shenyang, 110122, China
| | - Juan Liu
- Department of Biomedical Information and Library, Tianjin Medical University, Tianjin, 300070 China
| | - Liting Xia
- Department of Occupational and Environmental Health, Tianjin Key Laboratory of Environment, Nutrition and Public Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China
| | - Yongfang Li
- Environment and Non-Communicable Disease Research Center, Key Laboratory of Arsenic-related Biological Effects and Prevention and Treatment in Liaoning Province, School of Public Health, China Medical University, Shenyang, 110122, China
| | - Naijun Tang
- Department of Occupational and Environmental Health, Tianjin Key Laboratory of Environment, Nutrition and Public Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China
| | - Quanmei Zheng
- Environment and Non-Communicable Disease Research Center, Key Laboratory of Arsenic-related Biological Effects and Prevention and Treatment in Liaoning Province, School of Public Health, China Medical University, Shenyang, 110122, China
| | - Guifan Sun
- Environment and Non-Communicable Disease Research Center, Key Laboratory of Arsenic-related Biological Effects and Prevention and Treatment in Liaoning Province, School of Public Health, China Medical University, Shenyang, 110122, China.
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8
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Ahmad H, Zhao L, Liu C, Cai C, Ma F. Ultrasound assisted dispersive solid phase microextraction of inorganic arsenic from food and water samples using CdS nanoflowers combined with ICP-OES determination. Food Chem 2020; 338:128028. [PMID: 33091983 DOI: 10.1016/j.foodchem.2020.128028] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Revised: 09/02/2020] [Accepted: 09/03/2020] [Indexed: 10/23/2022]
Abstract
Direct determination of arsenic species in real samples is challenging due to their trace concentration and spectral interferences by coexisting ions. Herein, we proposed an ultrasound-assisted dispersive solid phase microextraction (DSPME) procedure for the analyses of the trace inorganic arsenic. The hydrothermally synthesized cadmium sulfide nanoparticles (CdS NPs) completely adsorbed both arsenic species within 20 s at the initial arsenic concentration of 100 µg L-1. The detection limit (3 S/m) of the proposed method was found to be 0.5 ± 0.2 and 0.8 ± 0.2 ng L-1 for As(III) and As(V), respectively. The accuracy of the method against the systematic and constant errors was confirmed by the analysis of the Standard Reference Material (SRM) (>95% recovery with <5% RSD). The Student's t-test values were found to be less than the critical Student's t value at a 95% confidence level. The method was successfully employed for the determination of arsenic in food samples.
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Affiliation(s)
- Hilal Ahmad
- College of Chemistry and Environmental Engineering, Shenzhen University, 1066 Xueyuan Ave., Shenzhen 518055, PR China
| | - Lihua Zhao
- College of Chemistry and Environmental Engineering, Shenzhen University, 1066 Xueyuan Ave., Shenzhen 518055, PR China
| | - Changkun Liu
- College of Chemistry and Environmental Engineering, Shenzhen University, 1066 Xueyuan Ave., Shenzhen 518055, PR China.
| | - Chaojie Cai
- College of Chemistry and Environmental Engineering, Shenzhen University, 1066 Xueyuan Ave., Shenzhen 518055, PR China
| | - Fuqing Ma
- College of Chemistry and Environmental Engineering, Shenzhen University, 1066 Xueyuan Ave., Shenzhen 518055, PR China
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9
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Huq ME, Fahad S, Shao Z, Sarven MS, Khan IA, Alam M, Saeed M, Ullah H, Adnan M, Saud S, Cheng Q, Ali S, Wahid F, Zamin M, Raza MA, Saeed B, Riaz M, Khan WU. Arsenic in a groundwater environment in Bangladesh: Occurrence and mobilization. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2020; 262:110318. [PMID: 32250801 DOI: 10.1016/j.jenvman.2020.110318] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2019] [Revised: 06/16/2019] [Accepted: 02/20/2020] [Indexed: 05/24/2023]
Abstract
Groundwater with an excessive level of Arsenic (As) is a threat to human health. In Bangladesh, out of 64 districts, the groundwater of 50 and 59 districts contains As exceeding the Bangladesh (50 μg/L) and WHO (10 μg/L) standards for potable water. This review focuses on the occurrence, origin, plausible sources, and mobilization mechanisms of As in the groundwater of Bangladesh to better understand its environmental as well as public health consequences. High As concentrations mainly was mainly occur from the natural origin of the Himalayan orogenic tract. Consequently, sedimentary processes transport the As-loaded sediments from the orogenic tract to the marginal foreland of Bangladesh, and under the favorable biogeochemical circumstances, As is discharged from the sediment to the groundwater. Rock weathering, regular floods, volcanic movement, deposition of hydrochemical ore, and leaching of geological formations in the Himalayan range cause As occurrence in the groundwater of Bangladesh. Redox and desorption processes along with microbe-related reduction are the key geochemical processes for As enrichment. Under reducing conditions, both reductive dissolution of Fe-oxides and desorption of As are the root causes of As mobilization. A medium alkaline and reductive environment, resulting from biochemical reactions, is the major factor mobilizing As in groundwater. An elevated pH value along with decoupling of As and HCO3- plays a vital role in mobilizing As. The As mobilization process is related to the reductive solution of metal oxides as well as hydroxides that exists in sporadic sediments in Bangladesh. Other mechanisms, such as pyrite oxidation, redox cycling, and competitive ion exchange processes, are also postulated as probable mechanisms of As mobilization. The reductive dissolution of MnOOH adds dissolved As and redox-sensitive components such as SO42- and oxidized pyrite, which act as the major mechanisms to mobilize As. The reductive suspension of Mn(IV)-oxyhydroxides has also accelerated the As mobilization process in the groundwater of Bangladesh. Infiltration from the irrigation return flow and surface-wash water are also potential factors to remobilize As. Over-exploitation of groundwater and the competitive ion exchange process are also responsible for releasing As into the aquifers of Bangladesh.
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Affiliation(s)
- Md Enamul Huq
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China
| | - Shah Fahad
- College of Plant Science and Technology, Huazhong Agricultural University, Shizishan Street-1, Wuhan, 430070, Hubei, China; Department of Agriculture, University of Swabi, Khyber Pakhtunkhwa, Pakistan.
| | - Zhenfeng Shao
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China.
| | - Most Sinthia Sarven
- College of Plant Science and Technology, Huazhong Agricultural University, Shizishan Street-1, Wuhan, 430070, Hubei, China
| | - Imtiaz Ali Khan
- Department of Agriculture, University of Swabi, Khyber Pakhtunkhwa, Pakistan
| | - Mukhtar Alam
- Department of Agriculture, University of Swabi, Khyber Pakhtunkhwa, Pakistan
| | - Muhammad Saeed
- Department of Agriculture, University of Swabi, Khyber Pakhtunkhwa, Pakistan
| | - Hidayat Ullah
- Department of Agriculture, University of Swabi, Khyber Pakhtunkhwa, Pakistan
| | - Muahmmad Adnan
- Department of Agriculture, University of Swabi, Khyber Pakhtunkhwa, Pakistan
| | - Shah Saud
- Department of Horticulture, Northeast Agriculture University, Harbin, China
| | - Qimin Cheng
- Huazhong University of Science and Technology, School of Electronics Information and Communications, 1037 Luoyu Road, Wuhan, 430074, China
| | - Shaukat Ali
- Global Change Impact Studies Centre (GCISC), Ministry of Climate Change, Pakistan; Environmental Monitoring and Science Division, Alberta Environment and Parks, Canada
| | - Fazli Wahid
- Department of Agriculture, University of Swabi, Khyber Pakhtunkhwa, Pakistan
| | - Muhammad Zamin
- Department of Agriculture, University of Swabi, Khyber Pakhtunkhwa, Pakistan
| | - Mian Ahmad Raza
- Department of Agriculture, University of Swabi, Khyber Pakhtunkhwa, Pakistan
| | - Beena Saeed
- Department of Agriculture, University of Swabi, Khyber Pakhtunkhwa, Pakistan
| | - Muhammad Riaz
- Department of Environmental Sciences and Engineering, Government College University Faisalabad, Allama Iqbal Road, Faisalabad, Pakistan
| | - Wasif Ullah Khan
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, 100083, China
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Naser AM, Wang Q, Shamsudduha M, Chellaraj G, Joseph G. Modeling the Relationship of Groundwater Salinity to Neonatal and Infant Mortality From the Bangladesh Demographic Health Survey 2000 to 2014. GEOHEALTH 2020; 4:e2019GH000229. [PMID: 32159051 PMCID: PMC7025866 DOI: 10.1029/2019gh000229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 01/14/2020] [Accepted: 01/18/2020] [Indexed: 06/10/2023]
Abstract
We evaluated the relationship of drinking water salinity to neonatal and infant mortality using Bangladesh Demographic Health Surveys of 2000, 2004, 2007, 2011, and 2014. Point data of groundwater electrical conductivity (EC)- a measure of salinity-were collated from the Bangladesh Water Development Board and digitizing salinity contour map. Data for groundwater dissolved elements (sodium, calcium, magnesium, and potassium) data came from a national hydrochemistry survey in Bangladesh. Point EC and dissolved minerals data were then interpolated over entire Bangladesh and extracted to each cluster location, the primary sampling unit of Bangladesh Demographic Health Surveys. We used restricted cubic splines and survey design-specific logistic regression models to determine the relationship of water salinity to neonatal and infant mortality. A U-shaped association between drinking water salinity and neonatal and infant mortality was found, suggesting higher mortality when salinity was very low and high. Compared to mildly saline (EC ≥0.7 and < 2 mS/cm) water drinkers, freshwater (EC < 0.7 mS/cm) drinkers had 1.37 (95% CI: 1.01, 1.84) times higher neonatal mortality and 1.43 (95% CI: 1.08, 1.89) times higher infant mortality. Compared to mildly saline water drinkers, severe-saline (EC ≥10 mS/cm) water drinkers had 1.77 (95% CI: 1.17, 2.68) times higher neonatal mortality and 1.93 (95% CI: 1.35, 2.76) times higher infant mortality. We found that mild-salinity water had a high concentration of calcium and magnesium, whereas severe-salinity water had a high concentration of sodium. Freshwater had the least concentrations of salubrious calcium and magnesium.
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Affiliation(s)
- Abu Mohd Naser
- Emory Global Diabetes Research Center, Hubert Department of Global Health, Rollins School of Public HealthEmory UniversityAtlantaGAUSA
| | | | - Mohammad Shamsudduha
- Institute for Risk and Disaster ReductionUniversity College LondonLondonUK
- Department of GeographyUniversity of SussexBrightonUK
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Groundwater Chemistry and Blood Pressure: A Cross-Sectional Study in Bangladesh. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16132289. [PMID: 31261639 PMCID: PMC6651438 DOI: 10.3390/ijerph16132289] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 06/24/2019] [Accepted: 06/25/2019] [Indexed: 12/22/2022]
Abstract
Background: We assessed the association of groundwater chemicals with systolic blood pressure (SBP) and diastolic blood pressure (DBP). Methods: Blood pressure data for ≥35-year-olds were from the Bangladesh Demographic and Health Survey in 2011. Groundwater chemicals in 3534 well water samples from Bangladesh were measured by the British Geological Survey (BGS) in 1998-1999. Participants who reported groundwater as their primary source of drinking water were assigned chemical measures from the nearest BGS well. Survey-adjusted linear regression methods were used to assess the association of each groundwater chemical with the log-transformed blood pressure of the participants. Models were adjusted for age, sex, body mass index, smoking status, geographical region, household wealth, rural or urban residence, and educational attainment, and further adjusted for all other groundwater chemicals. Results: One standard deviation (SD) increase in groundwater magnesium was associated with a 0.992 (95% confidence interval (CI): 0.986, 0.998) geometric mean ratio (GMR) of SBP and a 0.991 (95% CI: 0.985, 0.996) GMR of DBP when adjusted for covariates except groundwater chemicals. When additionally adjusted for groundwater chemicals, one SD increase in groundwater magnesium was associated with a 0.984 (95% CI: 0.972, 0.997) GMR of SBP and a 0.990 (95% CI: 0.979, 1.000) GMR of DBP. However, associations were attenuated following Bonferroni-correction for multiple chemical comparisons in the full-adjusted model. Groundwater concentrations of calcium, potassium, silicon, sulfate, barium, zinc, manganese, and iron were not associated with SBP or DBP in the full-adjusted models. Conclusions: Groundwater magnesium had a weak association with lower SBP and DBP of the participants.
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