Statistical analysis of arsenic contamination in drinking water in a city of Iran and its modeling using GIS

Systematic review and meta-analysis of arsenic concentration in drinking water sources of Iran

Recent studies have found arsenic contamination of drinking water in some parts of Iran, as in many other countries. Thus, a comprehensive systematic review is necessary to assess the distribution and concentration of arsenic in drinking water sources. For this purpose, articles published from the first identification until December 2023, were retrieved from various national and international databases. Of all the studies examined (11,726), 137 articles were selected for review based on their conceptual relationship to this survey. A review of the extracted studies presented that ICP methods (ICP-MS, ICP-OES, 56%) and atomic absorption spectrophotometry (AAS, 34.1%) were the two most commonly used techniques for the analysis of arsenic in water samples. The order of arsenic content in the defined study areas is descending, as follows: northwest ˃ southeast ˃ southwest ˃ northeast. A review of studies performed in Iran depicted that provinces such as Kurdistan, Azerbaijan, and Kerman have the highest arsenic concentrations in water resources. Accordingly, the maximum concentration of arsenic was reported in Rayen, Kerman, and ranged from < 0.5-25,000 µg/L. The primary cause of elevated arsenic levels in water resources appears to be geologic structure, including volcanic activity, biogeochemical processes, sulfur-bearing volcanic rocks, Jurassic shale, the spatial coincidence of arsenic anomalies in tube wells and springs, and, to some extent, mining activities. The findings of the presented survey indicate that it is essential to take serious measures at the national level to minimize the health risks of arsenic contamination from drinking water consumption.

The association of arsenic exposure with mortality due to cancer, diabetes, Alzheimer's and congenital anomalies using Poisson regression

The present study aims to determine the relationship between the concentration of arsenic in the groundwater of Hamadan province and the mortality rate due to various types of malignancies, congenital anomalies, diabetes mellitus and Alzheimer's. Mortality data due to various causes of death in Hamadan province were collected for five years (2016-2020). Sampling of drinking water was determined in the reference laboratory using polarography method. Poisson regression was used to investigate the relationship between arsenic level and the death rate due to various types of disease, at a significant level (p value < 0.05). According to the results of Poisson regression, among the various causes of death (N = 8042), Alzheimer's 5.94 (3.67-9.61), diabetes mellitus 4.05 (3.5-5.37), congenital malformations 2.98 (1.88-4.72), breast cancer 2.72 (1.56-4.71), leukemia 1.90 (1.24-2.92), stomach cancer 1.64 (1.28-2.10), Liver cancer 1.58 (1.58-2.30), other digestive organs 5.86 (3.38-10.16), meninges and brain cancer 1.57 (1.02-2.41) showed the highest relationship with arsenic contamination. The results of this study could be evidence for a positive and significant relationship between arsenic concentrations and mortality rates due to cancers, diabetes mellitus, Alzheimer disease, and congenital malformations. Therefore, it's necessary to use appropriate water treatment methods to remove arsenic at the source in contaminated areas.

Arsenic level in drinking water, its correlation with water quality parameters, and associated health risks

This study aimed to evaluate the occurrence and likelihood of health risks related to arsenic in drinking water of all counties of the Hamadan province in the northwest of Iran. In this work, 370 samples were collected from all of the water resources of urban and rural regions, during 5 years (2017 to 2021). Oracle Crystal Ball software was used to perform the Monte Carlo simulation and investigate the potential health risks. According to the results, the average values of arsenic in the nine counties were in the order Kabudarahang (40.1 ppb), Malayer (13.1 ppb), Nahavand (6.1 ppb), Bahar (2.05 ppb), Famenin (0.41 ppb), Asadabad (0.36 ppb), Tuyserkan (0.28 ppb), Razan (0.14 ppb), and Hamadan (< 0.1 ppb). The highest concentration of arsenic occurred in Kabudarahang with a maximum value of 185 ppb. In the spring season, the average concentration of the cations, including calcium, magnesium, sodium, lead, cadmium, and chromium, obtained 109.51 mg/l, 44.67 mg/l, 20.50 mg/l, 88.76 ppb, 0.31 ppb, and 0.02 ppb, respectively. Based on the Delphi classification, the P 90% of oral lifetime cancer risk, in Hamadan province, were within level II (low risk) to VII (extremely high risk). The risk analysis revealed there was a possible carcinogenic risk to humans from oral exposure to As-contaminated groundwater, especially in Kabudarahang county. Therefore, there is an urgent need for management and precise measures in contaminated areas to reduce and prevent the adverse health effects of arsenic.

Increased urinary arsenic concentration in newly diagnosed type 2 diabetes mellitus: a gender-independent, smoking-dependent exposure biomarker in older adults in Tehran

Arsenic is ranked in the top ten environmental toxicants but its impact on type 2 diabetes mellitus (T2DM) and its association with other human health effects is contradictory. We aimed in this study to compare the urinary arsenic concentration (u As) in older age adults (> 40 years) and their T2DM subgroup in an age and gender-matched case control study to find the association of u As with, diet, oxidative stress, smoking, anthropometric factors, and lifestyle in our study participants. Face-to-face interviews based on structured questionnaires were conducted on 200 female and male volunteers (100 cases and 100 control). Considering the exclusion criteria, u As concentration and serum biomarkers of oxidative stress (malondialdehyde, superoxide dismutase, catalase) of 30 newly diagnosed T2DM and 30 control were determined by ICP-mass analysis and ELISA reader respectively. Despite the similarities in sociodemographic, diet, and lifestyle factors in males and females and their T2DM subgroups, a 4 times difference in u As levels between T2DM (93.7 ng/L (32)) and their healthy counterparts (23.7 ng/L (2.3)) without meaningful associations with gender, age, BMI, diet, and lifestyle was observed. Mean u As concentration in total population of smokers was significantly higher than non-smokers ((119 ng/L vs. 22.5 ng/L (p = 0.03)) and oxidative stress markers were not significantly higher in T2DM smokers than non-smokers. Chronic arsenic exposure through smoking could be contributed to the incidence of T2DM in older age adults. Oxidative stress markers were not significantly increased in smoker subgroup compared with non-smokers but except smoking pattern, other variables did not affect u As concentration. Precautionary measure to reduce the exposure of people with this element is recommended to prevent the arsenic-induced T2DM in human populations.

Effects of lead and cadmium on the immune system and cancer progression

In our daily life, we are surrounded by harmful pollutants, including heavy metals that are not visible in the macroscopic view easily. Heavy metals can disrupt different aspects of human health, such as the immune system which has gained a lot of attention in recent decades. This had led to its rapid progression and new insights into its alterations in different diseases especially cancer. Heavy metals are non-biodegradable materials that exist in different parts of the food cycle, such as fruits and vegetables as commonly consumed foods and also unexpected sources such as street dust, that exists in the streets that we pass every day, soil, air, and water. These heavy metals can enter the human body through respiratory, cutaneous, and gastrointestinal pathways and then accumulate in different organs, leading to their encountering with various parts of the body. These sources and natural characteristics of heavy metals facilitate their interaction with the immune system. In this review, we investigated the effect of lead and cadmium, as pollutants that exist in many different parts of the human environment, on the immune system which is known to have a key role in the pathophysiology of cancer.

How do data-mining models consider arsenic contamination in sediments and variables importance?

Arsenic (As) is one of the most important dangerous elements as more than 100 million of people are exposed to risk, globally. The permissible threshold of As for drinking water is 10 μg/L according to both the WHO's drinking water guidelines and the Iranian national standard. However, several studies have indicated that As concentrations exceed this threshold value in several regions of Iran. This research evaluates an As-susceptible region, the Tajan River watershed, using the following data-mining models: multivariate adaptive regression splines (MARS), functional data analysis (FDA), support vector machine (SVM), generalized linear model (GLM), multivariate discriminant analysis (MDA), and gradient boosting machine (GBM). This study considers 12 factors for elevated As concentrations: land use, drainage density, profile curvature, plan curvature, slope length, slope degree, topographic wetness index, erosion, village density, distance from villages, precipitation, and lithology. The susceptibility mapping was conducted using training (70%) and validation (30%). The results of As contamination in sediment showed that classifications into 4 levels of concentration are very similar for two models of GLM and FDA. The GBM calculated the areas of highest arsenic contamination risk by MARS and SVM with percentages of 30.0% and 28.7%, respectively. FDA, GLM, MARS, and MDA models calculated the areas of lowest risk to be 3.3%, 23.0%, 72.0%, 25.2%, and 26.1%, respectively. The results of ROC curve reveal that the MARS, SVM, and MDA had the highest accuracies with area under the curve ROC values of 84.6%, 78.9%, and 79.5%, respectively. Land use, lithology, erosion, and elevation were the most important predictors of contamination potential with a value of 0.6, 0.59, 0.57, and 0.56, respectively. These are the most important factors. Finally, these data-mining methods can be used as appropriate, inexpensive, and feasible options to identify As-susceptible areas and can guide managers to reduce contamination in sediment of the environment and the food chain.

The Impact of Long-term Exposure to Low Levels of Inorganic Arsenic on the Hypomethylation of SEPT9 Promoter in Epithelial-Mesenchymal Transformed Colorectal Cancer Cell Lines

Inorganic arsenicals are worldwide environmental contaminants that affect molecular characteristics in biological systems and lead to genomic and epigenomic instability as well as epithelial mesenchymal transition (EMT). In this study, we aimed to investigate whether low levels of sodium arsenite (iAsIII) can influence EMT and genomic instability through microsatellite analysis. We have also determined epigenomic instability by investigating the methylation status of SEPT9 tumor marker in colorectal cancer (CRC) cell lines, Caco2 and HCT116, which were treated with iAsIII to assess IC50s. Short-term and long-term exposure to low concentrations (1 µM and 0.1 µM) of iAsIII in two separate experiments was implemented to analyze EMT, microsatellite status and the methylation pattern of SEPT9 promoter. As expected, after 20 days of exposure to iAsIII, the expression of CDH1 was significantly decreased while the expression of CDH2, FIB1 and VIM was increased in Caco2 and HCT116, a finding that confirmed EMT induction. However, there was no detectable alteration in the size of microsatellites. As for the methylation pattern, SEPT9 promoter was hypomethylated as a result of long-term exposure to 0.1 µM iAsIII in Caco2. Long-term exposure of HCT116 to both concentrations could induce hypomethylation of SEPT9 promoter. Our findings indicate no linkage between EMT induction and microsatellite status in iAsIII-treated CRC cell lines. For the first time, the current study has shown that the induction of EMT by iAsIII is linked with SEPT9 promoter hypomethylation in Caco2 and HCT116 in a concentration- and time-dependent pattern.