Environmental chronic exposure to metals and effects on attention and executive function in the general population

Journal Pre-proof Environmental chronic exposure to metals and effects on attention and executive function in the general population

Ata Rafiee, Juana Maria Delgado-Saborit, Peter D. Sly, Bernadette Quémerais, Fallah Hashemi, Sadaf Akbari, Mohammad Hoseini PII:

S0048-9697(19)35906-6

DOI:

https://doi.org/10.1016/j.scitotenv.2019.135911

Reference:

STOTEN 135911

To appear in:

Science of the Total Environment

Received date:

7 September 2019

Revised date:

16 October 2019

Accepted date:

1 December 2019

Please cite this article as: A. Rafiee, J.M. Delgado-Saborit, P.D. Sly, et al., Environmental chronic exposure to metals and effects on attention and executive function in the general population, Science of the Total Environment (2019), https://doi.org/10.1016/ j.scitotenv.2019.135911

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© 2019 Published by Elsevier.

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Environmental chronic exposure to metals and effects on attention and executive function in the general population Ata Rafiee1, Juana Maria Delgado-Saborit2, 3, 4, Peter D Sly5, Bernadette Quémerais1, Fallah Hashemi6, Sadaf Akbari7 and Mohammad Hoseini8* 1

Department of Medicine, University of Alberta, Edmonton, AB, Canada

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ISGlobal Barcelona Institute for Global Health, Barcelona Biomedical Research Park, Barcelona, Spain

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Population Health and Environmental Sciences, Analytical Environmental and Forensic Sciences, King's College

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London, United Kingdom Division of Environmental Health & Risk Management, School of Geography, Earth & Environmental Sciences,

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University of Birmingham, Birmingham, United Kingdom

Children’s Health and Environment Program, Child Health Research Centre, The University of Queensland, South

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Brisbane, Australia

Department of Environmental Health, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran

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Trauma and Injury Research Center, Iran University of Medical Sciences, Tehran, Iran

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Research Center for Health Sciences, Institute of Health, Department of Environmental Health, School of Health,

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Shiraz University of Medical Sciences, Shiraz, Iran

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6

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Assistant Professor

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Corresponding author: Mohammad Hoseini

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Department of Environmental Health Engineering, School of Public Health,

Shiraz University of Medical Sciences, Shiraz, Iran

Address: Razi blvd, Kuye Zahra Street, School of Public Health, Shiraz University of Medical Sciences, Shiraz, Iran. Tell: +98071-37251001

E-mail: [email protected]

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Abstract Heavy metals are neurotoxic, associated with brain dysfunction, and have been linked with cognitive decline in adults. This study was aimed to characterize chronic exposure to metals (Cd, Be, Co, Hg, Sn, V, Al, Ba, Cr, Cu, Fe, Li, Mn, Ni, Pb, and Zn) and metalloids (As, B, Sb) and assess its impact on cognitive performance of Tehran’s residents, capital of Iran. Scalp hair samples gathered from 200 volunteered participants (110 men and 90 women), aged 14-70 years and quantified by inductively

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coupled plasma atomic emission spectroscopy (ICP-OES). Attention and executive function, two measures of cognitive performance, were characterized using the trail making test (TMT) part A and B,

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respectively. Mental flexibility was characterized as the Delta TMT B-A scores and cognitive efficiency

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or dissimulation as the ration between TMT B and A scores. A comprehensive questionnaire was used to

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gather information on demographic and socioeconomic as well as lifestyle and health status. The highest and lowest mean concentrations were observed for B (325 µg/g) and As (0.29 µg/g), respectively. Results

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indicated that chronic metal exposure measured in hair changed significantly based on gender and age

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(p<0.05). The levels of Cr, Fe, Ni, Si, Hg, Pb and B were significantly higher in males' hair, whereas those of Ag and Ba were greater in females' hair (p<0.05). The results of the cognitive TMT test were

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significantly different between gender and age groups (p<0.05). Moreover, results revealed that As, Hg,

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Mn, and Pb levels in hair were significantly associated with poorer participants' performance scores in the TMT test (p<0.05). Age, gender, cigarette smoking, water-pipe smoking, traffic density in the area of residence, and dental amalgam filling were significant factors affecting the TMT test scores. The results suggest that chronic exposure to metals has detrimental effects on attention, executive function, mental flexibility and cognitive efficiency. Keywords: Biomonitoring, Cognitive performance, Exposure assessment, TMT test, Heavy metals.

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1. Introduction Environmental levels of metals deriving from anthropogenic activities have increased considerably in recent decades on a global scale (Liu et al., 2015; Zhu et al., 2018). Whereas some metals at specific trace levels play crucial roles in human health, e.g. transport of proteins, DNA repair (Amaral et al., 2008; Fábelová et al., 2018; Ventura et al., 2005); some heavy metals are neurotoxic and associated with brain

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dysfunction, impairment of the central nervous system (Chen et al., 2016) and linked with cognitive

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decline in adults (Iqbal et al., 2018). A recent review of the literature concluded that moderate evidence exists linking As and Al with an increased risk of dementia, while weak evidence was found for other

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metals, mainly due to the small number of published studies (Killin et al., 2016).

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Tehran, a major megacity in the Middle East faces severe environmental problems. Elevated

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concentrations of metals originated from traffic, industries, refineries, and waste water have been found in airborne particulate matter (MohseniBandpi et al., 2018), resuspended dust (Salmanzadeh et al., 2015),

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soil (Harati et al., 2011), food (Shirkhanloo et al., 2015) and drinking water (Ghahremanzadeh et al., 2018) in Tehran. Therefore, the population of this megacity can be exposed to metal concentrations from

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a myriad of exposure routes, including inhalation of airborne particulate matter and resuspended dust,

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dermal contact of dust and soil, and ingestion of food and water contaminated with metals. Independently of the route of exposure, once in the body, metals are preferentially accumulated in different tissues leading to an increase in their concentrations (Felix et al., 2015). Excretion of metals from the body occur through feces, urine, sweat, skin, hair, nails, sebum, semen, bile and saliva (Exley, 2013; Jandacek and Tso, 2001; Wang et al., 2012). To date, few studies have assessed the effect of exposure to metals on attention or executive function. Occupational exposure to metallic fumes has been associated with detriments in attention and executive function in welders exposed to manganese and aluminum fumes (Akila et al., 1999; Bowler et al., 2007a). In the NHANES III general population survey, urinary Cd was correlated with poor attention (Ciesielski

Journal Pre-proof et al., 2013). However, no study has reported the effect of chronic exposure to a wide range of metals on attention and executive function in the general population. The limited number of available studies evaluating the effects of metals on attention and executive function emphasizes the need to conduct further studies to strengthen the available evidence. Human biomonitoring (HBM) is a practical and reliable approach frequently used to characterize environmental and occupational exposures to pollutants (Hoseini et al., 2018; Rafiee et al., 2018a; Rafiee

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et al., 2019; Rafiee et al., 2018b). The use of urine and blood as matrices to determine the concentrations of metals in humans is widespread (Richmond-Bryant et al., 2014). However, in recent years, the use of

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scalp hair has increased because it offers some advantages over urine and blood (Amaral et al., 2008; Luo

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et al., 2014). The main elemental composition of hair is keratin, a protein containing cysteine sulfhydryl

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(thiol) groups which can bond to different elements (Pan and Li, 2015). Due to the continuous contact of the hair follicle with the bloodstream, elements in the blood can concentrate on the hair (McLean et al.,

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2009). The stability and high capacity of hair to accumulate metals during long-time periods represents an

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opportunity to use hair to monitor past and ongoing exposure to these pollutants, whereas urine and blood represent only recent exposures (Amaral et al., 2008; Luo et al., 2014; Pan and Li, 2015). Besides, some

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studies have found metal levels in hair ten-fold greater than those in other matrices such as urine and

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blood (Moreda-Piñeiro et al., 2007; Pan and Li, 2015), hence increasing the sensitivity to detect pollutant exposure. Last, but not least, hair sampling is non-invasive, and its transport, preparation, and analysis is more convenient than blood or urine (Drobyshev et al., 2017; Sazakli and Leotsinidis, 2017; Zhu et al., 2018). Despite many advantages that hair biomonitoring offers, there are some drawbacks including high variability in measured concentrations, the difficulty in differentiating between internal and external sources of contaminant, and the possibility of external contamination (Schramm, 2008; Smolders et al., 2009). The present study aims to a) characterize chronic exposure to a wide range of metals (Cd, Be, Co, Hg, Sn, V, Al, Ba, Cr, Cu, Fe, Li, Mn, Ni, Pb, and Zn) and metalloids (As, B, Sb), hereunder referred as metals, in scalp hair samples from residents of Tehran, capital of Iran; b) evaluate factors that could have potential

Journal Pre-proof impact on metal concentrations in the hair, including gender, age as well as environmental and lifestyle factors; and c) to investigate whether chronic exposure to metals has an effect on cognitive performance in the general population of a low and middle-income country.

2. Materials and methods 2-1. Study area description Tehran, the capital of Iran, located in the northern part of the country and with almost 12 million

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inhabitants, is the most populous city in Iran and the Middle East. The presence of various pollution

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sources such as high vehicle traffic, industrial activities on one hand, and the enclosure of the city by mountains, on the other hand, result in limited air circulation contributing to poor air quality in the city

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(Naddafi et al., 2011; Rafiee et al., 2018b). The present cross-sectional study was performed across

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different urban districts of Tehran from April to June 2018.

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2-2. Subject recruitment

Overall, 200 healthy inhabitants including 110 males and 90 females, living in the urban area of Tehran,

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were randomly chosen for hair sampling (Figure 1).

Recruitment of subjects into the study was subject to the following inclusion criteria: lived in Tehran's urban area over the past ten years

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no chronic disease

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not bald or with very short hair (scalp hair length less than 5 mm)

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no occupational exposure to metals

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not pregnant or breastfeeding

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Subjects gave consent to participate and to have scalp hair samples analyzed for metal concentrations, to provide personal information and to conduct cognitive testing. 2-3. Assessment of chronic metal exposure Samples were taken at subject’s regular hairdresser during routine haircuts. Hair samples were gathered from the back of the head as near as possible to the scalp (approximately 3g) using stainless steel scissors.

Journal Pre-proof Samples were stored in labelled polyethylene zip bags and transferred to the laboratory for further analysis. Hair samples were prepared for analysis according to the cleaning procedures proposed by the International Atomic Energy Agency (IAEA) (Katsanos et al., 1985). Briefly, hair samples were dispersed in acetone (Sigma-Aldrich, St. Louis, MO, USA) for 10 min, then, washed with ultra-pure water (Millipore, MA, France) and subsequently washed with acetone. The cleaned samples were dried at 65◦C in the

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oven for 10 h and then cut into small pieces of 0.5–1 cm length for digestion. A total of 100 mg of hair was added to the microwave Teflon cell (HNO3-HCLO4 V / V 3:1) with 3 mL of 65% nitric acid (Merck,

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Darmstadt Germany) and 1 ml of perchloric acid 70% (Merck, Darmstadt Germany). Then, the sample

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was digested in an ultra-wave microwave digestion system (1100 w high power Panasonic) according to

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the specific program in Table S1 (Supplementary Information). After digestion, the solution was diluted with 18MΩ cm demineralized water.

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The levels of 19 selected metals (As, B, Be, Cd, Co, Hg, Sb, Sn, V, Al, Ba, Cr, Cu, Fe, Li, Mn, Ni, Pb and

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Zn) in hair samples representative of metallic chronic exposure were determined using inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) with EOP flared end torch 2.5mm

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(SPECTRO Analytical Instruments Inc. Germany). Argon was employed for the plasma, nebulizer, and

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auxiliary gas. A four-channel pump controlled by a computer was used to deliver the sample into the instrument. The ICP-OES operating parameters are shown in Table S2 (Supporting Information) as well as the quality assurance and quality control measures are detailed in the Supporting Information (Table S3). 2-4. Assessment of potential confounders Participants answered a comprehensive questionnaire to gather information on demographic and socioeconomic status as well as lifestyle and health status. All information was self-reported by participants. Demographic and socioeconomic information included age (continuous), gender (2 categories: male, female), anthropometric measures height (continuous) and weight (continuous) to calculate body mass index (BMI, continuous). Environmental exposure information included cigarette

Journal Pre-proof smoking (2 categories: smokers, non-smokers), water-pipe smokers (2 categories: smokers, non-smokers), exposed to environmental tobacco smoke (ETS, 2 categories: ETS exposed, non-ETS exposed), amalgam tooth filling (2 categories: yes, no), traffic density near residential house (3 categories: low, medium, high), frequency of hair product use (4 categories: everyday, frequent use, once a week, seldom) and insecticide use (2 categories: yes, no). Diet exposure information such as fish consumption (2 categories:

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yes, no), and taking health supplement (2 categories: yes, no).

2-5. Assessment of cognitive function

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Participants completed the trail making test (TMT), a neuropsychological test of visual attention, mental

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flexibility, executive function, and switching tasks (Stebbins, 2007). The TMT has been widely used to

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assess the ability of brain-injured patients to complete set-switching tasks to demonstrate their ability to flexibly switch attention between competing task-set representations (Varjacic et al., 2018). Several

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cognitive processes and thus different brain regions are likely to be engaged when completing the TMT

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(Sanchez-Cubillo et al., 2009). The TMT Part B has been used as a screening test to identify patients with mild and moderate–severe brain injuries (Martin et al., 2003) and to detect different lesions in the

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executive function.

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dorsolateral prefrontal cortex and the anterior cingulate (MacPherson et al., 2017), brain regions related to

The TMT has two parts. In part A, the subject is instructed to connect 25 scattered dots which contain numbers from 1 to 25 in sequential order. The TMT-A score reflects visual attention ability and motor skills (Reitan, 1992). In part B, the subject must connect the dots in sequential order alternating between number and letters (e.g. 1-A-2-B, etc.). The time required to complete this part of the test is usually used as an index of executive function, such as the ability for cognitive alternation (Crowe, 1998). In both parts, the target is to complete the sequence as soon as possible, and the score is the time required to complete the sequence in each section (seconds). If the subject takes more than 300 seconds to complete part B, the score is capped at 300 s. The scores of part A and part B are measures of visual attention and executive function, respectively (Natl Acad, 2015). The difference between TMT B and TMT A scores

Journal Pre-proof (DeltaTMT) is a measure of speed (Salthouse, 2011). The ratio of TMT B over TMT A score (TMT Ratio) is a measure of cognitive efficiency or dissimulation (Martin et al., 2003). Higher scores represent worse cognitive performance. The TMT test was translated into the Persian alphabet to ensure that all the participants were familiar with

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the numbers and letters on the test.

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2-6. Statistical approach 2-6-1. Univariate analysis

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Univariate analysis was conducted using SPSS 21.0 package software (SPSS Inc. Chicago, IL).

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Kolmogorov–Smirnov test was used to determine the normality of data distribution. Mann–Whitney U

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test was used to investigate differences in chronic metal exposure according to binary covariates (e.g. gender), and Kruskal-Wallis test was used to examine differences according to multi categorical variable

2-6-2. Regression analysis

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(e.g. education status).

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We analyzed the association of individual chronic exposure to metals with cognitive measure of visual

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attention using the TMT Part A score, with executive function using the TMT Part B score, with reaction speed using the DeltaTMT score, and with cognitive efficiency or dissimulation using the TMT Ratio score. Linear regression coefficients (β) with corresponding 95% confidence intervals were estimated for increases of 1 µg/g of chronic metal exposure. Potential risk factors that could confound the associations between chronic metal exposure and cognitive performance were identified and described in a directed acyclic graph (DAG) with the DAGGitty program (Textor et al., 2011) as shown in Figure S1 (Supporting Information) (Greenland et al., 1999; Ogburn and VanderWeele, 2014). According to the DAG, the following covariates self-reported by the participants in the questionnaire were included in the models as covariates to adjust for potential

Journal Pre-proof confounding: age, gender, self-reported residential traffic exposure (3 categories), existence of dental amalgam implants, cigarette smoking (2 categories), water-pipe smoking (2 categories) and insecticide use (2 categories). Age was included as a continuous variable, whilst the rest of the covariates were introduced as categorical variables. Multiple linear regression analysis was applied using STATA 15.

3. Results 3-1. Socio-demographic characteristics and health status of the participants

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Table 1 summarizes information about socio-demographic characteristics, lifestyle habits, environmental

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exposure and health status of the studied subjects. Two hundred relatively healthy individuals, aged from 14 to 70 years old, participated in the present study. There was no significant difference between age

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in genders (P>0.05), however significant differences were observed between height, BMI, and

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weight of the participants. All participants were educated, and most of them had attended college.

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Based on the information provided by the questionnaire, 32 men and 22 women were classified as smokers. The number of subjects who had teeth feeling with amalgam were significantly higher

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among smokers in both studied groups (p<0.05).

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3-2. Distribution of chronic metal exposure Table S4 summarizes the concentrations of metals measured in the hair of the participants, and their

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percentiles are presented in Table S5 (Supplemental Information). The concentrations of metals in the hair of the studied subjects had the following trend: B > Zn > Al > Si > Fe > Cr > Cu > Hg > Pb > Mn > Ag > Ba > Ni > Sn > As. Very similar trends were observed for men and women (Table S4). The highest metal levels in the hair of the participants were detected for B (325 µg/g) and Zn (173 µg/g), respectively. Arsenic reported the lowest measurable geometric mean metal concentrations in both genders (0.29 µg/g), whereas Cd, Co and V were below the limit of detection (0.01-0.04 µg/g) in all cases. The levels of Cr, Fe, Ni, Si, Hg, Pb and B in the hair of male participants were significantly higher than those in female subjects (Mann-Whitney U test, p< 0.05), whereas the levels of Ag and Ba were significantly higher in females compared to males (p< 0.05). No significant differences were observed for Al, As, Cu, Hg, Mn,

Journal Pre-proof Sn, and Zn between both genders (p > 0.05). Significant differences (p< 0.01) in the concentrations of the sum of metals, Hg and Pb, were observed between smoker and non-smoker subjects (Figure 2). Besides, levels of Hg and Pb in the hair of subjects having dental amalgam fillings were significantly higher than those who did not have dental amalgam fillings (p< 0.05, Figure 3). 3-4. Distribution of cognitive assessment The time that male and female participants spent on completion part A of the TMT test were 46.8±30.0

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and 65.1±28.9 seconds, respectively. Likewise, men and women participants completed part B of the TMT test with mean time 194.9±79.0 and 145±76.9 seconds respectively. There were significant

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differences between male and female participants to complete both parts of the TMT test (Figure 4). It

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took longer times to complete part A of the TMT test (visual attention) in women than in men (Mann-

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Whitney U test, p < 0.05). On the contrary, male participants required longer time to complete part B of the TMT test (executive function) than female participants (Mann-Whitney U test, p < 0.05). The ratio of

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test TMT B/A was 4.98 ±2.68 for males and 2.31±1.01 for females which suggests relatively greater

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impairment on part B of the TMT test compared to performance on part A in males, whereas performance is similar in both tests for females showing better mental flexibility compared to males (Martin et al.,

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2003). The TMT Delta (B-A scores) is 148±72.1 in males and 80.2±60.4 in females, suggesting poorer

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performance for males than females in cognitive efficiency (Heaton et al., 1985). Results of participants who could not complete part B of the TMT test during 5 minutes were excluded from the dataset for further analysis.

3-4. Association between chronic metal exposure and cognitive performance The regression coefficients for the association between TMT test results and chronic metal exposure measure in the hair of the participants are presented in Table 2. Other potential confounding risk factors including, gender, age, smoking habits such as cigarette smoking and water-pipe smoking, existence of dental amalgam fillings, self-reported residential traffic density and insecticide use were also studied, and the results are also presented in Table 2.

Journal Pre-proof Concentrations of As, Hg, Mn, and Pb measured in hair had significant associations with both TMT-A and TMT-B in the studied subjects. In all cases increasing the time required to complete the tests, which represent worsening the cognitive performance of the subjects. The most significant effect was observed for Mn in both parts of the TMT test. In addition, higher concentrations of Zn in hair were associated with longer times required to complete the TMT-A test results, whereas higher levels of Sn were associated with a reduction of the time to complete the TMT-B test.

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The ratio of TMT-B to TMT-A, a measure of cognitive efficiency or dissimulation, was related to Hg and Pb, whereas the delta TMT score, a measure of mental flexibility, was associated with As, Hg, Pb (Table

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2). In both cases, chronic exposure was associated with higher scores, implying detrimental effects on

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these cognitive skills.

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Among other potential risk factors considered in the DAG model, significant associations were observed for age, cigarette smoking, and traffic density in the area of residence, on both TMT-A and TMT-B test

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results as well as Delta TMT and TMT ratio. Gender and water-pipe smoking were also associated with

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TMT-A test results, and teeth filling with amalgam was associated with an increase in the time required to complete TMT-B test. Gender was also related to TMT ratio, whereas water-pipe smoking was also

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4. Discussion

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associated with effects on the TMT Delta.

4-1. Routes of exposure to metals in the megacity of Tehran Tehran is surrounded by the Alborz Mountain Range and has climatological conditions propitious of temperature inversion trapping air pollution in the city due to the topographical barrier. Therefore, air pollution is one of the main environmental issues in Tehran, placing this metropolitan area as one of the world's most polluted cities (Heger and Sarraf, 2018). Particulate matter (PM) is among the main contributors to poor air quality in the megacity of Tehran (Shahbazi et al., 2016a), and thus inhalation of heavy metals bound to airborne or resuspended particulate matter is an important route of exposure to metals. Recent studies revealed high levels of heavy metals bound to airborne particulate matter (Arhami

Journal Pre-proof et al., 2017; MohseniBandpi et al., 2018), which could originate from tear and wear of brakes and tires (Sanderson et al., 2016), vehicle exhausts, industrial gaseous emissions, refineries, power plants and incinerators as well as from resuspension of soil dust (Sanderson et al., 2014).In Tehran, seventy percent of particulate matter is originated by traffic, with heavy-duty vehicles the main responsible of traffic PM emissions (85%), followed by motorcycles (12%) and cars (3%) (Shahbazi et al., 2016a). Elevated concentrations of heavy metals were reported from roadside soil and dust in Tehran (Salmanzadeh et al.,

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2015; Salmanzadeh et al., 2012; Yousefi et al., 2015). Energy conversion is the second largest contributor (20%) to PM in Tehran, followed by industries (7%), household and commercial (3%) (Heger and Sarraf,

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2018; Shahbazi et al., 2016a).

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Soil irrigated with wastewater containing metals in a Southern area of Tehran retained the metals in the

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superficial soil layers (Salmasi and Tavassoli, 2006) and hence, dermal contact of soil and deposited dust rich in metals are also potential routes of exposure to metals in Tehran (Kamani et al., 2017; Tchounwou

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et al., 2012). In addition, contaminated soils with heavy metals can contribute to accumulation of metals

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through the trophic chain (Harati et al., 2011). Citrus species and fruit products (Fathabad et al., 2018; Saleh et al., 2017), eggs (Salar-Amoli and Ali-Esfahani, 2015), milk (Tajkarimi et al., 2008), rice (Sharafi

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et al., 2019), canned fish (Andayesh et al., 2015) and corn (Ahmadi and Ziarati, 2015) available in

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markets in Tehran have been reported to contain elevated concentrations of metals. Similarly, high concentrations of metals in edible leafy vegetables farmed in the Southern part of Tehran have been reported (Shirkhanloo et al., 2015; Souri et al., 2018). Thus, dietary intake through ingestion of food contaminated with metals is another possible route of exposure to metals in Tehran (Shahbazi et al., 2016b). Elevated concentrations of Ni and Al were reported from drinking water extracted from ground water sources in North of Tehran (Farahmand et al., 2012), whereas high levels of V, Ni and Co were reported in well waters in the South of Tehran (Shirkhanloo et al., 2015) and high levels of As and Cd were found in the Tehran-Karaj aquifer located in the southern part of Tehran, which provides drinking water to more than half the city (Ghahremanzadeh et al., 2018). A study evaluating metals in tap drinking water after

Journal Pre-proof point of use water treatment system reported that concentrations of Cr, Cu, Fe, Mn, Ni, and Zn were within EPA and WHO guidelines (Rezaienia et al., 2019). Therefore, dietary intake of metals through drinking water contaminated with heavy metals is another likely source of metal exposure in Tehran. 4-2. Concentration of metals and metalloids in hair samples The levels of As in our study were 2.5 to 12 fold higher than those reported in previous studies (Coelho et al., 2013; Sazakli and Leotsinidis, 2017; Varrica et al., 2014). Nonetheless, the mean and also the 95th

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percentile arsenic measured in the hair of the participants were below the critical level of 1 µg/g recommended by WHO (Hindmarsh, 2000). However, as shown in Table 2, adverse effects were detected

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at these levels, with statistically significant associations between As levels with attention (TMT-A) and

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executive function (TMT-B). Exposure to As in Tehran might be related to dietary intake (Andayesh et

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al., 2015; Sharafi et al., 2019) and drinking water contaminated with As (Farahmand et al., 2012; Ghahremanzadeh et al., 2018).

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Results of Pb levels in the hair of participants in the present study were 2 to 16.5 fold higher than

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concentrations reported in previous studies (E et al., 2016; Peña-Fernández et al., 2014; Zhu et al., 2018). Mean levels of Pb in hair of men and women living in Taiyuan (China), an industrial city rich in coal

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reserves, were reported to be 2.96 and 2.95 µg/g 3.8 and 2.5-fold lower than the results of this study for

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men and women, respectively (Zhu et al., 2018). Pipes containing lead, which are common in water distribution networks in Iran, could be a possible source of exposure for the general population to Pb as all participants utilized tap water. Another possible source of lead exposure could be from resuspended dust exposure from soils historically enriched with leaded petrol exhausts (Del Rio-Salas et al., 2012; Layton and Beamer, 2009; Salmanzadeh et al., 2015; Salmanzadeh et al., 2012; Yousefi et al., 2015) as well as airborne PM2.5 (MohseniBandpi et al., 2018). Pica behavior of historically Pb enriched soils could be another potential source of chronic Pb exposure, but this would be more relevant to infants and young children, rather than to the adult population studied in the current study (Aelion et al., 2008; Ljung et al., 2006; Mielke and Reagan, 1998). The use of hair and cosmetic products could be another potential route of exposure to lead and other metals, with the exposure depending on the type, brand and country of

Journal Pre-proof origin of the cosmetic product (Iwegbue et al., 2016; Salama, 2016). Lead (and Ba) contamination of drinking water from weighting materials, such galena (PbS) and barite (BaSO4), used in drilling muds from oil fields (Pragst et al., 2017) South of Tehran could be another potential source of lead (and Ba) exposure. Lead intake in diet has been also suggested as a possible source of exposure (Andayesh et al., 2015; Fathabad et al., 2018; Salar-Amoli and Ali-Esfahani, 2015; Saleh et al., 2017). Lead contamination of soils and groundwater bodies from leachates in electronic waste management has been suggested as

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other possible sources of exposure to Pb in humans (Huo et al., 2007; Sepulveda et al., 2010; Sthiannopkao and Wong, 2013). The levels of Pb were significantly higher in hair of males than female

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participants, consistent with results reported for Polish university students (Szynkowska et al., 2015),

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Italian children (Sanna et al., 2003) and young adults in Pakistan (Ashraf et al., 1995). On the contrary,

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some studies had reported higher Pb concentrations for females than males, such as in a population of Italian (Tamburo et al., 2016) and Spanish children (Peña-Fernández et al., 2014). Higher Pb levels in the

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female hair could be attributed to the fact that women dye their hair more frequently using various hair

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dye products such as plant pigments and inorganic rinses, a common hair dye, which contains lead and other metals in its ingredient (Zhu et al., 2018).

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The levels of Hg in the hair of the male and female participants were 4.2 to 26 times higher than those

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reported in China and Spain (Molina-Villalba et al., 2015; Zhu et al., 2018). Some studies have revealed adverse effects of mercury (Hg) on children cognitive development (Sanders et al., 2015). The higher Hg levels in the hair of residents in Tehran could be attributed to the fact that almost 70% of the participants had teeth filling with amalgams that contain 50% mercury in its composition (Keanini et al., 2001). Moreover, based on questionnaire information, almost 60% of participants had fish in their diet once a week, which can lead to mercury accumulation from dietary intake. Indeed, elevated concentrations of mercury were reported in canned tuna marketed in Tehran (Andayesh et al., 2015), alongside other dietary products (Fathabad et al., 2018; Salar-Amoli and Ali-Esfahani, 2015). It has been reported that dietary intake and industrial activities are the main sources of Hg exposure in the general population (Zhu et al., 2018). The corresponding mean values in the present study were 6 fold higher in both genders than the

Journal Pre-proof United States National Research Council recommendation of a Hg safe limit of 1 µg/g Hg in hair (NRC, 2000). The results of Zn concentrations in the present study were lower than those reported in other regions (Tamburo et al., 2016; Varrica et al., 2014; Zhu et al., 2018). Zhu et al. (2018) reported that hair levels of Zn in male and female residents in China were 205 and 195 µg/g, respectively, which are 1.45 to 1.42 fold higher than the corresponding values in this study (Zhu et al., 2018). Zinc levels in the hair of male

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participant were higher than those in females. The greater level observed for Zn in hair of men participants could be attributed to the fact that men took more health supplements than women. Moreover,

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based on questionnaire information, the main health supplements that men had taken were zinc

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supplements and multivitamins. Our finding is inconsistent with the results of Varrica et al (2014) who

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found higher Zn levels in the hair of female than male in Sardinia (Italy). However, another study with Italian urban adolescents reported higher levels of Zn in the hair of men than women consistent with our

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results (De Prisco et al., 2010). Inhalation of Zn from PM2.5 (MohseniBandpi et al., 2018) and

sources of exposure to Zn.

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resuspended soil particles (Salmanzadeh et al., 2015; Salmanzadeh et al., 2012) could be other possible

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Our results revealed higher levels of nickel in men in comparison with the corresponding values in

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women. This was in agreement with the results reported by others who found that hair of men contained more nickel than women´s hair ((Barbieri et al., 2010; Peña-Fernández et al., 2014)). Results of Ni levels in the hair of the present study male and female participants were 2.5 to 12.7 fold higher than those reported in previous published works (Coelho et al., 2013; Sazakli and Leotsinidis, 2017; Varrica et al., 2014). However, Zhu et al (2018) reported Ni levels in men and women resident in Taiyuan, China, at 3.85 and 4.6 µg/g, respectively, which is 2 to almost 3 fold higher than the corresponding values in the present study. Possible environmental sources of exposure to nickel in Tehran could be from dietary intake (Ahmadi and Ziarati, 2015; Salar-Amoli and Ali-Esfahani, 2015; Shirkhanloo et al., 2015) and inhalation of airborne PM or resuspended soil (MohseniBandpi et al., 2018; Salmanzadeh et al., 2015; Salmanzadeh et al., 2012).

Journal Pre-proof Fe levels measured in the hair of male and female were 3 to 5 times higher than the corresponding values observed in the residents of Sant' Antioco in Italy (Varrica et al., 2014). (Zhu et al., 2018) reported Fe levels in resident of Taiyuan, China 66.5 and 7.6 µg/g, respectively, which is almost 2-fold higher than corresponding values in this study. Higher levels of Fe in men than women are reported in this study. This may due to the fact that men took more health supplements than women which included Fe in its ingredients. Besides, some studies proved that women in Iran suffer from iron deficiency anemia, as a

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common form of malnutrition (Nikzad et al., 2018). Finally, based on information obtained from questionnaire, men consumed more grilled foods (such as Kebab) than women. One of the popular grilled

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foods among Iranian is sheep's liver (Also called Jigar in Persian), which is rich in iron. Jigar

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consumption was more common among men than women in this study; therefore, dietary exposure of iron

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could contribute to the higher levels of Fe observed in men. Other sources of Fe could be attributed to inhalation of airborne aerosols (MohseniBandpi et al., 2018) and resuspended dust (Salmanzadeh et al.,

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2015; Salmanzadeh et al., 2012), dermal contact with soils (Harati et al., 2011) and dietary intake

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4-3. TMT scores

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(Ahmadi and Ziarati, 2015).

The scores of TMT Part A, Part B, DeltaTMT and TMT Ratio in the participants (aged 34 ± 15) are higher (i.e. worse) than those reported for a group of Spanish Caucasian healthy old adults aged 59.4 ± 6.9 years with 11.4 ±3.6 years of education (Sanchez-Cubillo et al., 2009). Subjects aged 30-36 with 1213 years of education with mild to severe head injury had also better scores in the TMT Parts A, B and Ratio TMT than the participants of this study (Martin et al., 2003). Likewise, better scores were also reported in non-demented older subjects with 13-14 years of education (Zec et al., 2015). On the other hand, lower (i.e better) scores were also reported for a group of healthy elderly participants in Sao Paolo (Brazil) aged 51-79 with 8-16 years of education (Souza et al., 2013) for TMT Part B and Delta TMT, whereas similar results were obtained in Part A only in the lower educated participants (8 ± 1

Journal Pre-proof years of education). Likewise, participants with Parkinson disease from Sao Paolo had similar TMT part A scores than the participants in Tehran, whilst better scores for Part B and Delta TMT (Souza et al., 2013). Participants in the US MOBILIZE Boston study (aged 78.1 ± 5.4) had also similar TMT Part A scores, but better TMT Part B and Delta TMT scores (Wellenius et al., 2012). Similar scores of TMT part A and B were observed in a Brazilian population with 2-8 years of education and >65 years old (Hamdan and Hamdan, 2009). A group of older Japanese (>70 years old) with 8-9 years of education had

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worse scores for TMT Part A and B, but similar Delta TMT and RatioTMT (Hashimoto et al., 2006). The comparison of the results of the participants in Tehran with scores from other studies highlights the

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importance of considering age, years of education, and neurological function as important influencing

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factors on the score. It also emphasizes the need to establish reference values for the population under

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study, as extrapolating values from one country to another might not be advisable in view of the current comparison.

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4-4. Association between metal exposure and cognitive performance

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The association between Pb content in hair and worse results on cognitive test measuring attention (TMTA test), executive function (TMT-B test), mental flexibility (Delta TMT) and cognitive efficiency or

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dissimulation (TMT Ratio) (Table 2) are consistent with the nature of Pb as a well-documented

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neurotoxicant (Boucher et al., 2012; Calderón et al., 2001; Mason et al., 2014; Morgan et al., 2001; Torrente et al., 2005). Previous studies reported that Pb exposure has been linked with decreased executive function, attention, visuo-spatial abilities and processing speed which are in agreement with our findings (Schwartz et al., 2005; Schwartz et al., 2000). Moreover, a recent study reported a strong correlation between Pb concentrations with mild, moderate and severe cognitive impairment in Pakistan, in line with our findings (Iqbal et al., 2018). Hg levels in hair had an impact on attention (TMT-A), executive function (TMT-B), mental flexibility (TMT Delta) and cognitive efficiency (TMT Ratio) results. As discussed earlier, the possible route of Hg exposure in the present study could be dental amalgam filling. Our results are in agreement with previous studies which considered mercury as one of the toxic elements potentially damaging children’s

Journal Pre-proof neurodevelopment (Grandjean and Herz, 2015). Hg has been associated with a range of neurological disorders, including ataxia, paralysis, retardation, dysarthria, dysesthesia, and cerebral palsy, especially in children (Hong et al., 2012). Distribution of Hg in the brain is not homogeneous, concentrating preferentially in the occipital lobe and cerebellum and basal ganglia, important areas for vision and movement (Davis et al., 1994), which in turn are influential in attention, executive function. Chronic exposure to As, measured in hair, is also significantly associated with worse results in the TMT

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test measuring attention (TMT-A), executive function (TMT-B) and cognitive efficiency (TMT Ratio). These results are consistent with Wasserman et al. (2004) who reported reduced intellectual function

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(Wechsler Intelligence Scale for Children, version III) after long-term exposure to As in children

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(Wasserman et al., 2004).

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Mn hair concentrations are associated with worse results in the TMT-A test measuring attention and the TMT-B test measuring executive function. Our results are consistent with studies reporting associations

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of Mn exposure with lower executive function in children (Carvalho et al., 2014), deficits in motor

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function, executive function and attention in children (Rodrigues et al., 2018) and with lower cognitive scores in several domains, including thinking, reading, calculation in children (Bhang et al., 2013;

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Bouchard et al., 2011; Khan et al., 2012). Our results are also consistent with results reported from

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confined welders occupationally exposed to Mn showing significant inverse dose-effect relationships between Mn and concentration and executive function (Bowler et al., 2007b). Mn exposure has been associated with pathological cognitive decline, resulting in excess of people with Alzheimer’s dementia in a cross-sectional study (Emard et al., 1994). Chronic exposure to Fe measured in hair of the participants from Tehran has been associated with increases in the TMT-A test scores, hence worsening attention of the subjects. This is in contrast with studies that report that iron deficiency anemia is associated with poorer cognitive (Cook et al., 2017), which could potentially affect functional connectivity in the adult life (Algarin et al., 2017). On the other hand, chronic exposure to iron concentrations from soils has been associated with neurodegenerative

Journal Pre-proof diseases, with some studies reporting an increased risk of dementia (Emard et al., 1994; Shen et al., 2014). Concentrations of Zn in hair were associated with poorer attention scores, as reported by the estimate effects on TMT-A scores (Table 2). Our results are consistent with those reported by Maylor et al (2006), who reported that Zn supplementation (15 mg/d) had detrimental effects on one measure of attention in healthy middle-aged and older adults participating in the ZENITH study (Maylor et al., 2006).

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4-5. Effects of age, gender and other exposure factors on cognitive performance 4-5-1. Age

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Results showed a significant difference (Kruskal Wallis test, p < 0.05) between age groups for the TMT

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test results as shown in Figure 4. Besides, linear regression results show significant relationships between

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age and TMT test results (Table 2). Previous studies indicated that age had a considerable impact on the performance of subjects in TMT test (Hamdan and Mara L. R. Hamdan, 2009; Hashimoto et al., 2006;

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Mitrushina et al., 2005; Periáñez et al., 2007; Tombaugh, 2004; Zec et al., 2015) which is consistent with

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our results. Generally, the time required to complete both part A and B of the TMT test increased as participants' age raised. Our findings are in agreement with the results reported by Hamdan et al. (2009)

4-5-2. Gender

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who observed that age was correlated with TMT grades (Hamdan and Mara L. R. Hamdan, 2009).

Gender had a significant effect on the time required to complete the test, with the longer time needed to complete both part A (β=0.502) and part B (β=0.289) for females. This result excludes data from subjects who exceeded 300 seconds to complete Part B of the test, who were mainly males (62% of excluded cases). The literature is heterogeneous as regards the effect of gender on TMT test scores. Zec et al. (2015) reported that females complete both parts of the tests faster than men in a population of nondemented older subjects (Zec et al., 2015). Meanwhile, Foroozandeh (2014) reported no gender

Journal Pre-proof differences in completing part A of the test, but males completed the test faster than females in part B in a non-clinical adult population in Iran similar to that recruited in this study (Foroozandeh, 2014). Mixed results were also reported in a large Latin American Spanish speaking study where gender differences were observed in a few countries, such as Honduras, Mexico, Paraguay and Peru, whereas no differences were observed in the other seven countries under consideration (Arango-Lasprilla et al., 2015). 4-5-3. Smoking status We found that smoking had a significant impact on TMT test results. It took longer time to complete the

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TMT test in participants who were smokers (β=0.481 for TMT-A and β=0.387 for TMT-B, p< 0.01). Our

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results are consistent with prior studies that reported association between smoking and detrimental effects

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on executive function (Paul et al., 2006; Swan and Lessov-Schlaggar, 2007) and attention (Conti et al.,

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2019; Gallinat et al., 2006; Gulec et al., 2018). The association between smoking and detrimental attention and executive function observed in this study could be related to the metal content on

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mainstream and side-stream smoke, but also other harmful components found in tobacco smoke such as

Saborit et al., 2009b).

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PAHs (Gallinat et al., 2006) and VOCs (Aquilina et al., 2010; Delgado-Saborit et al., 2009a; Delgado-

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Moreover, water-pipe smoking, which is popular among Iranian people, was identified as another risk

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factor increasing the TMT test results (p< 0.01). This is probably due to the fact that while one cigarette consists of 1-1.5 g tobacco, 10-20 g tobacco is used in each water-pipe smoking (Hoseini et al., 2018). Smoking can be a source of intake of metals like Pb, Al, Hg, and Cu which can be taken up by smokers both through inhalation and adsorption by hair (Bernhard et al., 2005; Chiba and Masironi, 1992). Our results are consistent with Meo et al. (2017) who reported that attention, in addition to alertness and memory, was impaired in apparently healthy young water-pipe smokers (Meo et al., 2017). 4-5-4. Traffic exposure Traffic exposure near the residential area was a risk factor significantly affecting the results of attention (β=0.118 for TMT-A, p < 0.05) and executive function (β=0.127 for TMT-B, p < 0.05), mental flexibility (β=0.106 for Delta TMT, p < 0.05) and cognitive efficiency (β=0.081 for TMT Ratio, p < 0.05). Our

Journal Pre-proof results are consistent with previous research that suggests that exposure to traffic and several air pollutants affect executive function (Wellenius et al., 2012) and attention (Chen and Schwartz, 2009; Cullen et al., 2018; Ranft et al., 2009). Other researchers found associations in the same direction but were not statistically significant (Gatto et al., 2014). Since the exposure to traffic air pollution is associated with increased environmental metal concentrations (Gietl et al., 2010; Sanderson et al., 2014), the association between traffic exposure and TMT test results may be related to the association between

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exposure to traffic air pollution and increased metal concentrations in the human body, both in blood and in scalp hair of the subjects. Previous studies revealed that exposure to traffic air pollution can lead to an

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increase in the levels of specific metals in human scalp hair (A et al., 2005; Mortada et al., 2001; Skalny

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et al., 2018) which is consistent with our findings. This is due to the fact that vehicular emissions are rich

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in metals (Wilhelm et al., 2002). It is worth noting that due to the phase-out of lead in petrol, recent studies fail to report effect of traffic exposure on lead content in hair scalp, as reported by Michalak et al.

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(2014) in southwestern Poland residents (Michalak et al., 2014). Likewise, this association might also

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reflect exposure to other components of the traffic pollution mixture, such as NO 2, PM10, PM2.5, black carbon and benzene, and could be also associated with other factors related to living in close proximity to

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al., 2016).

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traffic, such as noise (Belojevic et al., 2012; Clark and Paunovic, 2018; Kicinski et al., 2015; Tzivian et

4-5-5. Other contributory factors Results showed that dental amalgam fillings had a significant impact on executive function (β=0.382 for TMT-B, p < 0.01). It may be because amalgam contains 50% Hg and 30% Ag in its composition, which can have an impact on executive function and attention (Keanini et al., 2001). (Sletvold et al., 2012) reported the impact of exposure to metallic mercury on visual long-term memory, but contrary to our results, they could not find an association between Hg exposure and attention (TMT-A), executive function (TMT-B), or mental flexibility (Delta TMT) test performance in female dental workers Another significant factor which had an impact on TMT-B test results was using insecticides (β=0.188 for TMT-B, p < 0.05). Although our results did not show a significant relationship between exposure to

Journal Pre-proof insecticides and metals levels, previous epidemiologic studies revealed that chronic, low-dose exposure to insecticides was associated with cognitive outcomes (Furlong et al., 2014; Saillenfait et al., 2015). These are consistent with our findings that exposure to insecticides had an impact on part B of the TMT test where executive function of participants was investigated. One of the limitations of the present study is that due to cultural and personal attitudes, hair sampling from female subjects was challenging.

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5. Conclusion

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The aim of the study was to characterize chronic exposure to a wide range of metals using scalp hair samples from 200 residents of Tehran, the capital city of Iran and to investigated whether such chronic

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exposure could have an impact on the cognitive performance of the participants using the TMT test to

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evaluate attention, executive function, mental flexibility and cognitive efficiency or dissimulation.

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Results revealed that chronic exposure to As, Hg, Mn, and Pb had significant impacts on participants' cognitive performance measured with the TMT test. Age, cigarette smoking, and traffic density in the

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area of residence were all significant risk factors associated with attention, executive function, mental flexibility and cognitive efficiency or dissimulation. Other relevant factors affecting some of these

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cognitive domains were gender, presence of dental amalgam filling and water-pipe smoking.

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Our results suggest that chronic exposure to As, Hg, Mn, and Pb are associated with detrimental effects on the attention, executive function, mental flexibility and cognitive efficiency or dissimulation in the general adult population under study. Further studies should be conducted to explore whether chronic exposures to metals affect cognitive performance and development in infants and children given the possible interactions between metal exposures on children's neurodevelopment. To the best of our knowledge, this study represents the first human biomonitoring study reporting chronic exposure to a wide range of metals, measured in hair, in the general population of a low and middleincome country in the Middle East (Iran). The results of this study can be used for comparative purposes in future studies for other Middle Eastern countries and elsewhere.

Journal Pre-proof To the authors' knowledge, this is also the first study to report an effect of chronic exposure to a wide range of metals on attention, executive function, mental flexibility and cognitive efficiency or dissimulation in the general population, which also covers the adult life-span.

Acknowledgements The present work was financially supported by National Institute for Medical Research and Development (NIMAD) of Iran, under grant no. 971913. Dr JM Delgado-Saborit is a recipient of funds from the

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European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie

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grant agreement No 750531. The authors would like to express their thanks to all of the subjects who

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agreed to participate in this study.

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Figures legend: Figure 1 The random points weighted based on the population to select study subjects Figure 2 Concentrations of total metal, Hg and Pb in smoker and non-smoker subjects Figure 3 Concentration of Hg and Pb in the hair of subjects with and without dental amalgam fillings Figure 4 Time required to complete TMT tests in male and female participants andr or eie t efe fid ni

Figures Supplementary Information: Figure S1 Directed acyclic graph (DAG) of possible factors acting as covariates in the study

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Declaration of interests

☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Journal Pre-proof Table 1. Socio-demographic characteristics and health status of the participants Variables

Males

Females

No. of subjects Age (years) Height (cm) Weight (kg) BMI (kg/m2)

110 35 ± 16 178 ± 7 78 ± 11 25 ± 3

90 33 ± 15 163 ± 7 61 ± 9 23± 4

76 24

Yes No Water-pipe smoking (%) Yes No Environmental Tobacco Smoke (%) Yes No

30 70

ur

Low Medium High

Jo

Everyday Frequent Once a week Seldom Yes No Yes No Yes No

25 75

44 31 56 69 Teeth filling with amalgam (%) 69 66 67 31 34 33 Traffic situation near the place of residence (%) 20 35 26 60 55 58 20 10 16 Hair cosmetic products usage (%) 25 16 20 5 40 21 10 12 11 60 32 48 Taking health supplement (%) 55 37 47 45 63 53 Fish consumption (%) 67 55 62 33 45 38 Using insecticides (%) 67 55 55 33 45 45

lP

20 80

33 67

re

20 80

na

Yes No

of

Yes No

ro

15 53 27 5

200 34 ± 15 171 ± 10 70 ± 13 24 ± 3.5 Education (%) 21 18 36 45 43 35 2 Employment (having any job) (%) 63 71 37 29 Cigarette smoking (%) 24 27.5 76 72.5

-p

High school Diploma or less Bachelor's degree Master's degree PhD

Total

pvalue 0.450 0.000 0.000 0.001 0.268 0.016 0.017 0.031 0.044

0.381

0.032

0.000

0.735

0.017 0.476 0.052 0.119 0.000 0.651 0.000 0.008

0.089

0.089

Journal Pre-proof Table 2. Association between performance scores in TMT test of participants living in Tehran (Iran) and chronic metal exposure (measured in hair) and other potential risk factors. Higher test scores represent worse cognitive performance

Estim ate

[95% Conf.

Interval ]

Estim ate

[95% Conf.

Interval ]

0.0

-0.001

0.018

0.0

-0.078

0.124

-0.061

0.011

0.028

0.238

-0.182

0.041

09

0.1 75

B

-0.009

0.06

0.0

0.083

0.211

0.1 11

-0.062

0.186

-

03 -0.127

0.118

0.1

77

44

0.0

-0.128

0.062

0.0

-0.514

0.033

0.091

22

0.2 01

Ni

0.088

0.458

0.075

0.527

*

0.0

0.1 50

Si

-0.028

0.242

0.108

0.327

0.0

0.0

0.0

0.1

38

0.061

0.000

-0.001

0.001

0.673

-0.032

-0.200

0.136

-0.003

0.005

0.001

-0.000

0.009

-0.143

-0.321

0.136

0.007

-0.018

0.021

-0.241

0.085

-0.041

0.177

0.003

0.000

0.005

0.187

-0.081

0.243

0.002

-0.004

0.008

0.005

-0.018

0.021

0.000

-0.001

0.001

0.084*

0.036

0.308

0.104*

0.042

0.311

0.120

-0.188

0.327

-0.007

-0.016

0.003

-0.126

-0.718

0.316

-0.006

-0.025

0.012

0.104

0.042

0.284

0.116*

0.051

0.212

-0.001

-0.072

0.044

-0.001

-0.003

0.001

-0.499

-0.631

0.732

-0.125

-0.329

0.080

0.008

-0.008

0.025

0.091#

0.011

0.245

0.012

-0.002

0.029

0.088#

0.022

0.285

0.124

0.001

-0.018

0.115

-0.887

0.188

-0.218

0.241

0.022

0.385

0.009

0.461

-0.527

0.298

0.052

0.417

-0.621

0.132

-0.225

-0.035

*

0.2

0.1

0.1 98

-0.617

0.098

23

Sn

-0.019

59

*

0.0

0.023

03#

73 Pb

0.007

74

Jo

Mn

*

0.284

ur

0.1

-0.028

21

66# Hg

0.0

na

0.1

-0.010

32

21 Fe

-0.437

0.0

35 Cu

-

lP

Cr

0.493

0.325*

*

0.0

93

Ba

-0.642

03

*

0.0

-0.055

50

40 As

Interval ]

of

0.0

[95% Conf.

ro

Al

TMT Ratio (cognitive efficiency or dissimulation)(Martin et al., 2003) Estimat [95% Interval e Conf. ]

Estimat e

-p

Ag

DeltaTMT score (seconds) (mental flexibility) (Salthouse, 2011)

TMT-B score (seconds) (Executive function)

re

Hair MM levels ((µg/g)

TMT-A score (seconds) (Attention)

*

0.0 94

-0.327

0.284

92

0.1 98*

Zn

0.1 55

Gender (m/f)

0.028

0.368

*

0.3

0.0

-0.624

0.127

-0.342

0.411

61 0.094

0.621

0.1

Journal Pre-proof 73*

02

0.693

0.1

0.086

-0.348

0.343

0.0

1

95

0.076

0.3

18 0.0

82 -0.817

0.078

18* 0.072

0.128

0.561

0.289*

0.118

0.624

-0.223

0.314

0.114*

0.036

0.308

0.098

0.616

0.182*

0.061

0.325

-0.521

0.212 0.004

-0.112

0.016

0.181*

0.055

0.324

0.251*

0.099

0.624

0.109

0.047

0.318

0.118*

0.048

0.276

0.008

-0.003

0.011

0.081*

0.029

0.187

0.032

-0.051

0.207

*

0.0

13 0.1

0.573

87*

26* 0.0

0.142

*

0.3

81*

0.215*

24 0.062

0.238

-0.724

0.225

0.1 27* 0.188 *

0.024 0.065

0.325 0.287

0.106* 0.066

-p

Insecticides use

0.217

0.489

re

Traffic density in area of residence (high regard to low)

0.4

89

0.076

lP

Traffic density in area of residence (medium regard to low)

*

na

Teeth filling with amalgam (n/y)

0.2

ur

Water-pipe smoking (n/y)

0.874

Jo

Cigarette smoking (n/y)

0.145

of

0.5

0.061

ro

Age (y)

52

-0.031

0.302 0.181

*p-value<0.05; # p-value<0.10

Journal Pre-proof Highlights: 

First study to assess effect of chronic metal exposure on cognitive performance on the general population



Significant relationship observed between chronic exposure to metals and attention, executive function, mental flexibility and cognitive efficiency. First study to characterize chronic metal exposure on the general adult population of a low and

ur

na

lP

re

-p

ro

of

middle income country in the Middle East.

Jo



Figure 1

Figure 2

Figure 3

Figure 4