Neuropsychological effects of long-term occupational exposure to mercury among chloralkali workers

Abstract

BACKGROUND:

Mercury is one of the most well-known toxic metals for humans. Chloralkali workers are exposed to mercury vapours extensively, which may be associated with neurotoxicity.

OBJECTIVE:

The aim of this study was to determine the associations between mercury concentration in blood and air samples, and mercury’s neuropsychological effects among chloralkali workers.

METHODS:

This study was conducted on 50 chloralkali workers as the exposed group and 50 non-industrial office workers as the unexposed group. All subjects were assessed using the Hamilton Depression Rating Scale, Piper Chronic Fatigue Scale and Essential Tremor Rating Scale. Mercury concentration was measured in blood and air samples using cold vapour atomic absorption spectrometry.

RESULTS:

There was significantly more severe fatigue, depression and tremor in the exposed group compared with the unexposed group. The mean concentration of blood mercury in the exposed group was 22.59±12.5μgL^–1 which was significantly higher than the unexposed group (1.28±1.05μg L^–1). Based on multiple linear regression, shift work, smoking, fatigue, depression and tremor were predictor variables for blood mercury concentration.

CONCLUSIONS:

This study indicated that this sample of chloralkali workers suffered from neuropsychological problems such as fatigue, depression and tremor, which is probably related to mercury exposure.

Keywords

Depression fatigue tremor mercury neurotoxicity

1 Introduction

Mercury (Hg) is a highly toxic metal and has become a global concern due to its adverse health and environmental effects [1]. It is well documented that exposure to mercury can cause harmful effects on vital organ systems such as the immune, respiratory, renal, digestive and nervous systems [2, 3]. In this regard the central nervous system (CNS) and kidneys are particularly susceptible to mercury [4]. Mercury can be released into the atmosphere by both anthropogenic and natural sources. The main anthropogenic sources of mercury are fossil fuel combustion, coal burning, waste incineration and various industries [5]. A great amount of mercury is released to the environment by chloralkali plants which use mercury for producing caustic soda and chlorine. These industries were responsible for the emission of about 15.146 tons of mercury into the environment over the world in 2018 [6]. In chloralkali plants which are based on mercury cell processes, mercury cells have been used in an electrochemical process for producing chlorine gas and sodium hydroxide from brine. During this process, the cathode, made from elemental mercury, forms an amalgam with sodium which runs over the cathodes. Flowing brine on the top, continually feeds the amalgam stream. Chlorine gas is produced by applying an electrical current to the anodes, suspended on the top of the cathodes. The amalgam proceeds to a decomposer, where it comes in contact with deionized water and produces elemental mercury, caustic solution and hydrogen [7]. Because of the high vapor pressure (1.8μgHg) and low boiling point of mercury (357°C), it can easily enter the environment and form compounds with mercury (II) cation (Hg⁺²) or mercury (I) cations (Hg⁺) [8].

Chloralkali workers are mostly exposed through breathing air polluted with mercury vapors, released from chloralkali electrochemical reactors (ECR) or direct skin contact. Family members of these workers may also become exposed to mercury through personnel’s clothes contaminated with mercury particles. Ingested metallic mercury enters the body through the gastrointestinal tract, but less than 1% of elemental mercury is uptaken by the body. In addition, breathing mercury vapors results in direct absorption of approximately 80% of it by the lungs, which is rapidly distributed by the blood to other organs, including the brain and kidneys [4]. Thus, some methods have been developed to remove mercury from the environment [9].

Elemental mercury is oxidized to mercury (II) which is able to pass the blood brain barrier to induce neurotoxicity [10]. The nervous system symptoms related to mercury exposure are tremor, insomnia, fatigue, irritability, loss of memory, and attention [11]. The level of mercury exposure and duration of exposure, play key roles in the intensity of these symptoms [12]. Mercury is distinguished from other toxic pollutants by its non-biodegradability, and ability to accumulate in human tissues. Neurotoxic effects of exposure to mercury happen even with low levels of urine mercury (mean: 10.4, range: 0.32–35.2μg/g creatinine) and include early alterations of motor function and neuroendocrine secretion; and have been reported in chloralkali workers [13]. Thus, monitoring mercury in workers’ blood, urine, hair and air can provide valuable information for risk assessment [14]. The American Conference of Governmental Industrial Hygienists (ACGIH) has assigned a threshold limit value of 0.025 mgm^–3 for mercury vapour, for a normal eight-hour working shift and a 40-hour working week [15]. Mercury levels in blood can be used to help diagnose recent mercury exposure and to evaluate patients’ response to chelation therapy [16].

The blood concentration threshold of mercury recommended by the US Environmental Protection Agency is 4.6μg/L [17]. The aim of this study was to determine the association between mercury concentration in blood and breathing zone air samples, and determine the neuropsychological symptoms caused by mercury exposure by comparing chloralkali workers with an unexposed population.

2 Material and methods

2.1 Participants

This case-control study was performed at a chloralkali unit in one of the national petrochemical companies of Iran. In this company, chlorine was produced by traditional mercury cell processes, which significantly increase the risk of mercury exposure in workers compared to other methods such as membrane cell and diaphragm cell [18]. The study population included all 73 workers who controlled the production of chlorine, caustic soda and hydrogen from sodium chloride. The inclusion criteria were: full-time work, with at least two-years work experience in the unit. The exclusion criteria were: having psychological and renal disease, using drugs consisting of mercury and being reluctance to participate. Workers who worked temporarily in the unit (n = 12), had less than one-year work experience (n = 3), were under medical care due to kidney and liver disease (n = 3), decided not to participate (n = 5) or did not meet the inclusion criteria were excluded. Finally, 50 workers participated in this study. In addition, 50 office workers who had the same level of physical activity and did not have mercury exposure were selected as the control group. None of the participants drank alcohol. The participants agreed to contribute to the study and signed the informed consent forms.

2.2 Measurements of depression, fatigue and tremor

Each participant was interviewed using a questionnaire about neurological problems (depression, fatigue and tremor), demographic and organizational information (Appendix A). The first part of the questionnaire contained questions about age, educational level, smoking, use of personal protective equipment, experience and shift work. Depression was evaluated by the Hamilton Depression Rating Scale (HDRS). This questionnaire is designed to be used by health care professionals during clinical interviews [19]; and consists of 17 items asking about symptoms related to depression, including depressed mood, feeling of guilt, suicide, work and activities, retardation, agitation, psychic anxiety, somatic anxiety, hypochondrias is and loss of weight which are scored on a 5 point scale, ranging from 0 = not present to 4 = severe; and insomnia (early in the night), insomnia (middle of the night), insomnia (early hours of the morning), somatic symptoms including gastro-intestinal symptoms and general somatic symptoms such as loss of libido, menstrual disturbances and insight which are scored from 0 to 2. Higher scores reflect more marked depression symptoms. Scoring is based on these 17-items and scores of 0–7 are considered as no depression symptom or remission, 8–13 suggests mild depressive disorder, 14–18 is moderate depressive disorder and scores over 19 indicate severe depressive disorder. The Cronbach’s alpha of the questionnaire was reported to be 0.88 [20].

A validated Persian version of the Piper Chronic Fatigue Scale (PFS) was used for assessing fatigue [21] in this study. In this study, the Cronbach’s alpha of this questionnaire was 0.75 which made it sufficiently reliable. This questionnaire consists of 22 items related to the temporal dimension of fatigue. Each subscale related to PFS is scored using a number between 0 and 10. The interpretation of the results is as follows: 0, means no tiredness; 1–3, minor fatigue; 4–6, moderate exhaustion; and 7–10, severe fatigue [22].

Tremor was evaluated using the Essential Tremor Rating Scale (ETRS) including 21 items. ETRS has two sections including daily living activity (12 items about the impact of tremor on daily living activities) and a performance section (9 items about tremor in head, voice, and both arms and legs) scored from 0 (never) to 4 (severe). The maximum total score in tremor’s impact on activities of daily living (ADL) and performance section are 48 and 64 respectively. In this study, a total score was obtained to compare with other variables [23, 24].

2.3 Mercury in air samples

Twenty air samples were collected in employees’ breathing zone according to the NIOSH 6009 analytical method. Each solid sorbent tube, which contained 200 mg Hopcalite in a single section, were attached to the pumps with tygon tubing and the flow rate was adjusted on 0.2 Lmin^–1. A personal sampling pump was calibrated with a sampling tube in the flow path, after and before sampling, by a primary flow calibrator (Bios, Defender 510, USA). The sampling duration was set for 3 hours of the work shift. Air samplers were capped and packed securely according to the standard method for shipment. Sorbent and the front glass wool plug from each sampler were placed in separate 50 ml volumetric flasks and 2.5 mL HNO₃, followed by 2.5 mL HCl was added. Hopcalite sorbent was dissolved then it was diluted to 50 mL with deionized water. The experiments were performed using the electro cold vapour atomic absorption spectrometer (CVAAS, GBC–932, 3000, Australia). All containers (quartz crucibles, plastic tubes) were cleaned with detergent and treated successively by hydrochloric acid and rinsed with de-ionized water. Microwave digestions were carried out with a Multi wave 3000 (Anton Paar, 100 mL, 20 bars; Austria). Pure argon gas (99.99%) was used as a carrier gas for CV-AAS analysis and the pH values of the solutions were measured by a digital pH meter (Metrohm 744). Personal pumps and BOD bottles were used for air sampling in the factory.

2.4 Mercury in blood samples

For sampling, all glass tubes were washed with a 0.5 moL/LHNO₃ solution for at least 24 hours and thoroughly rinsed 6 times with ultrapure water before use. As mercury concentrations in whole blood are very low, even minor contamination at any stage of sampling, sample storage and handling, or analysis has the potential to affect the accuracy of the results. 10 mL blood samples were collected from 50 chloralkali workers and 50 unexposed matched controls, aged 25 to 50 years. Participants had not eaten anything for about 7 hours before sampling. All blood samples were taken at the end of shift work, and end of the work week. For the analysis of the 100 blood samples, 10μL of pure heparin liquid was added. Blood samples were stored at –20°C in a clean glass tube until analysis.

Blood samples (10 mL) were transferred into sterile glass tubes. Dispersive liquid-liquid micro-extraction has been developed as a new mode of liquid phase micro-extraction and has attracted increasing attention for its simple operation, high enrichment factor, rapidity and high extraction efficiency [25]. In this work, 0.15 g of Trioctylmethyl ammonium thiosalicylate (TOMATS) was added to 10 mL of blood samples and the pH was adjusted to 7 with a buffer solution in a centrifuge tube. Then, the mixtures were shaken with a vortex apparatus for 2 min. Mercury (Hg⁺²) was complexed and pre-concentrated as Hg-TOMATS in Task Specific Ionic Liquid (TSIL). The phases were separated by centrifuging the turbid solution for 3 min with 3500 rpm. After micro-extraction with ionic liquid and back extraction with nitric acid, the blood mercury concentration was determined by Cold Vapor-Atomic Absorption Spectrophotometry (CV-AAS). This method had been validated in this study (supplementary file) [26, 27].

2.5 Ethical considerations

This study was conducted according to the Ethics in Research Guidelines of Iran and the declaration of Helsinki. Individual informed consents were obtained from all participants.

2.6 Statistical analysis

Descriptive statistics was reported for all variables. The normality of quantitative data and equality of variances were analysed by the Kolmogorov-Smirnov and Levene’s tests respectively. Chi-square tests were used to evaluate the difference between the demographic variables, and the depression and fatigue variable in the exposed and unexposed groups. The difference of tremor and the level of blood mercury between the two groups was assessed using the Mann-Whitney U-test. Spearman correlation coefficients were used to analyse the relation between mercury airborne levels and blood mercury concentrations. Multivariate linear regression modelling was done to investigate the effect of independent variables on blood mercury concentration. Non-normal variables were normalized using the method recommended by Templetion (2011), before entering them into the regression model [28]. All statistical tests were set at a P < 0.05 significance level and were performed using SPSS v24.

3 Results

More than half of the case group had a work experience of fewer than 10 years and 72% of them worked in shifts, while most of the office workers in the control group (70 percent) did not do shift work. Most of the workers in both groups worked between 8 to 10 hours per day and were nonsmokers. Among demographic variables, only BMI and shift work were significantly different between the exposed and unexposed groups. The number of shift workers and overweight in the exposed group were higher than the unexposed group. The workers in the case group significantly, reported more depression, fatigue and tremor than the control group (Table 1).

Table 1
Demographic characteristics and neurological impairments observed in the case and control groups

Variables Classification Participants P-value

Exposed n = 50 Unexposed n = 50

Age (y) <30 21 (42) 11 (22) 0.097^†

30–40 20 (40) 28 (56)

40< 9 (18) 11 (22)

BMI (kg/m²) Underweight 8 (16) 6 (12) 0.019^†

Normal weight 21 (42) 26 (52)

Pre-obesity 9 (18) 16 (32)

Obesity 12 (24) 2 (4)

Experience (y) <10 26 (52) 28 (56) 0.806^†

10–19 17 (34) 14 (28)

>19 7 (14) 8 (16)

Working hours per day ≤8 12 (24) 16 (32) 0.373^†

>8 38 (76) 34 (68)

Shift work Yes 36 (72) 15 (30) >0.001^†

No 14 (28) 35 (70)

Smoking Yes 10 (20) 9 (18) 0.858^†

No 35 (70) 39 (78)

Former 5 (10) 2 (4)

Depression Normal 7 (14) 20 (40) >0.001^†

Mild 8 (16) 15 (30)

Moderate 13 (26) 11 (22)

Severe 22 (44) 4 (8)

Fatigue No tiredness 8 (16) 20 (40) 0.018^†

Minor 14 (28) 13 (26)

Moderate 19 (38) 15 (30)

Severe 9 (18) 2 (4)

Tremor ADL 28.55±9.8 17.69±10.5 >0.001^‡

Performance 33.94±16.31 23.69±12.85 0.003^‡

Total score 62.49±19.88 41.39±15.46 >0.001^‡

Variables	Classification	Participants	P-value
Age (y)	<30	21 (42)	11 (22)	0.097^†
	30–40	20 (40)	28 (56)
	40<	9 (18)	11 (22)
BMI (kg/m²)	Underweight	8 (16)	6 (12)	0.019^†
	Normal weight	21 (42)	26 (52)
	Pre-obesity	9 (18)	16 (32)
	Obesity	12 (24)	2 (4)
Experience (y)	<10	26 (52)	28 (56)	0.806^†
	10–19	17 (34)	14 (28)
	>19	7 (14)	8 (16)
Working hours per day	≤8	12 (24)	16 (32)	0.373^†
	>8	38 (76)	34 (68)
Shift work	Yes	36 (72)	15 (30)	>0.001^†
	No	14 (28)	35 (70)
Smoking	Yes	10 (20)	9 (18)	0.858^†
	No	35 (70)	39 (78)
	Former	5 (10)	2 (4)
Depression	Normal	7 (14)	20 (40)	>0.001^†
	Mild	8 (16)	15 (30)
	Moderate	13 (26)	11 (22)
	Severe	22 (44)	4 (8)
Fatigue	No tiredness	8 (16)	20 (40)	0.018^†
	Minor	14 (28)	13 (26)
	Moderate	19 (38)	15 (30)
	Severe	9 (18)	2 (4)
Tremor	ADL	28.55±9.8	17.69±10.5	>0.001^‡
	Performance	33.94±16.31	23.69±12.85	0.003^‡
	Total score	62.49±19.88	41.39±15.46	>0.001^‡

^†Chi-Square, ^‡Mann-Whitney U.

The mean blood mercury levels of the case and control subjects were significantly different (P < 0.001). All chloralkali workers had blood mercury levels more than the biological exposure index (15μg/l) recommended by ACGIH (Table 2). In addition, the mean level of blood mercury had a positive correlation with the mean level of mercury in air samples (r = 0.34, p = 0.04).

Table 2

Statistical parameters for determining mercury in blood and breathing air sample

Sample	Mean (SD)	Range	P-value
Blood samples μgL^–1	Worker	22.59±12.5	4–63.5	<0.001
	Control group	1.28±1.05	0.7–8
Air samples mg m^–3	Worker	0.042±0.009	0.02–0.07	–
	Control group	ND^*	–

^*Not detectable.

According to multiple linear regression, significant predictors of blood mercury levels were smoking, fatigue, depression and tremor (ADL and performance). The chloralkali workers who were former smokers, had significantly less blood mercury levels than current smokers. A significant direct correlation was observed between severity of fatigue, depression and tremor, and blood mercury concentration.

4 Discussion

The results of this study showed the high prevalence of neurological problems including depression, fatigue and tremor in workers occupationally exposed to mercury vapor. According to the inclusion criteria, none of the participants had a history of neurological disorders, thus these symptoms in exposed subjects may be attributed to their mercury exposure.

Table 3
Multiple linear regression of blood mercury levels predictors

Variable B t P-Value

Shift No vs Yes –0.192 –2.978 0.052

Smoking Former vs Yes –0.113 –1.802 0.004

Fatigue Minor vs No –0.147 –1.895 0.061

Moderate vs No –0.454 5.99 <0.001

Severe vs No –0.339 4.69 <0.001

Depression Moderate vs No –0.24 – 3.55 0.001

Severe vs No –0.327 –4.369 0.044

ADL –0.18 – 2.15 0.034

Performance –0.138 2.16 0.033

Variable	B	t	P-Value
Shift	No vs Yes	–0.192	–2.978	0.052
Smoking	Former vs Yes	–0.113	–1.802	0.004
Fatigue	Minor vs No	–0.147	–1.895	0.061
Moderate vs No	–0.454	5.99	<0.001
Severe vs No	–0.339	4.69	<0.001
Depression	Moderate vs No	–0.24 –	3.55	0.001
Severe vs No	–0.327	–4.369	0.044
ADL	–0.18 –	2.15	0.034
Performance	–0.138	2.16	0.033

In this study, air mercury exposures were determined by air sampling. There was no detectable mercury in the breathing air of the unexposed group. The results also showed that the blood mercury concentration in chloralkali workers were higher than the unexposed group. A significant correlation was found between air mercury and blood mercury in the exposed group. There are few studies that have assessed the relation between mercury in air and blood and most studies have been conducted many years ago. For example, Stopford et al. (1978) looked at the correlation of general environmental exposure and breathing zone mercury vapor exposure with blood and urine mercury levels. They found an excellent correlation between blood mercury levels and breathing zone mercury levels as well as between total urine mercury values collected at the end of the workweek and breathing zone mercury vapor exposure levels [29]. Smith et al. (1970) also studied mercury exposure in chloralkali workers. They found an excellent correlation between average exposure to mercury in air and blood; and when corrected for specific gravity, total urine mercury levels were the same as in the Stopford et al.’s study, but blood mercury levels were about twice as high. Workers in the Smith’s study worked for longer time periods in a mercury-exposed environment, than workers in the Stopford’s study. With longer exposures, blood mercury levels will be higher, reflecting body stores of mercury, even without further exposures [30].

There were significant correlations between blood mercury levels and smoking, depression, fatigue and tremor (both ADL and performance) in this study. The chloralkali workers who did not smoke had lower blood mercury concentrations than those who were smokers. But, in contrast, Li et al. (2008) reported that smoking did not have a significant correlation with urinary mercury concentration [31]. However, in Li’s study only 3 persons from 22 participants were smokers. As reported in previous studies, the tobacco in each cigarette consists of about 2.95–10.2 ng mercury [32] and smoking plays a minor role as a source for mercury uptake [33] but smoking in workplaces can increase intake, when workers smoke with unwashed hands contaminated with mercury.

Similar to other studies, the prevalence of depression in the exposed group was significantly higher than the unexposed group. Grum et al. (2006) found that the average scores for depression and negative self-concept were significantly higher in the ex-mercury miners’ group than the controls and they suggested that high levels of depression could be one of the reasons for the higher risk of suicide among miners in the last 45 years. In their study, the miners were exposed to mercury for a period of 7–10 years and the average urine mercury levels ranged from 20 to 120μg/L [34]. In line with our results, Echeverria et al. (2010) indicated that urinary mercury concentration is significantly associated with the total score of the Beck Depression Index among dentists (β= 0.29, P = 0.02). The geometric means of urinary mercury levels in dentists and dental assistants, who were exposed to mercury for an average of 19 and 10 years, were 2.52 (±2.22) and 1.98 (±1.98) μg/L, respectively [35].

Neurological impairments can usually be observed in chronic exposure to mercury vapor. Nonspecific symptoms such as weight loss, anorexia, gastrointestinal disturbance and fatigue have also been reported at low exposure levels. Researchers think damage of mitochondrial membranes due to the affinity of mercury to sulfhydryl groups may be related to chronic fatigue syndrome [36]. Neghab et al. (2012) found that somatic fatigue had a significant correlation with urinary mercury concentration. But, depression and tremor, was not related to urinary mercury concentration [37]. However, the mean of air mercury concentration in their study (3.97±6.28μg/m³) was very lower than our study (0.042±0.009 mg/m³). Weldon et al. (2000) reported that 67% of females who were non-occupationally exposed to mercury and their mean urine mercury concentration was 146.7μg/L, experienced fatigue [38]. Higher exposure to mercury concentrations are related to fine muscle fasciculations punctuated every few minutes by coarse shaking which is called mercurial tremor [36]. Induced hand and forearm tremor by mercury exposure has been described by several studies [39, 40]. Harari et al. (2012) described the association between blood and urine mercury concentration and the center frequency of the tremor, reaction time and postural stability among gold miners [40]; and recently Anglen et al. (2015) reported subclinical increase in the prevalence of tremor in dentists aged 23–50 years, with a mean urinary mercury concentration of about 4.7μg/L [39]. Risher et al. (2005) suggested that tremor patterns generate new evidence of long term effects of mercury exposure [12]. A review suggested that physical examination is appropriate for assessing workers with urine mercury >200μg/L, while neurobehavioral tests are more suitable for those with lower urine mercury levels [10]. Consistent with our results, Clarkson et al. (2005) indicated that the systemic clinical symptoms of mercury vapor exposure on the CNS are erythrism, tremor, and peripheral neuropathy [41]. There are many studies that have shown the effect of mercury exposure on CNS among exposed workers. However, in contrast some studies have not found significant differences between the prevalence of neurological dysfunctions among the mercury exposed group compared to the unexposed group [42, 43]. These different results may be due to different estimates of exposure, time and dose of exposure and various effect parameters. It is highly likely that by increasing the dose and time of exposure as well as interacting with other neurotoxic metals, the adverse health effects of mercury increases commensurately. There is no clear threshold for mercury exposure, which is supposed to be safe for the CNS and many researchers used different sorbents such as gold, graphene and silica for sampling and removal of such pollutants from workplaces [44 –46].

This study showed that chloralkali workers are at risk of developing neurological impairments such as depression, fatigue and tremor due to exposure to mercury. In addition, biological monitoring of mercury in blood can be used to evaluate exposure to mercury and is a reliable indicator of recent exposure.

This study had some limitations. One of the most important of them was the small sample size. In addition, we assessed depression, fatigue and tremor using questionnaires which might have over or underestimated the symptoms.

5 Conclusions

In high exposures to mercury, observed mostly in occupational settings, the severity of symptoms correlates with the duration and intensity of exposure. The levels of mercury in human blood depend on the duration of working and the volume of breathing air. Mercury concentration levels in human blood and breathing zone air samples in these chloralkali workers were higher than OSHA and ACGHI thresholds. Results show that increased mercury concentration in human blood and breathing zone air samples may lead to important neuropsychological problems in workers. Therefore, the concentration of mercury in human blood and breathing air must be controlled in industrial workers. The results showed that mercury concentrations in blood samples of exposed subjects were significantly higher than unexposed controls. The correlation between mercury concentration in air and mercury concentration in blood samples was statistically significant.

Conflict of interest

The authors declare no conflict of interest.

Footnotes

Acknowledgments

The authors wish to thank the Iranian Petroleum Industry Health Research Institute (IPIHRI), Shahroud University of Medical Sciences (SHMU) and the Iranian Research Institute of Petroleum Industry (RIPI) for supporting this work. (971896).

Appendix A is available in the electronic version of this article: .

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