Personality traits in miners with past occupational elemental mercury exposure.

In this study, we evaluated the impact of long-term occupational exposure to elemental mercury vapor ([Hg.sup.0]) on the personality traits of ex-mercury miners. Study groups included 53 ex-miners previously exposed to [Hg.sup.0] and 53 age-matched controls. Miners and controls completed the serf-reporting Eysenck Personality Questionnaire and the Emotional States Questionnaire. The relationship between the indices of past occupational exposure and the observed personality traits was evaluated using Pearson's correlation coefficient and on a subgroup level by machine learning methods (regression trees). The ex-mercury miners were intermittently exposed to [Hg.sup.0] for a period of 7-31 years. The means of exposure-cycle urine mercury (U-Hg) concentrations ranged from 20 to 120 [micro]g/L. The results obtained indicate that ex-miners tend to be more introverted and sincere, more depressive, more rigid in expressing their emotions and are likely to have more negative self-concepts than controls, but no correlations were found with the indices of past occupational exposure. Despite certain limitations, results obtained by the regression tree suggest that higher alcohol consumption per se and long-term intermittent, moderate exposure to [Hg.sup.0] (exposure cycle mean U-Hg concentrations > 38.7 < 53.5 [micro]g/L) in interaction with alcohol remain a plausible explanation for the depression associated with negative self-concept found in subgroups of ex-mercury miners. This could be one of the reason for the higher risk of suicide among miners of the Idrija Mercury Mine in the last 45 years. Key words: depression, elemental mercury, ex-mercury miners, Hg, negative self-concept, occupational exposure, personality traits. Environ Health Perspect 114:290-296 (2006). doi:10.1289/ehp.7863 available via http://dx.doi.org/[Online 18 January 2006]

**********

The central nervous system is the critical organ for elemental mercury vapor ([Hg.sup.0]) exposure [World Health Organization (WHO) 1976]. Postmortem studies (Byrne et al. 1995; Falnoga et al. 2000; Kosta et al. 1975) have shown that the accumulation of Hg in the brains of ex-mercury miners was very high even several years after exposure. Strong Hg accumulation and retention were found particularly in the hippocampus, cerebellar cortex, nucleus dentatus, pituitary, and the pineal gland.

Long-term occupational exposure to [Hg.sup.0] is associated with symptoms of erethism, characterized by irritability, depression, introversion, apprehension, loss of self-confidence, and other nonspecific symptoms (WHO 1976, 1991, 2003). These symptoms also characterized the clinical pictures of [Hg.sup.0]-intoxicated miners of the Idrija Mercury Mine (Hribernik 1950; Kobal 1975, 1991).

Only a few studies have evaluated the residual, mostly neurologic, neurophysiologic, and neuropsychologic effects associated with remote occupational [Hg.sup.0]-exposure (Albers et al. 1988; Andersen et al. 1993; Ellingsen et al. 1993; Letz et al. 2000; Mathiesen et al. 1999). To our knowledge, only the study of Letz et al. (2000) evaluated residual mood effects in workers previously exposed to [Hg.sup.0], but the authors state that no changes were observed.

An epidemiologic study (Boffetta et al. 1998) of the causes of death among miners in certain mercury mines revealed an increased mortality rate due to suicide among the miners of the Idrija Mercury Mine. During the long-term medical monitoring of miners exposed to [Hg.sup.0] (Hribernik 1950; Kobal 1975, 1991), changes to miners' personalities were observed several times. Our purpose in the present study is to evaluate the impact of long-term occupational exposure to [Hg.sup.0] on the personality traits reported by ex-miners in the Eysenck Personality Questionnaire (EPQ) and the Emotional States Questionnaire (ESQ) in the period after exposure. We focused particularly on the relationship between past occupational [Hg.sup.0] exposure and appearance of depressive mood and negative self-concept among exminers, which could increase the risk of suicide.

Materials and Methods

Subjects. One hundred twenty males examined in the study were divided into ex-mercury miners and control groups. The ex-mercury miners were recruited from the Idrija Mercury Mine. The inclusion criteria for ex-mercury miners were age younger than 64 years, exposure to [Hg.sup.0] for at least 3 years or 12 exposure cycles, and no exposure to [Hg.sup.0] in at least the past 12 or 8 months but urinary mercury (U-Hg) excretion below 15 [micro]g/L at last exposure. Exposure cycle is defined as number of days per month of work in [Hg.sup.0]-contaminated work areas in the mine. These criteria were met by 60 ex-mercury miners who were identified from the company's medical records and biological monitoring data. The control workers--60 males--were taken from "mercury-free" forestry occupations. These workers performed jobs as choppers and transport workers and were located in neighboring municipalities to match the ex-mercury miners as closely as possible for socioeconomic factors. The workload in their jobs was similar to those of ex-mercury miners, which varied from 5.0 to 9.0 Kcal/min (Kobal 1991). Ex-miners were additionally exposed to silica dust and periodically to radon and its daughters (the most exposed group of miners did not receive more than 8 mSv for 2,000 hr of work a year). The subjects of both groups worked only in day shifts.

The final selection of the study population was based on medical examinations and some biologic analyses conducted at the time of the survey. The following criteria were applied: ex-mercury miners and control workers were neither currently nor previously exposed to lead, cadmium, or solvents, and the medical history and medical examinations of the control workers and ex-mercury miners did not reveal any neurologic or psychiatric affections (e.g., alcoholism, head trauma, meningitis, epilepsy, episodes of severe depression), metabolic disorders, hepatic or renal disease, or medical treatment possibly influencing the results of psychologic tests (e.g., p-blocker, antidepressive agent, etc.).

Fourteen subjects did not meet the above selection criteria and were excluded from the definitive population, which at the end consisted of 53 ex-mercury miners and 53 control group workers. Two ex-miners were excluded because of hypertension and renal disease, two because of alcohol abuse, one because of episodes of cerebral ischemia, and one because of metabolic disorders. Two control workers were excluded because of sick leave, two because of unwillingness to participate, one because of metabolic disorders, and one because of alcohol abuse. One ex-miner and one control worker were excluded from psychologic examinations because of their low general intellectual level, which caused obvious difficulties in understanding instructions during the test session.

The study group of ex-mercury miners was examined after exposure to [Hg.sup.0]. This group consisted of 20 retired miners and 33 still active but [Hg.sup.0]-unexposed miners (mining and production of Hg was stopped in 1994). In the past, mercury miners were intermittently exposed during working cycles to native Hg at air [Hg.sup.0] concentrations varying from 0.05 to > 1.00 mg/[m.sup.3]. When [Hg.sup.0] exposure exceeded the occupational exposure limit of 0.1 mg/[m.sup.3], miners used personal protective equipment, for example, half masks or Racal helmets with [Hg.sup.0]-absorbing filters (Kobal and Dizdarevic 1997).

The study was conducted with the approval of the State Ethical Commission and in accordance with the ethical standards laid down in the Helsinki Declaration. All participants gave their written informed consent before being included in the study.

Medical and psychologic examination. To standardize as much as possible with respect to work shift schedules, we conducted the examinations once a week on Friday. The medical examination included determination of general clinical status of examinees' medical histories and lifestyle habits (smoking, alcohol consumption). Examinations were performed by a physician-occupational medicine specialist with long-term experience in the health surveillance of workers exposed to [Hg.sup.0], in line with the standard clinical methodology. The overall examination time was approximately 120 min per subject, including the time required for giving instructions on how to perform the tests.

The self-reported mean alcohol consumption was converted to units of pure alcohol in milliliters per day (Kobal et al. 2004). A dental amalgam score was calculated using the methodology proposed by Aposhian et al. (1992). The examination included venous blood and urine sampling (8-hr urine samples collected from 2100 to 0600 hr) for determination of a) blood total Hg (B-THg) and U-Hg; b) selected hematologic data (erythrocytes, erythrocyte sedimentation rate, hematocrit, hemoglobin in blood, leucocytes, mean corpuscular hemoglobin, reticulocytes, thrombocytes, differential leukocyte count); c) selected blood and urinary data on the kidney and urinary tract (creatinine and urea in blood, urine test strip analyses, urine albumin and creatinine); and d) serum [gamma]-glutamyltransferase (GGT), aminotransferases, bilirubin, blood glucose, and c-reactive protein. All participants completed a Slovene translation (Lojk 1981) of the EPQ (Eysenck and Eysenck 1975) and the ESQ (Lamovec 1989). The collected data proved the EPQ questions to be appropriate for the Slovene population, as they were for the British and Danish (Eysenck and Eysenck 1975; Mortensen et al. 1996) populations. The personality structure appears to be similar in spite of the differences in nationality (Lojk 1981). The self-administrated Emotional State scales include 54 emotional descriptors rated on a 4-point scale from "none at all" to "extreme." The items consist of five emotional states: depression, contentment, aggression, indifference (tendency to emotional rigidity), and self-concept (positive and negative). The ESQ has a very similar theoretical view, as presented in the study by Sjoberg and Swensson (1976) and based on the study results of the Slovene population (Lamovec 1988). The factor analysis of primary emotions showed that the depression indicated in our questionnaire conforms with the clinical description of this condition, which, apart from depression, also includes elements of anxiety (Lamovec 1989). The estimates of the degree of reliability could be arbitrary to some extent, but some of the values of Cronbach [alpha] could hardly be rated as relatively high. However, the total measures of the Cronbach [alpha]-coefficient (Vogt 1993) and the Guttman split-half coefficient are beyond the lower level of acceptable reliability (Table 1). It could be suggested that, because reliability is associated with accuracy of the test, ESQ may be ranged among those psychometric tests with fairly good reliability.

Assessment of exposure. Environmental and biological data on the group of miners studied have been collected from 1959 onward from daily reports on [Hg.sup.0] measurements in the workplace, personal medical records, and biological monitoring data. On the basis of their exposure records, the following environmental indices of [Hg.sup.0] occupational exposure were calculated for each miner: a) years of work in the mercury mine (years of exposure); b) cycles of exposure (intervals of work exposed to [Hg.sup.0]); and c) average time-weighted (ATW) air [Hg.sup.0] concentration expressed in milligrams [Hg.sup.0] per cubic meter of air (Kobal and Dizdarevic 1997). [Hg.sup.0] in the air within the mine was generally determined by ultraviolet photometry using two portable instruments (model K-23 mercury vapor meter, Beckman Coulter, Fullerton, CA, USA; mercury indicator, Beckman Coulter UK Ltd., Shawcity, UK) designed to detect minute concentrations as described elsewhere (Kobal and Dizdarevic 1997).

The miners were biologically monitored by U-Hg analyses. High variations of U-Hg excretion are characteristic for the intermittent type of exposure observed in miners of the Idrija Mercury Mine (Kobal 1991). To avoid overestimation of the integral internal doses received during miners' occupational exposures, we considered not only the peak U-Hg levels of the cycles but also all U-Hg measurements obtained during and after the exposure cycles. The results of more than 5,400 U-Hg measurements (spot urine samples) were identified from the 53 ex-mercury miners. On the basis of these data, the following individual biological indices of occupational exposure were calculated: a) geometric mean of cycle U-Hg level, calculated from all urine samples determined during and after the cycles of exposure expressed in micrograms Hg per liter; b) the geometric mean of cycle peak U-Hg level, calculated from all cycle peak-Hg levels expressed in micrograms Hg per liter; c) the cumulative U-Hg level (the sum of U-Hg levels of all cycles) expressed in micrograms Hg per liter; d) cumulative peak U-Hg level (the sum all cycle peak U-Hg levels); and e) the U-Hg level at last exposure expressed in micrograms Hg per liter. The actual background exposure to inorganic Hg was evaluated by determining present and U-Hg. The potential methyl mercury exposure (from fish intake) was evaluated by determining blood methylmercury.

Biological analyses. B-THg and U-Hg were determined by cold-vapor atomic absorption spectrophotometry (CVAAS). The limit of detection of B-THg was 0.05 ng Hg/mL of blood. The actual U-Hg concentration was analyzed in an 8-hr urine sample collected in a metal-free polypropylene bottle during the night (2200-0600 hr). The detection limit of Hg in a 0.5-mL urine sample was 0.05 ng (Horvat et al. 1986, 1991). Before 1970, U-Hg was analyzed using the dithizone method, and afterward using the above-mentioned CVAAS technique expressed in micrograms per liter. Creatinine in urine was measured on a Roche/Hitachi 917 automated biochemical analyzer (Roche, Mannheim, Germany). The GGT, asparate aminotransferase (AST), and alanine amino-transferase (ALT) as alcohol abuse markers (Joachim 1995) and other basic routine biochemical and hematologic parameters were determined by applying the usual clinical biochemical methods (data not shown).

Data analyses. The group differences in all observed parameters were evaluated by applying a one-way analysis of variance using ANOVA software. The relationship between exposure and other variables was evaluated by Pearson's correlation coefficient, which reflects the degree of linear relation between two sets of data. The SPSS for Windows (version 11.0.1; SPSS Inc., Chicago, IL, USA) software package was used for all computations. Machine learning methods were used to find possible explanations of associations between the target variables (personality traits) and biological indicators of occupational [Hg.sup.0] exposure in combination with covariables on the subgroup level. We used these methods because they produce interpretable models, as opposed to most other nonlinear modeling procedures, which give us models that are hard to interpret (so-called black box models). Machine learning methods used are model trees (Quinlan 1992), which are a generalization of regression trees (Breiman et al. 1984).

Regression trees are a formalism for representation of piecewise constant functions, whereas model trees are more general and are a formalism for representation of piecewise linear functions. Like classic regression equations, model trees predict the value of a dependent variable (called target variable or class) from the values of a set of independent variables (called attributes). Data represented in the form of a table can be used for learning or construction of a model tree. In the table, each row (example or subject) has the form ([x.sub.1], [x.sub.2],..., [x.sub.n], y), where [x.sub.i] are values of n attributes (e.g., subjects' ages, daily consumption of alcohol, etc.) and y is the value of the target variable (e.g., the ESQ depression score). Unlike classic regression approaches, which find a single equation for a given set of data, model trees partition the space of examples into axis-parallel rectangles and fit a model to each of these partitions. A model tree has a test in each inner node that tests the value of a certain attribute, and in each leaf a model for predicting the target variable: the model can be a linear equation or merely a constant. Given a new example (subject) for which the value of the target variable should be predicted, the tree is interpreted from the root. In each inner node, the prescribed test is performed, and according to the result, the corresponding left or right subtree is selected. When the selected node is a leaf, the value of the target variable for the new example is predicted according to the model in the leaf.

A number of systems are available for inducing regression and model trees, such as RETIS (Karalic 1992) and M5 (Quinlan 1992). The latter is one of the best-known systems for regression and model tree induction. We used the M5' system (Wang and Witten 1997), a reimplementation of M5 within the WEKA software package (Witten and Frank 1999). The parameters of M5' were set to their default values.

A model tree for each of the selected target variables of personality traits (only target variables with group differences of p < 0.01 have been considered) was induced on the following features (independent variable): groups (ex-mercury miners; underground work, controls; work in the open), subgroups of ex-mercury miners (active but not exposed to [Hg.sup.0] miners; retired miners), age, residence (municipality of Idrija, other location, town center, hillside), dental amalgam score, cigarettes per day, alcohol consumption (milliliters per day), years of work in the mercury mine (years of exposure), work cycles of Hg exposure (number), the geometric mean of cycle U-Hg level in micograms per liter, the geometric mean of peak cycle U-Hg level in micograms per liter, cumulative U-Hg and cumulative peak U-Hg levels in micograms per liter, U-Hg level at last exposure micograms per liter, and time since last exposure in days (exposure-free interval). Those miners with an exposure-free interval of < 12 months were excluded from evaluation. Model trees for depression score and negative self-concept score were induced on subjects from both groups (miners and controls), whereas for modeling the lie score, only the miners were considered. Only those models that, in addition to indicators of occupational exposure, showed characteristics common to both groups were used. To stress the significance of last exposure in these evaluations, all U-Hg values of last exposure < 10 [micro]g/L were ignored (five miners). Each model was evaluated using Pearson's correlation coefficient on the training data only because we were interested in possible explanations of group differences that were already found to be significant.

Results

Characteristics of ex-mercury miners and controls. Despite their similar socioeconomic conditions, lifestyle, and same biologic characteristics, the groups differed with respect to the location of their work, which is performed underground by miners and above ground by controls, as well as by their occupational exposure to [Hg.sup.0] and some other previously mentioned pollutant in the mine.

The observed groups did not differ in mean age, body mass index (BMI), dental amalgam score, fish intake, cigarette and alcohol consumption (Table 2). The mean consumption of alcohol tended to be higher in miners (35 vs. 22 mL/day). The number of alcohol consumers with > 20 mL/day was higher in miners (28% vs. 19%), but no significant differences between the two groups were detected (p > 0.05). At these levels of alcohol consumption, induction of the microsomal ethanol-oxidizing system and increased activity of certain liver enzymes may be expected (Marks et al. 1996), but on a group level no differences in the mean serum GGT and AST levels (p > 0.05) were detected between miners and controls (data not shown). A slight correlation between alcohol consumption and serum GGT (r = 0.31, p = 0.034) and AST (r= 0.48, p = 0.000) was found in miners.

The groups did not differ in mean B-THg concentrations, which represents the actual exposure to [Hg.sup.0] and methylmercury (fish intake). The dental Hg amalgam score in controls correlated with B-THg (r = 0.30, p = 0.04); no such correlation was found in the group of ex-mercury miners. The U-Hg concentration (micrograms per gram creatinine) was significantly higher (p = 0.003) in the miner group than in the control group because of the higher U-Hg excretion in ex-mercury miners whose interval since last exposure was < 6 years.

Occupational [Hg.sup.0] exposure status. Mercury miners were observed in the period after long-term intermittent exposure to [Hg.sup.0], which lasted 7-31 years. Before the present observations, the miners had no longer been exposed to [Hg.sup.0] for on average 5.9 years (range, 8-336 months). Because of job rotations (from [Hg.sup.0]-contaminated to noncontaminated workplaces), the miners were periodically, in cycles, exposed to [Hg.sup.0] several times a year (Kobal and Dizdarevic 1997). The total number of exposure intervals--cycles of exposure--varied from 13 to 119. On average, the miners' cycles of [Hg.sup.0] exposure lasted 19 days (range, 3-34 days). The biological indices of occupational exposure presented in Table 3 were relatively high despite the use of personal protective equipment. The geometric mean of cycles U-Hg levels varied from 20 to 120 [micro]g/L, yet intraindividual variability was very high, with a coefficient of variability in the range of 53-104%.

The best positive correlation with the biological indices of exposure was shown by the cycles number of exposure. Its correlation with the cycle U-Hg level (r = 0.395, p = 0.003), the cycle peak U-Hg level (r = 0.371, p = 0.006), and the U-Hg level at last exposure (r = 0.374, p = 0.005) was moderate but significant. A relatively good correlation was found between U-Hg at last exposure and the mean cycle U-Hg concentration (r = 0.448, p = 0.001). No positive correlation was found between the present U-Hg level and past external or biologic occupational exposure indices.

Psychologic evaluation. Table 4 presents the EPQ. A comparison of the group of ex-mercury miners and the control group revealed a lower mean score of extraversion in the miners group (p = 0.017). The average score on the lie scale was also lower in the group of miners (p = 0.003).

Table 5 presents the ESQ. The average scores for depression and negative self-concept were significantly higher (p < 0.01) in the ex-mercury miners' group than in the controls. The indifference average score also tended to be higher in miners (p = 0.025) than in controls. We found no correlation of lie, depression, negative self-concept score, or other EPQ and ESQ variable scores with past external or biological occupational exposure indices evaluated using Pearson's correlation coefficient. A positive significant correlation between the depression score and the negative self-concept score was found in miners (r = 0.757, p = 0.009) and controls (r = 0.807, p = 0.000). No correlation was found between alcohol consumption and lie score, or between depression score and negative self-concept score.

The model trees built for lie, depression, and negative self-concept scores (only target variables with group differences of p < 0.01 have been considered) are presented in Figures 1, 2, and 3, respectively.

The model tree predicting the lie score is constructed only on ex-mercury miners. The model tree presented in Figure 1 contains two leaves (linear regression models LM1 and LM2). Alcohol consumption tended to slightly increase the lie score in the subgroup of ex-mercury miners younger than 54.4 years. In the subgroup of older ex-mercury miners, age prominently increased the lie score. No association with external or biological indices of previous exposure is presented in the constructed model tree.

The model tree predicting the depression score, as presented in Figure 2, is constructed on the group of miners and controls. The model tree contains four leaves (linear regression models LM1-LM4), of which three contain constant predictions and one contains a linear model. It is evident from the LM1 model, which was based on a larger number of subjects (39 controls and 9 ex-mercury miners) that low alcohol consumption (< 26.6 mL/day), at lower levels of past ex-miner occupational exposure (mean cycle U-Hg < 38.7 [micro]g/L), did not increase the depression score. Model LM2 relates to the increased depression score in six ex-mercury miners at an intermediate level of exposure (mean cycle U-Hg from > 38.7 to < 53.5 [micro]g/L) and low alcohol consumption (< 26.6 mL/day). The depression score in model LM3, which represents 22 ex-miners with higher past occupational exposure (mean cycle U-Hg > 53.5 [micro]g/L), is not consistent with the expectations observed in model LM2 at an intermediate cycle U-Hg level. The higher consumption of alcohol per se associated with number of cigarettes smoked per day in the model LM4 (> 26.6 mL/day) tends to increase the depression score in 14 ex-mercury miners and 10 controls. If the dental amalgam score is interpreted as the number of repaired teeth improving external appearance (and not as an additional source of occupational exposure), this could be associated with the partial reduction of the depression score among persons in the LM4 model.

In the group with higher alcohol consumption (> 26.6 mL/day) in the LM4 model, the mean GGT concentration in serum (0.99 [+ or -] 0.75 [micro]katal/L) was slightly increased (95th percentile value of the normal male population is 0.92 [micro]katal/L) and significantly higher (p < 0.05) than in the subgroups with lower alcohol consumption (< 26.6 mL/day) in the LM1 (0.45 [+ or -] 0.29 [micro]katal/L) and LM3 (0.45 [+ or -] 0.47 [micro]katal/L) models but statistically insignificantly lower in comparison with the subgroup in the LM2 model (1.44 [+ or -] 2.7 [micro]katal/L). On the basis of mean GGT values in serum, we have assumed that alcohol consumption in these subgroups of ex-miners was also increased during occupational exposure in the past (Joachim 1995).

The model tree predicting the negative self-concept score presented in Figure 3 is constructed on the group of miners and controls. The model tree contains two leaves with one linear model each (LM1 and LM2). Model LM1 represents 50 controls and 3 ex-mercury miners with a relatively low negative self-concept score. Age and alcohol consumption partly increased their negative self-concept score. LM2, which represents ex-mercury miners (n = 47, only miners with last exposure U-Hg > 10 [micro]g/L), associates the negative self-concept score with the mean cycle U-Hg level (> 32.5 [micro]g/L) and the U-Hg level at last exposure. The cumulative U-Hg peak level did not increase the observed score.

Discussion

The present exposure to [Hg.sup.0] was low in both groups and at a level in the general population that is not associated with particular, actual sources of Hg (Minoia et al. 1990; Nordberg et al. 1992; Schaller et al. 1983; Yamamura 1990). The geometric means of cycle U-Hg levels (range, 20-120 [micro]g/L) represent reliable averages of the internal doses of [Hg.sup.0] received by ex-miners during previous occupational exposure. This range of U-Hg levels can be found in many studies (WHO 2003) and, generally speaking, also in our long-term observations (Kobal 1975, 1991; Kobal et al. 1999) associated with neurotoxic effects. Considering the above-mentioned level of [Hg.sup.0] doses received and the results of quoted postmortem studies of ex-mercury miners (Byrne et al. 1995; Falnoga et al. 2000; Kosta et al. 1975), it may be presumed that the accumulation and retention of Hg in the central nervous systems of observed miners during occupational exposure was moderate but characterized by considerable interindividual variability.

The results obtained from the EPQ showed significant differences at the group level between ex-mercury miners and controls. The lower EPQ score of extraversion found in ex-mercury miners suggests that miners are less outgoing and more introverted than the control group. The influence of age on extraversion in males has been reported in some studies (Eysenck and Eysenck 1975; Lojk 1981) but not in ex-mercury miners as opposed to controls (r = -0.39, p = 0.001). It is evident from the regression tree that the lower score on the lie scale (EPQ) of ex-mercury miners is not associated with indices of [Hg.sup.0] exposure but increases slightly with alcohol consumption and prominently with age in the subgroup of retired miners. A moderate correlation between age and lie score was also observed on the group level (r = 0.47, p = 0.000). The lower lie score in the subgroup of younger ex-mercury miners (< 54.5 years) suggests that sincerity could be an important personality trait enabling miners to preserve their collaborative and team-working spirit in the mine.

The results obtained from the ESQ also showed significant differences at the group level between miners and the control group. Ex-mercury miners tend to be more rigid in expressing their emotions but are significantly more depressive and are likely to have a more negative self-concept than the members of the control group (p < 0.01). The relative indifference (emotional rigidity) expressed by the indifference score seems to be a common characteristic of ex-mercury miners, which correlated well with the depression score of miners (r = 0.607, p = 0.000). The indifference established in miners in the period after exposure is in genuine contradiction to the known emotional lability that is typical for the state of increased absorption and chronic occupational intoxication with [Hg.sup.0] (Hribernik 1950; Kobal 1975; WHO 2003).

It is evident from the regression tree in Figure 2 that permanent, increased alcohol consumption per se (> 26 mL/day) increases depression in the subgroup of ex-mercury miners and controls, which is also reported in other studies (Leibenluft et al. 1993; Schuckit 1986). Individual susceptibility due to the interaction of [Hg.sup.0] and alcohol could be a possible explanation for the higher depression score observed in 6 ex-miners (with slightly increased GGT) at an intermediate mean cycle U-Hg level (> 38.7 < 53.5 [micro]katal/L) compared with 22 ex-mercury miners with a higher mean cycle of U-Hg (> 53.5 [micro]katal/L). Theoretically, such interactions also cannot be completely excluded among ex-miners from the subgroup with higher alcohol consumption. It is known that after inhalation, [Hg.sup.0] enters the bloodstream, where it undergoes oxidation in red blood cells by the hydrogen peroxide catalase pathway (Halbach and Clarkson 1978). The oxidation of [Hg.sup.0] can be inhibited by ethanol (Nielsen-Kudsk 1973), which could increase the accumulation of Hg in the brain (Magos et al. 1989). The differences in enzyme function could be a likely basis for the different response to [Hg.sup.0] in the observed subgroup of ex-miners.

It is evident from the regression tree in Figure 3 that the root node of the tree separated the whole population in the miner and control groups. The internal doses received during past occupational exposure, expressed by a geometric mean of cycle U-Hg level above 32.5 [micro]g/L, seems to be a basic independent variable that separated the two groups and selected 47 ex-mercury miners with a higher negative self-concept. As evident from the constructed model, the cumulative U-Hg peak level is obviously not the most suitable indicator of the total mean internal dose received during past exposure. As mathematic values, the mean cycle U-Hg level and the cumulative U-Hg peak level are in contrast. The first indicator represents the mean of all U-Hg values in which lower values are dominant, and the other indicator represents only the highest values of all exposure cycles.

[FIGURE 3 OMITTED]

However, the correlation between depression and negative self-concept (r = 0.757, p = 0.000) dearly shows that negative self-concept is accompanied with increased depression in subgroups of miners presented in the model tree predicting the depression score. It could be suggested that further investigations including more refined measures of self-concept and self-esteem, and measures of affect (positive and negative) as possible moderators, buffers, or mediators of personality Hg exposure relationship should be done.

Scopoli (1771) precisely described the symptoms and signs of occupational poisoning with [Hg.sup.0] and specifically mentions the "unusually sad mental state of these workers." Alternations of emotional state, mood, and some unspecific symptoms were most frequently observed at U-Hg levels ranging from 30 to 100 [micro]g/L (Piikivi and Hanninen 1989; Piikivi et al. 1984; Roels et al. 1985; WHO 1991), whereas in some studies these were also observed at lower levels of occupational exposure, that is, at U-Hg mean levels ranging from 30 to 40 [micro]g/L (Echeverria et al. 1995; Soleo et al. 1990). In the study by Soleo et al. (1990) and Echeverria et al. (1995), the personalities of exposed workers were considerably changed at lower levels of occupational exposure, whereas certain mood measures were associated with Hg exposure. In patients not occupationally exposed to [Hg.sup.0] who attributed their illness to Hg from amalgam fillings, a subtle preclinical effect on mood (Echeverria et al. 1998), depression, less extraversion, and more emotional lability were detected (Grandjean et al. 1997). Only a few investigations using the measurements of neuropsychologic effects to study workers previously exposed to [Hg.sup.0] are available to our knowledge (Kishi et al. 1994; Letz et al. 2000; Mathiesen et al. 1999). Mood scales (tension, depression, anger, fatigue, and confusion) were applied only in the study of Letz et al. (2000), but no residual mood changes with depression have been observed.

Any disturbance of the balance between serotonin and melatonin can, in the opinion of certain researchers (van Heeringen 2001), influence the occurrence of depression. Some studies have reported a decreased nocturnal melatonin concentration in the blood of depressed patients (Beck-Friis et al. 1985; McIntyre et al. 1986; Wetterberg 1985). In our ex-mercury miners, however, we detected precisely the opposite, that is, an increased concentration of melatonin in morning blood samples (Kobal et al. 2004). Theoretically, consideration should also be given to the potential impacts of Hg on the metabolism of neurotransmitters (Mottet et al. 1997) and the impacts of increased accumulation of Hg in the pineal gland itself (Falnoga et al. 2000; Kosta et al. 1975), which might also influence the synthesis of melatonin and, indirectly, the balance of serotonin and melatonin (Kasper et al. 1996). In evaluating the potential synergistic neurotoxic impacts of alcohol and Hg, which, in the opinion of certain authors (Halliwell and Gutteridge 1989; Lund et al. 1993; Mottet et al. 1997), are connected with the increased production of free radicals, we must nevertheless consider its interaction with antioxidative enzyme catalase in erythrocytes (Halbach and Clarkson 1978).

This depressive mood itself, especially in association with negative self-concept, could consequently increase the risk of suicide among miners of the Idrija Mercury Mine. Other studies (Kobal Grum 2003) also indicate that a low or negative self-concept could be a significant factor for suicidal behavior. Researchers exploring this variable have maintained that poor self-concept can lead to self-loathing and to consideration of suicide (Harter and Marold 1994). However, the increased mortality due to suicide among miners of the Idrija Mercury Mine in the last 45 years (period of follow-up, 1950-1995; number of miners, 1,589; number of observed suicides, 40; standardized mortality ratio, 123; 95% confidence interval, 88-168; unpublished data) cannot completely confirm the relation between occupational exposure to [Hg.sup.0] in interaction with permanent alcohol consumption and depression with associated negative self-concept as one of the potential causes of suicidal behavior. This is primarily because the results of the epidemiologic study on the mortality of miners in four mercury mines (Boffetta et al. 1998) are not consistent, probably due to errors in the classification of the cause of death in some countries, or due to variations in psychosocial or genetic risk factors (Marusic and Farmer 2001). Despite the inconsistent results of the above-mentioned epidemiologic study, our assumption is also supported by a rough comparison of the share (%) of ex-miners in the subgroup with increased depression (considering only the six miners with moderate [Hg.sup.0] exposure and moderate alcohol consumption), which is slightly above 11%, and the share (%) of suicides resulting in death among the miners of the Idrija Mercury Mine in the past 45 years, which has attained 2.5%.

Conclusions

The results obtained in the present study have shown some significant differences, on the group level, in the personality traits of ex-mercury miners compared with controls. Ex-mercury miners are less extraverted, more sincere, more rigid in expressing their emotions, more depressive, and have a more negative self-concept. The lack of correlation between the established target variables of personality traits of ex-mercury miners and the indicators of past occupational exposure on the group level, and the small number of persons in certain subgroups constructed in model trees are the main obstacles preventing the more reliable interpretation of results obtained. Despite these limitations, the abovementioned theoretical outline and our results suggest that permanent higher alcohol consumption per se, at low levels of [Hg.sup.0] exposure, and the mutual interaction of long-term increased exposure to [Hg.sup.0] with long-term moderate alcohol consumption have presumably had a decisive influence on the development of depression associated with negative self-concept in the subgroup of ex-mercury miners observed. This could, together with other psychosocial factors, be one of the potential reasons for the higher rate of suicide among miners of the Idrija Mercury Mine observed in the last 45 years.

The study thus provides further support to the efforts of other studies aimed at reducing the occupational exposure levels of [Hg.sup.0] to the lowest observed adverse effect level (United Nations Environment Programme 2002; WHO 2003) capable of preventing not only the actual effects on the central nervous system but also the late effects of [Hg.sup.0] exposure on the potential development of depression and negative self-concept, which can significantly decrease resistance toward psychosocial stress factors. The results of the present study suggest that alcohol consumption, although moderate, is not always beneficial and could be avoided during actual occupational exposure to [Hg.sup.0].

REFERENCES

Albers JW, Kallenbach LR, Fine Ld, Langolf GD, Wole RA, Donofrio PD, et al. 1988. Neurological abnormalities associated with remote occupational elemental mercury exposure. Ann Neurol 24:651-659.

Andersen A, Ellingsen DG, Morland T, Kjuus H. 1993. A neurological and neurophysiological study of chloralkali workers previously exposed to mercury vapor. Acta Neurol Scand 88:427-433.

Aposhian HV, Bruce DC, Alter W, Dart C, Hudbut KM, Aposhian MM. 1992. Urinary mercury after administration of 2,3-dimercaptopropane-1-sulfonic acid: correlation with dental amalgam score. FASEB J 6:2472-2476.

Beck-Friis J, Ljunggren JG, Thoren M, Rosen D, Kjellman BF, Wetterberg L. 1985. Melatonin, cortisol and ACTH in patients with major depressive disorders and healthy humans with special reference to the outcome of the dexamethasone suppression test. Psychoneuroendocrinology 10:173-186.

Boffetta P, Garcia-Gomez M, Pompe-Kirn V, Zarizde D, Bellander T, Bulbulyan M, et al. 1998. Cancer occurrence among European mercury miners. Cancer Causes Control 9:591-599.

Breiman L, Friedman JH, Olshen RA, Stone CJ. 1984. Classification and Regression Trees. Belmont, CA:Wadsworth International Group.

Byrne AR, Skreblin M, Falnoga I, Al-Sabti K, Horvat M. 1995. Mercury and selenium: perspectives from Idrija. Acta Chim Slov 42:175-198.

Echeverria D, Aposhian HV, Woods JS, Heyer NJ, Aposhian MM, Bittner AC, et al. 1998. Neurobehavioral effects from exposure to dental amalgam: new distinctions between recent exposure and Hg body burden. FASEB J 12:971-980.

Echeverria D, Heyer NJ, Martin MD, Naleway CA, Woods JS, Bittner AC. 1995. Behavioral effects of low-level exposure to [Hg.sup.0] among dentists. Neurotoxicol Teratol 17:161-168.

Ellingsen DG, Morland T, Andersen A, Kjuus H. 1993. Relation between exposure related indices and neurological and neurophysiological effects in workers previously exposed to mercury vapour. Br J Ind Med 50:736-744.

Eysenck HJ, Eysenck SBG. 1976. Manual of Eysenck Personality Questionnaire. London:Hodder & Stoughton.

Falnoga I, Tusek-Znidric M, Horvat M, Stegnar P. 2000. Mercury, selenium and cadmium in human autopsy samples from Idrija residents and mercury mine workers. Environ Res 84:211-218.

Grandjean P, Guldager B, Larsen IB, JOrgensen PJ, HOlmstrup P. 1997. Placebo response in environmental disease, chelation therapy of patients with symptoms attributed to amalgam fillings. J Occup Environ Med 8:707-714.

Halbach S, Clarkson TW. 1978. Enzymatic oxidation of mercury vapor by erythrocytes. Biochem Biophys Acta 523:522-531.

Halliwell B, Gutteridge JMC. 1989. Free Radicals in Biology and Medicine. 2nd ed. Oxford, UK:Clarendon Press.

Harter S, Marold D. 1994. The directionality of the link between self esteem and depressed affect: beyond causal modeling. In: Rochester Symposium on Developmental Psychopathology. Vol 5: Disorders and Dysfunctions of the Self (Cicchetti D, Toth SL, eds). Rochester, NY:University of Rochester Press, 333-369.

Horvat M, Begic I, Prosenc A, Konda D, Smrke J, Byrne AR, et el. 1991. A study of some trace elements in human hair and the foeto placental system in women from Central Slovenia. In: Trace Elements in Health and Disease (Aitio A, Aro A, Jarvisalo J, Vainio H, eds). Cambridge, UK:Royal Society of Chemistry, 83-91.

Horvat M, Zvonaric T, Stegnar P. 1986. Optimization of a wet digestion method for the determination of mercury in blood by cold vapour atomic absorption spectrometry (CV AAS), Vestn Slov Kern Drus 33:475-487.

Hribernik I. 1950. Nasa opazovanja o prefesionalnem zastrupljenju u ziovim srebrom v Idriji (1946-1950) [in Slovene]. [Transl.: Our observations of professional mercury intoxications in Idrija (1946-1950)]. Arh Hig Rada 1:291-299.

Joachim H. 1995. Clinical chemistry proof of alcohol abuse. Dtsch Med Wochenschr 120:585-588.

Karalic A. 1992. Employing linear regression in regression tree leaves. In: Proceedings of the 10th European Conference on Artificial Intelligence (ECAI '92), 3-7 August 1992, Vienna, Austria (Neuman B, ed). New York:John Wiley & Sons, 440-441.

Kasper S, Neumeister A, Rieder N, Hesselmann B, Ruhrmannn S. 1996. Serotonergic mechanisms in the pathophysiology and treatment of seasonal affective disorder. In: Biologic Effects of Light (Holick MF, ed). Berlin:W. de Gruyter, 325-331.

Kishi R, Doi R, Fukuchi Y, Satoh H, Satoh T, One A, et al. 1994. Residual neurobehavioural effects associated with chronic exposure to mercury vapour. Occup Environ Med 51:35-41.

Kobal AB. 1975. Profesionalna Ekspozicija Anorganskemu Zivemu Srebru in Spremembe v Serumskih Proteinih [in Slovene] [MSc Thesis]. Zagreb:University of Zagreb.

Kobal AB. 1991. Poklicna Izpostavljenost Elementarnemu Zivemu Srebru in Vsebnost Zivega Srebra v Krvi, Eritrocitih, Plaz'mi, Izdihanemu Zraku in Urinu ter Aktivnost Katalaze v Eritrocitih [in Slovene, abstract in English] [PhD Thesis]. Ljubljana, Slovenia:University of Ljubljana.

Kobal AB, Dizdarevic T. 1997. The health safety programme for workers exposed to elemental mercury at the mercury mine in Idrija. Water Air Soil Pollut 97:169-184.

Kobal AB, Horvat M, Prezelj M, Kobal Grum D, Sesek BA, et al. 2004. The impact of long-term past exposure to elemental mercury on antioxidative capacity and lipid peroxidation in mercury miners. J Trace Elem Med Biol 17:261-274.

Kobal AB, Nanut E, Horvat M, Stegnar P, Sabadin A. 1999. Evaluation of internal doses of mercury at intermittent exposure to elemental mercury at the mine in Idrija. In: Mercury Contaminated Sites (Ebinghaus R, Turner RR, de Lacerda LD, Vasiliev O, Salomons W, eds). Berlin/Heidelberg:Springer-Verlag, 271-279.

Kobal D. 2000. Basic Aspects of Self-Concept. Ljubljana, Slovenia:Pedagoski Institut, 87-127.

Kobal Grum D. 2003. Beings of Self-Concept. Ljubljana, Stovenia:i2,173-185.

Kosta L, Byrne AR, Zelenke V. 1975. Correlation between selenium and mercury in man following exposure to inorganic mercury. Nature 254:238-239.

Lamovec T. 1988. Prirocnik za Psihologijo Motivacije in Emocij [in Slovene]. Univerza v Ljubljani, Filozofska Fakulteta, Oddelek za Psihologijo, 241-256.

Lamovec T. 1989. Emocije in Obrambni Mehanizmi [in Slovene]. Ljubljana, Slovenia:Zavod SR Slovenije za Produktivnost Dela, Center za Psihodiagnosticna Sredstva.

Leibenluft E, Fiero PL, Bartko JJ, Morel DE, Rosenthal NE. 1993. Depressive symptoms and the self reported use of alcohol, caffeine and carbohydrates in normal volunteers and four groups of psychiatric outpatients. Am J Psychiatry 150(2):294-301.

Letz R, Gerr F, Cragle D, Green RC, Watkins J, Fidler AT. 2000. Residual neurologic deficits 30 years after occupational exposure to elemental mercury. Neurotoxicology 21:459-474.

Lojk L. 1981. EPQ Eysenckov Osebnostni Vprasalnik, Prirocnik [in Slovene]. Ljubljana, Slovenia:Zavod SR Slovenije za Produktivnsot Dela.

Lund BO, Miller DM, Woods JS. 1993. Studies on Hg (II)-induced [H.sub.2][O.sub.2] formation and oxidative stress in vivo and in vitro in rat kidney mitochondria. Biochem Pharmacol 45:2017-2024.

Magos L, Clarkson TW, Hudson AR. 1989. The effects of dose of elemental mercury and first-pass circulation time on exhalation and organ distribution of inorganic mercury in rats. Biochem Biophys Acta 99:85-89.

Marks DB, Marks AD, Smith CM. 1996. Basic Medical Biochemistry. Baltimore, MD:Williams & Wilkins.

Marusic A, Farmer A. 2001. Genetic risk factors as possible causes of the variation in European suicide rates. Br J Psychiat 179:61-65.

Mathiesen T, Ellingsen D, Kjuus H. 1999. Neuropsychological effects associated with exposure to mercury vapor among former chloralkali workers. Scand J Work Environ Health 5:342-350.

McIntyre IM, Judd FK, Norman TR, Burrows GD. 1985. Plasma melatonin levels in depression. Australia and New Zealand. J Psychiatr 20:381-383.

Minoia C, Sabbioni E, Apostoli P. 1990. Trace elements reference values in tissues from inhabitants of the European Community. A study of 46 elements in urine, blood, and serum of Italian subjects. Sci Total Environ 95:89-105.

Mortensen EL, Reinisch JM, Sanders SA. 1996. Psychometric properties of the Danish 16PF and EPQ. Scand J Psychol 37:221-225.

Mottet NK, Vahter ME, Charleston JS, Friberg LT. 1997. Metabolism of methylmercury in the brain and its toxicological significance. In: Metal Ions in Biological Systems (Sigel A, Sigel H, eds). New York:Marcel Dekker, 371-403.

Nielsen-Kudsk F. 1973. Biological oxidation of elemental mercury. In: Mercury, Mercurials and Mercaptans (Miller MW, Clarksen TW, eds). Springfield, IL:Charles C. Thomas, 355-371.

Nordberg GF, Brune D, Gerhardsson L, Grandjean P, Vesterberg O, Wester PO. 1992. The ICOH and IUPAC international programme for establishing reference values of metals. Sci Total Environ 120:17-21.

Piikivi L, Hanninen H. 1989. Subjective symptoms and psychological performance of chlorine-alkali workers. Scand J Work Environ Health 15:69-74.

Piikivi L, Hanninen H, Martelin T, Mantere P. 1984. Psychological performance and long-term exposure to mercury vapors. Scand J Work Environ Health 10:35-41.

Quinlan JR. 1992. Learning with continuous classes. In: Proceedings of the Australian 5th Joint Conference on Artificial Intelligence, 16-18 November 1992, Hobart, Australia. (Adams A, Stealing L, eds). Singapore:World Scientific, 343-348.

Reels H, Gennart JP, Lauwerys R, Buchet JP, Malchaire J, Bernard A. 1985. Surveillance of workers exposed to mercury vapour: validation of previously proposed biological threshold limit value for mercury concentration in urine. Am J Ind Med 7:45-71.

Schaller KH, Breininger M, Schiele R. 1983. Der Quecksilberspiegel fur Blut und Urin bei Normalpersonen. Arztliches Laboratorium 29:325-334.

Schuckit MA. 1986. Genetic and clinical implications of alcoholism and affective disorder Am J Psychiatry 143:140-147.

Scopoli JA. 1771. De Hydrorgyro Idriensi Tentamina Physico-Chymica-Medica. 2nd ed. Janae et Lipsiae, DEU:Joann. Gull. Hartung.

Sjoberg L, Swensson E. 1976. The Polarity and Dimensionality of Mood. Goteborg, Sweden:University of Goteborg.

Soleo L, Urbano ML, Petrera V, Ambrosi L. 1990. Effects of low exposure to inorganic mercury on psychological performance. Br J Ind Med 47:105-109.

United Nations Environment Programme. 2002. Global Mercury Assessment. Geneva:UNEP Chemicals.

van Heeringen K. 2001. Suicide, serotonin and the brain. Criss 22:66-70.

Vogt WP. 1993. Dictionary of Statistics and Methodology: A Nontechnical Guide for the Social Sciences. London:Sage Publications.

Wang Y, Witten IH. 1997. Induction of model trees for predicting continuous classes. In: Proceedings of the Poster Papers of the European Conference on Machine Learning (ECML '97), 23-25 April 1997, Prague, Czech Republic. (van Someren M, Widmer G, eds). Prague:University of Economics, Faculty of Informatics and Statistics, 126-137.

Wetterberg L. 1985. Melatonin and affective disorders. Ciba Found Symp 117:253-265.

WHO. 1975. Mercury. Environmental Health Criteria 1. Geneva:World Health Organization.

WHO. 1991. Inorganic Mercury. Environmental Health Criteria 118. Geneva:World Health Organization.

WHO. 2003. Elemental Mercury and Inorganic Mercury Compounds: Human Health Aspects. Concise International Chemical Assessment Document 50. Geneva:World Health Organization.

Witten IH, Frank E. 1999. Data Mining: Practical Machine Learning Tools and Techniques with JAVA Implementations. San Francisco:Morgan Kaufmann.

Yamamura Y. 1990. Mercury concentrations in blood and urine as indicators of exposure to mercury vapour. In: Biological Monitoring of Exposure to Industrial Chemicals (Fiserova-Bergerova V, Ogata M, eds). Cincinnati, OH:American Conference of Industrial Hygienists, 113-117.

This article is part of the mini-monograph "Health Effects of Mercury."

Address correspondence to D. Kobal Grum, Department of Psychology, Faculty of Arts, University of Ljubljana, 1000 Ljubljana, Slovenia. Telephone: [phone]. Fax: [phone]. E-mail: [e-mail]

We thank the Ministry of Education, Science and Sport, and the Idrija Mercury Mine for their financial support throughout the project (grant 3411-9823 0304, project L3-0304-0312-98).

The authors declare they have no competing financial interests.

Received 22 November 2004; accepted 14 June 2005.

Darja Kobal Grum, (1) Alfred B. Kobal, (2) Niko Arneric, (3) Milena Horvat. (4) Bernard Zenko. (5) Saso Dzeroski. (5) and Josko Osredkar (6)

(1) Department of Psychology, Faculty of Arts, University of Ljubljana, Slovenia; (2) Department of Occupational Medicine, Idrija Mercury Mine, Idrija, Slovenia; (3) Clinical Institute of Occupational, Traffic and Sports Medicine, University Medical Centre, Ljubljana, Slovenia, Departments of (4) Environmental Sciences and (5) Knowledge Technologies, Jozef Stefan Institute, Ljubljana, Slovenia; (6) University Medical Centre Ljubljana, Clinical Institute of Clinical Chemistry and Biochemistry, Ljubljana, Slovenia

Table 1. Reliability coefficients of ESQ.

Behavior                                      Guttman
characteristics          Cronbach [alpha]    split-half

Depression                     0.85             0.83
Contentment                    0.86             0.87
Aggression                     0.68             0.65
Indifference                   0.67             0.67
Positive self-concept          0.71             0.65
Negative self-concept          0.71             0.73
  Total                        0.89             0.84

Table 2. Characteristics of observed groups.

                               Miners                 Controls
                               (n=53)                  (n=53)
Characteristics           Mean [+ or -] SD        Mean [+ or -] SD

Age                     47.32 [+ or -] 9.90     44.64 [+ or -] 8.54
BMI (kg/[m.sup.2])       27.8 [+ or -] 4.1       27.4 [+ or -] 4.1
Dental amalgam score     12.8 [+ or -] 12.4      12.5 [+ or -] 10.9
Fish meals/week          0.52 [+ or -] 0.96      0.59 [+ or -] 0.88
Cigarettes/day (a)       21.6 [+ or -] 7.3       20.5 [+ or -] 9.5
Alcohol (mL/day) (b)     35.2 [+ or -] 40.2      22.4 [+ or -] 18.6
B-THg ([micro]g/L)        2.5 [+ or -] 1.5        2.5 [+ or -] 1.2
U-Hg ([micro]g/g
  creatinine)             2.1 [+ or -] 1.4        1.4 [+ or -] 1.1

Characteristics         p-Value

Age                      0.072
BMI (kg/[m.sup.2])       0.536
Dental amalgam score     0.912
Fish meals/week          0.649
Cigarettes/day (a)       0.693
Alcohol (mL/day) (b)     0.099
B-THg ([micro]g/L)       0.158
U-Hg ([micro]g/g
  creatinine)            0.003

(a) Percentage of smokers: miners, 59%; controls, 41%.
(b) Percentage of alcohol consumers > 20 mL/day: miners, 28%;
controls, 19% (p > 0.05). Data from Kobal et al. (2004).

Table 3. External and biological indices of previous
occupational [Hg.sup.0] exposure in miners (n = 53).

                                      Geometric
Indices                            mean [+ or -] SD         Range

Years of exposure                 14.6 [+ or -] 5.5          7-31
Cycles of exposure                  41 [+ or -] 21          13-119
ATW air [Hg.sup.0]                0.29 [+ or -] 0.08      0.14-0.45
concentration (mg/[m.sup.3])
Cycle U-Hg level ([micro]g/L)     53.1 [+ or -] 20.5        20-120
Cycle peak U-Hg level             77.2 [+ or -] 23.0        40-134
  ([micro]g/L)
Cumulative U-Hg level            6,584 [+ or -] 4,444    1,286-21,390
  ([micro]g/L)
Cumulative peak U-Hg             3,900 [+ or -] 2,196     794-11,365
  level ([micro]g/L)
Last exposure U-Hg                  26 [+ or -] 29          8-135
  level ([micro]g/L)

Table 4. Average scores on the EPQ of observed groups.

                   Miners (n=53)         Controls (n=53)

EPC              Mean [+ or -] SD       Mean [+ or -] SD      p-Value

Psychoticism     3.80 [+ or -] 2.37     3.74 [+ or -] 2.06     0.905
Extraversion    12.09 [+ or -] 3.81    13.93 [+ or -] 3.15     0.017
Neuroticism      8.14 [+ or -] 4.27     7.55 [+ or -] 4.21     0.522
Lie             12.45 [+ or -] 4.22    15.05 [+ or -] 3.54     0.003

Table 5. Average scores on the ESQ. of observed groups.

                               Miners                Controls
                               (n=53)                 (n=53)

ESQ                       Mean [+ or -] SD       Mean [+ or -] SD

Depression               20.33 [+ or -] 5.07    17.73 [+ or -] 3.61
Contentment              30.52 [+ or -] 4.97    31.05 [+ or -] 6.06
Aggressions              17.17 [+ or -] 4.20    15.95 [+ or -] 2.71
Indifference              9.74 [+ or -] 2.73     8.51 [+ or -] 2.11
Positive self-concept    15.52 [+ or -] 3.16    16.51 [+ or -] 2.91
Negative self-concept     8.98 [+ or -] 2.51     7.68 [+ or -] 1.71

ESQ                      p-Value

Depression                0.009
Contentment               0.667
Aggressions               0.122
Indifference              0.025
Positive self-concept     0.143
Negative self-concept     0.008