American Journal of Industrial Medicine 22:325-335 (1992)
Neurobehavioral Effects of Long-Term Occupational Exposure to Organic Solvents: Two Comparable Studies A. Spurgeon, PhD, C.N. Gray, PhD, J. Sims, PhD, 1. Calvert, MA, L.S. Levy, PhD, P.G. Harvey, PhD, and J.M. Harrington, MD
Two comparable cross-sectional studies were carried out employing the same methodology but involving two separate solvent-exposed populations (N = 90, N = 144). In each study, solvent-exposed workers were compared with age-matched controls on tests selected from the Neurobehavioral Evaluation System and on standardized questionnaire measures of symptomatology and psychiatric state. A similar pattern of results was obtained in the two studies indicating a significant effect on cognitive functioning, after controlling for confounding variables, occurring in those with more than 30 years of exposure. A more specific effect on learning processes was observed in those with more than 10 years of exposure. There were no indications in either study of a solvent-related increase in psychiatric symptoms. o 1992 WiIey-Liss, Inc. Key words: long-term solvent exposure, psychiatric symptoms, painters, neurobehavioral testing
INTRODUCTION
During the last 25 years, the results of a number of epidemiologic studies have suggested that long-term occupational exposure to organic solvents may result in damage to the central nervous system [Hanninen et al., 1976; Hane et al., 1977; Eloffson et al., 1980; Cherry et al., 1985; Mikkelsen et al., 1988; Baker et al., 1988; Bleecker et al., 19911. Behavioral manifestations of such damage include an increase in psychiatric symptoms, reported memory and concentration difficulties, and impairment of cognitive functioning as demonstrated by performance on neurobehavioral tests. In many cases these effects are subtle, occumng in the absence of overt clinical signs and only measurable by use of psychological test procedures. Since such effects cannot be mimicked in animal models and because of the dearth of information concerning dose-effect relationships, there is continuing controversy Institute of Occupational Health, University of Birmingham, Edgbaston, Birmingham, England ( A S . , I.C., L.S.L., J.M.H.). Deakin University, Geelong, Australia (C. N .G.). Free University of Amsterdam, Amsterdam, The Netherlands (J.S.). Central Birmingham Health Authority, Birmingham, England (P.G.H.). Address reprint requests to Dr. A. Spurgeon, Institute of Occupational Health, University of Birmingham, Edgbaston, Birmingham B15 2TT, England. Accepted for publication February 3, 1992.
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about the nature and severity of the problem. This debate has recently been renewed in Denmark where concern over occupational solvent exposure originated and where some scientists have recently challenged the conclusions of the earlier data [ErreboKnudsen and Olsen, 1986; Gade et al., 19881. There are numerous methodological difficulties in this area associated, for example, with the elimination of selection bias in the exposed populations, appropriate matching of controls, avoidance of acute effects in the assessment of long-term damage, and the influence of other factors on test performance. In particular, some of the possible inconsistency in results may be accounted for by the wide range of neurobehavioral assessment methods employed and by the lack of a standardized approach to psychological testing. In recent years, there has been a move toward harmonization of methods with the development of test batteries designed specifically for the purpose of assessing and monitoring the effects of neurotoxicants in occupational settings. In addition, the use of computer administered tests has enhanced the standardization of testing procedure and scoring, as well as providing for increased comparability of results. The present investigation employed one such test battery, the Neurobehavioral Evaluation System, (NES) [Baker et al., 19851 in two comparable cross-sectional studies where the same methodology was employed on two separate solvent-exposed populations. In addition, the psychiatric status and the frequency of symptom reporting in the exposed population were compared with those of the controls using standardized questionnaires, which are well supported by a quantity of normative data. The objectives of the present investigation therefore were 1) to establish whether the performance of the solvent exposed populations was significantly poorer than that of the controls in neurobehavioral tests reputed to be sensitive to the effects of nervous system damage; 2) to establish whether the psychiatric status and health of the solvent exposed workers were inferior to those of the controls; 3) to establish whether a dose-effect relationship existed where there was any observed impairment of cognitive performance or psychiatric status; and 4) to compare the patterns of neurobehavioral performance and symptomatology observed in the two studies. MATERIALS AND METHODS Populations In Study I, the exposed population consisted of 90 brush painters employed by hospital maintenance departments in a large UK health authority. The study population represented 67% of all those painters employed by the authority. Twenty-nine percent were unwilling to take part in the study and 4% were excluded due to pre-set exclusion criteria, namely previous head injury, alcohol or drug dependency, or existing disease affecting the nervous system. Exposed subjects were individually age-matched with randomly selected maintenance workers employed on the same sites whose occupations did not involve significant solvent exposure. In Study 11, the exposed population consisted of 144 solvent-exposed workers drawn from three organizations, namely the Ministry of Defense, a further regional health authority, and the maintenance section of a large city housing department. They represented a range of occupations, i.e., brush painters, paintsprayers, printers, coach trimmers, boat builders, and degreasers. The study population represented 83% of available subjects. Five percent refused to take part, 2% were excluded, and
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suitable controls were unavailable for the remaining 10%. Individually age-matched controls were again randomly selected from non-exposed maintenance workers employed on the same sites. In both studies, all participants were male and U.K.-born, i.e., English was their first language. The age range was 21-65 years. Measures In both studies, exposed subjects and controls completed a series of computer-administered psychological tests drawn from the NES. In Study I, these were Symbol-Digit-Substitution (SDS), Pattern Memory (PM), Serial Digit Learning (SDL), Switching Attention (SA), and Continuous Performance Test (CPT). These tests were selected to assess a range of cognitive functions and also included one test (SDS) known to be extremely sensitive to CNS damage regardless of its etiology or location. These tests were repeated in Study I1 with the following exceptions. SA proved too difficult for most subjects and was thus replaced with two additional learning tests: Paired Associate Learning (PAL) and the longer-term recall test, Associate Recall Test (ART), involving re-administration of items at the end of the test battery. The CPT was replaced with a Simple Reaction Time test (SRT) because of indications from other studies [Iregren, 1982; Cherry et al., 19851 that reaction time tests are particularly sensitive to the effects of solvent exposure. In both studies, the vocabulary test from the NES was included as a measure of pre-morbid ability. The National Adult Reading Test (NART) [Nelson, 19821 was included as an additional measure in Study I1 in accordance with recommendations of the WHO working group [WHO, 19891 which suggested that two measures of premorbid ability should be employed. There is considerable evidence to suggest that the NART is both resistant to CNS damage and correlates highly with I.Q. as conventionally measured, [Nelson, 19821. Standardized questionnaire outcome measures were as follows. 1. The General Health Questionnaire (GHQ) was employed to assess psychiatric morbidity [Goldberg, 19781. This is a well-established questionnaire designed to screen for psychiatric morbidity in community and occupational samples and includes assessment of both minor and severe psychiatric symptoms. Threshold values for those considered “at risk” of developing psychiatric illness are provided which allow for a comparison of the number of individuals in each group falling above and below the threshold. In Study I, the 30 item version was used. Because of increased time availability, however, the 60 item version, allowing increased sensitivity, was used in Study 11. 2. The Cognitive Failures Questionnaire (CFQ) was included to assess self-reported memory difficulties. This questionnaire is also supported by data on reliability and validity and has been used in other studies to assess behavioral memory in relation to environmental and individual factors [Broadbent et al., 19821. 3. The Orebro 16-item questionnaire [Hogstedt et al., 19841 was used to assess frequency of symptom reporting. This questionnaire was developed specifically as a screening tool for solvent-exposed workers, and some normative data on such populations are available [Hogstedt et al., 19841.
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In addition to psychological tests and standardized questionnaires, all participants completed an occupational history questionnaire together with questionnaires concerned with educational level, computer experience, alcohol consumption, and with more immediate influences on test performance, namely recent virus infections, medication use, and sleep loss. Procedure Participants were tested in groups of four in a mobile laboratory driven to their workplace. Questionnaires were completed in an adjacent room. Testing for both exposed subjects and controls took place in the morning immediately before work commenced, i.e., prior to solvent exposure, and controlling for time-of-day effects on the tests. In Study I, 63% of exposed subjects and in Study 11, 75% of exposed subjects were tested on a Monday morning, i.e., at least 48 hours had elapsed since their last solvent exposure. The remainder were tested on a Tuesday morning with at least 12 hours having elapsed since last exposure. In Study I, exhaled breath samples were taken from all participants prior to testing and analyzed for solvent content using a mass spectrometer. Since these were negative for all subjects including those tested on Tuesdays (detection limits for toluene, xylene, and white spirit < 1 ppm), this procedure was not repeated in Study 11. In both studies, the time spent by participants on the NES was on average about 40 minutes with a further 40 minutes required to complete all the questionnaires. Overall therefore, although there were some minor variations in the selection of measures used in Study I and Study 11, in essence the protocol, conduct and information acquired were considered to be highly comparable between the two studies. RESULTS
The following procedure was adopted in respect of the analysis in both studies: 1. descriptive data were analyzed to identify any major influences on test and questionnaire measures; 2. the two groups, i.e., exposed and controls, were initially compared in terms of performance on each psychological test and each standardized questionnaire score; 3. further analysis was performed to assess dose-effect, adjusting for the influence of relevant covariates.
Descriptive Data Educational level. In both studies, the educational level of the controls was significantly higher than that of the exposed subjects (McNemar test: Study I: p = .02, Study 11: p = .004). Pre-morbid ability. In both studies, comparison of the vocabulary scores of the two groups using paired “t” tests showed that the scores of the controls were significantly higher than those of the exposed subjects (Study I: t = 2.58, p = .01; Study 11: t = -2.92, p = .004). In Study 11, NART error scores, compared using a paired t test, were significantly higher in the exposed group than in the control group (t = 4.51; p = .OOOl). NART error scores were highly negatively correlated with vocabulary (correct response) scores (r = -0.75). It was thus clear from these measures, and that of
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TABLE I. NES Test Scores: Comparison of Exposed and Controls* P
Test
N
Exposed mean (SD)
Controls mean (SD)
C.I. mean difference
Study I SDS Study I1 SDS, resp. timekrial (sec) Study I PM, No. correct Study I1 PM, No. correct Study I SDL, total score Study I1 SDL, total score Study I CFT, resp. time (msec) Study I1 SRT, resp. time (msec)
90
27.9 (9.1)
25.3 (6.8)
0.48 to 4.72
2.42
.02
140”
23.7 (5.9)
22.6 (6.0)
0.46 to 2.68
2.80
,006
88”
12.3 (1.7)
12.4 (1.7)
-0.62 to 0.42
-0.52
.60
140”
12.3 (1.9)
12.5 (1.9)
-0.58 to 0.16
-0.98
.32
88”
9.2 (9.1)
8.1 (5.2)
-0.45 to 2.65
1.51
.I4
140”
6.2 (4.7)
5.6 (4.2)
-0.32 to 1.54
1.31
.I8
90
449.6 (46.4)
443.7 (41.3)
-6.21 to 18.19
0.98
.33
139”
312.7 (64.7)
302.9 (64.8)
-4.15 to 23.77
1.39
.I7
t
value
*In PM, a higher score denotes better performance. In all other tests a higher score denotes a worse performance. ”Some data lost due to computer malfunction.
educational level, that in both studies, the pre-morbid ability of the controls was higher than that of the exposed subjects and would need to be taken into account where any differences in test performance between the two groups were observed. Computer experience. Ratings of computer experience were compared between exposed and control groups using a McNemar test. In Study I, controls appeared to have significantly more computer experience (p = .003). There was no difference in reported computer experience between the exposed and control groups in Study I1 (p = .19). Alcohol consumption. Very few subjects in either study consumed wine or spirits on a regular basis. Alcohol consumption was confined largely to beer. In both studies, the exposed group consumed slightly more pints of beer per week than controls (Study I: exposed 9.8, controls 8.0; Study 11: exposed 7.1, controls 6.5). These differences were not statistically significant. The figures are also well below recommended amounts contained in government health guidance leaflets (i.e., no more than 11 pints, or 22 units of alcohol, per week) suggesting that, even allowing for under-reporting, these were not particularly heavy drinking groups. Immediate influences of test performance. The frequency of occurrence of these factors was extremely low and judged unlikely to significantly affect results. Comparison of Two Groups Initially paired “t” tests were performed on the NES data to compare the performance of the exposed and control groups in both studies (Tables I, 11). In both studies, there was a statistically significant difference between the mean scores of the exposed subjects and the controls in the SDS test, but no significant differences were evident in PM, SDL, CPT,and SRT. With the exception of PM, the scores of participants in Study I1 were generally superior to those in Study I, possibly
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TABLE 11. PAL and ART Scores: Comparisons of Exposed and Controls in Study 11* Test PAL Trial I, No. recalled PAL Trial 2, No. recalled PAL Trial 3, No. recalled ART No. recalled
N
Exposed N = 139 mean (SD)
Controls N = 139 mean (SD)
CI mean difference
t
P value
139”
3.99 (1.76)
4.28 (1.86)
-0.65 to 0.07
- 1.57
.I2
139”
4.59 (2.40)
5.39 (2.12)
-1.29 to -0.31
-3.25
,001
139”
5.47 (2.39)
6.12 (2.27)
-1.15 to -0.17
-2.68
,008
139”
5.40 (2.45)
6.19 (2.20)
-1.30 to -0.28
-3.06
,003
*Note: In PAL and ART, a higher score = better performance. “Some data lost due to computer malfunction.
reflecting the higher pre-morbid ability of the former, as evidenced by vocabulary scores and ratings of educational level. In Study 11, in the PAL test, the exposed subjects learned significantly fewer word pairs over the three trials. The difference between exposed and controls was statistically significant in trials 2 and 3. Both exposed and control groups maintained the level of learning attained in trial 3 when re-tested at the end of the test battery (ART). Mean scores on questionnaire measures were compared between exposed and controls in both studies using paired t-tests (Table 111). There were no significant differences between the mean scores on the GHQ and the CFQ in either study. GHQ scores were low relative to normative data, i.e., the “at risk” threshold for community samples using the GHQ 30 is 4 and using the GHQ-60 is 12. In neither Study I nor Study I1 were there significantly more exposed subjects than controls falling above the “at risk” threshold (McNemar test: p = . 8 5 , p = .19, respectively). Scores on the CFQ were very similar for the two groups across both studies and did not suggest any increase in reported memory problems in the exposed groups. In Study 11, the exposed population appeared to have significantly more symptoms than the controls (Orebro-16 questionnaire). However the mean symptom scores for the exposed group were almost identical for the two studies, the difference in Study I1 resulting from a lower mean score in the control group. Dose-Effect
Exposure assessment. In both studies, duration of exposure in years was used as a measure of “dose.” Industrial hygiene data were unavailable for most of the period covering the working lives of the participants, which in some cases extended over more than 30 years. In Study I, duration in years appeared to represent the most accurate estimate of exposure since this group had homogeneous working conditions, the majority of subjects having worked in the same occupation all their lives carrying out jobs which were very similar in content to one another. The correlation between age and duration of occupation was 0.86. The population in Study I1 was more heterogeneous and an argument may be advanced for attempting a more sophisticated assessment of exposure or “dose” based on information recorded on the occupational history questionnaire. However, for the present purposes, that of directly comparing the two studies, duration of exposure in years was once more used as a surrogate for
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TABLE 111. Questionnaire Measures: Comparison of Exposed and Controls in Studies I & I1 Measure
N
Exposed mean (SD)
Controls mean (SD)
CI mean difference
Study I GHQ-30 Study I1 GHQ-60
90 144
2.54 (4.5) 3.57 (5.78)
90
35.44 (14.50) 35.68 (14.33) 3.42 (3.1) 3.54 (2.62)
1.91 (3.1) 4.81 (8.14) 34.66 (11.01) 33.44 (15.78) 3.12 (2.9) 2.62 (2.72)
-0.51 to 1.76 -0.46 to 2.92 -3.25 to 4.83 -1.00 to 5.48 -0.59 to 1.19 0.30 to 1.54
Study I Study II Study I Study II
CFQ" CFQ" Orebro-16 Orebro-16
144 90 144
P
t
value
1.11 1.44
.27 .15 .70 .17 .49 403
0.39 1.37 0.70 3.00
"Max score 100.
"dose. " In both studies therefore, the population was structured into four exposure groups (group 1 < 10 years, group 2 = 10-20 years, group 3 = 21-30 years, group 4 > 30 years). Analysis of covariance was carried out to assess the effect of exposure on each test performance after adjustment for the following covariates: rating of previous computer experience, pre-morbid ability (vocabulary score), alcohol consumption (pints per week), and time last solvent exposure. These factors were selected a priori on the basis that there are empirical reasons to assume they could influence test performance. In both studies, the results indicated a significant effect of solvent exposure, after adjustment for covariates, on SDS response times only in Exposure Group 4, i.e., those with more than 30 years of occupational exposure. (Results relating to SDS for studies I and 11 are shown in Tables IV and V, respectively.) In Study I1 the results indicate a significant effect of exposure on PAL performance in all groups exceeding 10 years of exposure (Table VI). No significant effects of exposure were noted in response to other test outcomes after adjustment for covariates. DISCUSSION
The results of this investigation give some support to the view that long-term solvent exposure can result in some measure of impairment of cognitive function. In our two studies, a significant effect of exposure on performance was observed in the Symbol-Digit Substitution test. This is a computer adaptation of the Digit Symbol test [Wechsler, 19811 which has been used in other settings as a sensitive screening test for brain damage [Smith, 19821. There are also indications from studies employing both computer-administered and original versions of the test of its sensitivity to the effects of neurotoxicants [Lindstrom, 1980; Lindstrom and Wickstrom, 1983; Fidler et al., 1987; Baker et al., 19881. In our investigation, two studies were carried out employing the same measures and procedures. The fact that a very similar pattern of results was obtained in the two studies adds weight to the view that this is a genuine effect of solvent exposure. Analysis of dose-effect, using years of exposure as a measure for dose, showed that in both studies, after taking into account other possible influences on performance, a significant effect of exposure remained only in those with more than 30 years of exposure. There was also evidence of an effect of exposure on PAL performance in Study 11, in this case occurring in all groups with more than 10 years' exposure. Exposed
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TABLE IV. Analysis of Covariance: Estimates for Mean Differences in SDS Scores in Study I Coefficient Exposure group 1 Exposure group 2 Exposure group 3 Exposure group 4 Covariates Computing experience Pre-morbid ability Alcohol consumption Recent exposure
S.E.
t
0.53 3.16 0.97 4.45
3.90 2.33 2.10 2.13
0.14 1.35 0.46 2.09"
0.45 0.04 -0.36 I .26
1.88 0.10 0.22 1.74
0.24 0.41 - 1.65 0.72
CI -7.23 to 8.29 - I .49 to 7.81 -3.22 to 5.15 0.21 to 8.70 -3.29 -0.16 -0.79 -2.21
to 4. I9 to 0.24 to 0.07 to 4.73
ap < .05.
TABLE V. Analysis of Covariance: Estimates for Mean Differences in the SDS Scores in Study I1 ~
Coefficient Exposure group 1 Exposure group 2 Exposure group 3 Exposure group 4 Covariates Computing experience Pre-morbid ability Alcohol consumption Recent exposure
S.E.
t
1.10 1.14 1.38 3.70
1.27 1.03 1.36 1.35
0.86
-1.99 -0.02 0.01 -1.54
0.84 0.05 0.01 0.95
-2.36 -0.43 0.38 - 1.63
CI
1.10
- 1.42 to 3.62 -0.09 to 3.17
1.02 2.75"
-1.31 t04.06 1.04 to 6.36 -3.65 -0.1 I -0.02 -3.42
to -0.32 to 0.71 to 0.03 to 0.33
"p < .01.
TABLE VI. Estimates for Mean Differences in PAL Scores in Study I1 Exposure group 1 Exposure group 2 Exposure group 3 Exposure group 4 Covariates Computing experience Pre-morbid ability Alcohol consumption Recent exposure
Coefficient
S.E.
t
-1.11 -2.88 -2.12 -1.87
0.83 0.68 0.89 0.88
- 1.34 -4.21" -2.39b -2. 13b
0.55 0.03 0.01 0.62
2.28b 2.19b 0.58 0.33
1.23 0.07 0.01 0.20
CI -2.76 -4.23 -3.88 -3.60
to 0.53 to -1.53 to -0.37 to -0.13
0.16 to 2.33 0.01 to 0.13 -0.01 to 0.02 - 1.02 to 1.42
"p < .001. bp < .05.
subjects learned fewer word pairs overall than controls, although the rate of acquisition after trial I, i.e., a mean of one item per trial, was similar in the two groups. In addition, both groups maintained the learning level acquired at the end of PAL when retested (ART) at the end of the test battery. This suggests that there may be a specific effect on learning processes which requires further investigation, using techniques designed to define more precisely which aspects of learning and memory processes are involved. It is noteworthy that in neither study was there any apparent
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effect on another learning test, SDL, either in terms of the level or the pattern of learning. There are numerous differences between SDL and PAL, for example the use of digits as opposed to words, serial as opposed to paired-associate techniques, and, in this particular test battery, strategy instructions in the case of SDL which were absent in PAL. This last difference (presence or absence of strategy instructions) may also account for the discrepancy between the findings of this study in relation to Serial Digit Learning and those of Bleecker et al. [ 19911 who used the WAIS-R version of the test [Wechsler, 19811 and noted a relationship with solvent exposure. The results of this investigation, therefore, while supporting the view that long-term solvent exposure may damage the central nervous system, appear also to underline the subtlety of these effects and point to the need to investigate their particular nature more closely. While there is clearly a place in these types of studies for tests which are highly sensitive to brain damage, regardless of its location or etiology, there is also a need to develop techniques capable of isolating the particular aspects of cognitive functioning which may be affected. This may involve addressing not only effects on the specific processes involved in, for example, short- and long-term memory storage, but also on other aspects of performance such as the subjects’ ability to employ available strategies and to compensate for any developing difficulties. Such factors may have direct implications for an individual’s everyday functioning. In these two studies, it is important to note that there was no indication that solvent exposed workers were aware of experiencing more memory difficulties than controls nor that they suffered from more psychiatric symptoms. Scores on the GHQ were low in both studies for both groups as compared with data from community samples [Goldberg et al., 19701. Slightly more of the exposed groups had scores above the “at risk” threshold as defined by Goldberg [1978], but the difference between the two groups was not statistically significant. Scores on the symptom questionnaire were also low in both groups for both studies as compared with those reported by Hogstedt for solvent-exposed workers in Sweden [Hogstedt et al., 19841. Although there was a statistically significant difference between the mean symptom of scores of exposed subjects and controls in Study 11, this appeared to be the result of a particularly low score in the control group. Overall, therefore, our data did not provide evidence of a high level of symptom reporting in these solvent-exposed groups. A frequently encountered criticism of cross-sectional studies is the possible existence of a “survivor effect,” i.e., those most severely affected may have left the workforce. It is clearly not possible to address this question fully without long-term follow up of the study participants. However, while this may be a valid criticism where “all or none” effects are under investigation (for example the development of tumors), it is perhaps less tenable in neurotoxicity studies where one might expect a gradation of effect occurring over a long period of time. Given such a situation, one would presumably expect to find a proportion of any exposed workforce suffering from effects of somewhat greater magnitude than those observed here, particularly in relation to psychiatric and other symptomatology. A further question relates to the varying levels of exposure occurring over time. Although the present exposure to solvents of the groups involved was not considered to be above current UK occupational exposure limits, previous exposure may have been higher in some occupational groups. It is possible to argue, therefore, that the effect observed may have related to higher earlier exposures rather than to current
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levels. However, the finding of an effect on PAL after only 10 years of exposure suggests that this is not the case. In conclusion, therefore, the results of our investigation provide some evidence of an effect on cognitive functioning after many years of solvent exposure. This evidence is particularly persuasive in the light of the similar pattern of results obtained in the two comparable studies. The observed effect appears much less severe than that reported in some other studies of solvent-exposed groups, and was not apparently accompanied by any awareness on the part of the subjects of psychiatric difficulties or other symptoms. Because of the apparently subtle nature of those effects, therefore, future work in this area would benefit from the further development of more sophisticated techniques designed to define more precisely the nature of neurotoxic effects in occupational settings. ACKNOWLEDGMENTS
The researchers gratefully acknowledge the support of the U.K. Health and Safety Executive in funding this investigation. Particular thanks are also due to Dr. Ching Aw for his advice during the setting up of the project and to Elaine Baker for her preparation of the manuscript. We are also grateful to the representatives of the various organizations involved, who helped us greatly with administration. Finally, special thanks are due to all those workers who so willingly and cheerfully participated. REFERENCES Baker EL, Letz RE, Eisen EA, Pothier LJ, Plantamura DL, Larson M, Wolford R (1988): Neurobehavioral effects of solvents in construction painters. J Occup Med 30:116-123. Baker EL, Letz R, Fidler A (1985): A computer administered neurobehavioral evaluation system for occupational and environmental epidemiology. J Occup Med 27:206-212. Bleecker ML, Bolla KI, Agnew J, Schwartz BS, Ford DP (1991): Dose-related subclinical neurobehavioral effects of chronic exposure to low levels of organic solvents. Am J Ind Med 19:715-728. Broadbent DE, Cooper PF, Fitzgerald P, Parkes KR (1982): The cognitive failures questionnaire (CFQ) and its correlates. Br J Clin Psycho1 21:l-16. Cherry N. Hutchins H, Pace T, Waldron HA (1985): Neurobehavioral effects of repeated occupational exposure to toluene and paint solvents. Br J Ind Med 42:291-300. Elofsson SA, Gamberale F, Hindmarsh I, Iregren A, Isaksson A, Johnsson I, Knave B, Lydahil E, Mindus P, Persson HE, Philipson B, Steby M, Struwe G , Soderman E, Wernberg A, Widen L (1980): Exposure to organic solvents. A cross-sectional epidemiological investigation on occupationally-exposed car and industrial spray painters with special reference to the nervous system. Scand J Work Environ Health 6:239-273. Errebo-Knudsen EO, Olsen F (1986): Organic solvents and the presenile dementia (The painters syndrome). A critical review of the Danish literature. Science Total Environment 48:45-67. Fidler AT, Baker EL, Letz RE (1987): Neurobehavioral effects of occupational exposure to organic solvents among construction painters. Br J Ind Med 44:292-308. Gade A, Mortensen EL, Bruhn P (1988): Chronic painters syndrome. A reanalysis of psychological test data in a group of diagnosed cases based on comparisons with matched controls. Acta Neurol Scand 77:293-306. Goldberg D (1978): “Manual of the General Health Questionnaire.” Windsor: NFER-Nelson. Goldberg DP, Cooper B, Eastwood MR, Kedward HB, Shepherd M (1970): A standardised psychiatric interview for use in community surveys. Br J Prev SOCMed 24:18-23. Hane M, Axelson 0, Blume J, Hogstedt C, Sundell L, Ydreborg B (1977): Psychological function changes among house painters. Scand J Work Environ Health 3:91-99.
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Hanninen H, Eskelinen MA, Husman KAJ, Nurminen M (1976): Behavioral effects of long-term exposure to a mixture of organic solvents. Scand J Work Environ Health 4:240-255. Hogstedt C, Anderson K, Hane M (1984): A questionnaire approach to the monitoring of early disturbances in central nervous functions. In Aitio A, Riihimaki V, Vaninio H (eds): “Biological Monitoring and Surveillance of Workers Exposed to Chemicals. ” Washington: Hemisphere Pub1 COT, pp 275-287. Iregren A (1982): Effects on psychological test performance of workers exposed to a single solvent (toluene): a comparison with effects of exposure to a mixture of organic solvents. Neurobehav Toxic01 Teratol 4:695 -70 1. Lindstrom K (1980): Changes in psychological performances of solvent-poisoned and solvent-exposed workers. Am J Ind Med 1:69-84. Lindstrom K, Wickstrom G (1983): Psychological function changes among maintenance house painters exposed to low levels of organic solvent mixtures. Acta Psychiatr Scand 67(Suppl 303):81-91. Mikkelsen S, Jorgensen M, Browne E, Gyldensted C (1988): Mixed solvent exposure and organic brain damage. A study of painters. Acta Neurol Scand Vol. 78 (Suppl 118):143. Nelson HE (1982): “ ‘National Adult Reading Test’; “Test Manual.” Windsor: NFER-Nelson. Smith A (1982): “Manual of the Symbol Digit Modalities Test.” Los Angeles: Western Psychological Services. Wechsler D (1981): “WAIS-R Manual.” New York: Psychological Corporation. WHO (1989): Environmental Health Series No. 36. Chronic effects of organic solvents on the central nervous system-core protocol for an international collaborative study.
Neurobehavioral Effects of Long-Term Occupational Exposure to Organic Solvents: Two Comparable Studies A. Spurgeon, PhD, C.N. Gray, PhD, J. Sims, PhD, 1. Calvert, MA, L.S. Levy, PhD, P.G. Harvey, PhD, and J.M. Harrington, MD
Two comparable cross-sectional studies were carried out employing the same methodology but involving two separate solvent-exposed populations (N = 90, N = 144). In each study, solvent-exposed workers were compared with age-matched controls on tests selected from the Neurobehavioral Evaluation System and on standardized questionnaire measures of symptomatology and psychiatric state. A similar pattern of results was obtained in the two studies indicating a significant effect on cognitive functioning, after controlling for confounding variables, occurring in those with more than 30 years of exposure. A more specific effect on learning processes was observed in those with more than 10 years of exposure. There were no indications in either study of a solvent-related increase in psychiatric symptoms. o 1992 WiIey-Liss, Inc. Key words: long-term solvent exposure, psychiatric symptoms, painters, neurobehavioral testing
INTRODUCTION
During the last 25 years, the results of a number of epidemiologic studies have suggested that long-term occupational exposure to organic solvents may result in damage to the central nervous system [Hanninen et al., 1976; Hane et al., 1977; Eloffson et al., 1980; Cherry et al., 1985; Mikkelsen et al., 1988; Baker et al., 1988; Bleecker et al., 19911. Behavioral manifestations of such damage include an increase in psychiatric symptoms, reported memory and concentration difficulties, and impairment of cognitive functioning as demonstrated by performance on neurobehavioral tests. In many cases these effects are subtle, occumng in the absence of overt clinical signs and only measurable by use of psychological test procedures. Since such effects cannot be mimicked in animal models and because of the dearth of information concerning dose-effect relationships, there is continuing controversy Institute of Occupational Health, University of Birmingham, Edgbaston, Birmingham, England ( A S . , I.C., L.S.L., J.M.H.). Deakin University, Geelong, Australia (C. N .G.). Free University of Amsterdam, Amsterdam, The Netherlands (J.S.). Central Birmingham Health Authority, Birmingham, England (P.G.H.). Address reprint requests to Dr. A. Spurgeon, Institute of Occupational Health, University of Birmingham, Edgbaston, Birmingham B15 2TT, England. Accepted for publication February 3, 1992.
0 1992 Wiley-Liss, Inc.
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about the nature and severity of the problem. This debate has recently been renewed in Denmark where concern over occupational solvent exposure originated and where some scientists have recently challenged the conclusions of the earlier data [ErreboKnudsen and Olsen, 1986; Gade et al., 19881. There are numerous methodological difficulties in this area associated, for example, with the elimination of selection bias in the exposed populations, appropriate matching of controls, avoidance of acute effects in the assessment of long-term damage, and the influence of other factors on test performance. In particular, some of the possible inconsistency in results may be accounted for by the wide range of neurobehavioral assessment methods employed and by the lack of a standardized approach to psychological testing. In recent years, there has been a move toward harmonization of methods with the development of test batteries designed specifically for the purpose of assessing and monitoring the effects of neurotoxicants in occupational settings. In addition, the use of computer administered tests has enhanced the standardization of testing procedure and scoring, as well as providing for increased comparability of results. The present investigation employed one such test battery, the Neurobehavioral Evaluation System, (NES) [Baker et al., 19851 in two comparable cross-sectional studies where the same methodology was employed on two separate solvent-exposed populations. In addition, the psychiatric status and the frequency of symptom reporting in the exposed population were compared with those of the controls using standardized questionnaires, which are well supported by a quantity of normative data. The objectives of the present investigation therefore were 1) to establish whether the performance of the solvent exposed populations was significantly poorer than that of the controls in neurobehavioral tests reputed to be sensitive to the effects of nervous system damage; 2) to establish whether the psychiatric status and health of the solvent exposed workers were inferior to those of the controls; 3) to establish whether a dose-effect relationship existed where there was any observed impairment of cognitive performance or psychiatric status; and 4) to compare the patterns of neurobehavioral performance and symptomatology observed in the two studies. MATERIALS AND METHODS Populations In Study I, the exposed population consisted of 90 brush painters employed by hospital maintenance departments in a large UK health authority. The study population represented 67% of all those painters employed by the authority. Twenty-nine percent were unwilling to take part in the study and 4% were excluded due to pre-set exclusion criteria, namely previous head injury, alcohol or drug dependency, or existing disease affecting the nervous system. Exposed subjects were individually age-matched with randomly selected maintenance workers employed on the same sites whose occupations did not involve significant solvent exposure. In Study 11, the exposed population consisted of 144 solvent-exposed workers drawn from three organizations, namely the Ministry of Defense, a further regional health authority, and the maintenance section of a large city housing department. They represented a range of occupations, i.e., brush painters, paintsprayers, printers, coach trimmers, boat builders, and degreasers. The study population represented 83% of available subjects. Five percent refused to take part, 2% were excluded, and
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suitable controls were unavailable for the remaining 10%. Individually age-matched controls were again randomly selected from non-exposed maintenance workers employed on the same sites. In both studies, all participants were male and U.K.-born, i.e., English was their first language. The age range was 21-65 years. Measures In both studies, exposed subjects and controls completed a series of computer-administered psychological tests drawn from the NES. In Study I, these were Symbol-Digit-Substitution (SDS), Pattern Memory (PM), Serial Digit Learning (SDL), Switching Attention (SA), and Continuous Performance Test (CPT). These tests were selected to assess a range of cognitive functions and also included one test (SDS) known to be extremely sensitive to CNS damage regardless of its etiology or location. These tests were repeated in Study I1 with the following exceptions. SA proved too difficult for most subjects and was thus replaced with two additional learning tests: Paired Associate Learning (PAL) and the longer-term recall test, Associate Recall Test (ART), involving re-administration of items at the end of the test battery. The CPT was replaced with a Simple Reaction Time test (SRT) because of indications from other studies [Iregren, 1982; Cherry et al., 19851 that reaction time tests are particularly sensitive to the effects of solvent exposure. In both studies, the vocabulary test from the NES was included as a measure of pre-morbid ability. The National Adult Reading Test (NART) [Nelson, 19821 was included as an additional measure in Study I1 in accordance with recommendations of the WHO working group [WHO, 19891 which suggested that two measures of premorbid ability should be employed. There is considerable evidence to suggest that the NART is both resistant to CNS damage and correlates highly with I.Q. as conventionally measured, [Nelson, 19821. Standardized questionnaire outcome measures were as follows. 1. The General Health Questionnaire (GHQ) was employed to assess psychiatric morbidity [Goldberg, 19781. This is a well-established questionnaire designed to screen for psychiatric morbidity in community and occupational samples and includes assessment of both minor and severe psychiatric symptoms. Threshold values for those considered “at risk” of developing psychiatric illness are provided which allow for a comparison of the number of individuals in each group falling above and below the threshold. In Study I, the 30 item version was used. Because of increased time availability, however, the 60 item version, allowing increased sensitivity, was used in Study 11. 2. The Cognitive Failures Questionnaire (CFQ) was included to assess self-reported memory difficulties. This questionnaire is also supported by data on reliability and validity and has been used in other studies to assess behavioral memory in relation to environmental and individual factors [Broadbent et al., 19821. 3. The Orebro 16-item questionnaire [Hogstedt et al., 19841 was used to assess frequency of symptom reporting. This questionnaire was developed specifically as a screening tool for solvent-exposed workers, and some normative data on such populations are available [Hogstedt et al., 19841.
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In addition to psychological tests and standardized questionnaires, all participants completed an occupational history questionnaire together with questionnaires concerned with educational level, computer experience, alcohol consumption, and with more immediate influences on test performance, namely recent virus infections, medication use, and sleep loss. Procedure Participants were tested in groups of four in a mobile laboratory driven to their workplace. Questionnaires were completed in an adjacent room. Testing for both exposed subjects and controls took place in the morning immediately before work commenced, i.e., prior to solvent exposure, and controlling for time-of-day effects on the tests. In Study I, 63% of exposed subjects and in Study 11, 75% of exposed subjects were tested on a Monday morning, i.e., at least 48 hours had elapsed since their last solvent exposure. The remainder were tested on a Tuesday morning with at least 12 hours having elapsed since last exposure. In Study I, exhaled breath samples were taken from all participants prior to testing and analyzed for solvent content using a mass spectrometer. Since these were negative for all subjects including those tested on Tuesdays (detection limits for toluene, xylene, and white spirit < 1 ppm), this procedure was not repeated in Study 11. In both studies, the time spent by participants on the NES was on average about 40 minutes with a further 40 minutes required to complete all the questionnaires. Overall therefore, although there were some minor variations in the selection of measures used in Study I and Study 11, in essence the protocol, conduct and information acquired were considered to be highly comparable between the two studies. RESULTS
The following procedure was adopted in respect of the analysis in both studies: 1. descriptive data were analyzed to identify any major influences on test and questionnaire measures; 2. the two groups, i.e., exposed and controls, were initially compared in terms of performance on each psychological test and each standardized questionnaire score; 3. further analysis was performed to assess dose-effect, adjusting for the influence of relevant covariates.
Descriptive Data Educational level. In both studies, the educational level of the controls was significantly higher than that of the exposed subjects (McNemar test: Study I: p = .02, Study 11: p = .004). Pre-morbid ability. In both studies, comparison of the vocabulary scores of the two groups using paired “t” tests showed that the scores of the controls were significantly higher than those of the exposed subjects (Study I: t = 2.58, p = .01; Study 11: t = -2.92, p = .004). In Study 11, NART error scores, compared using a paired t test, were significantly higher in the exposed group than in the control group (t = 4.51; p = .OOOl). NART error scores were highly negatively correlated with vocabulary (correct response) scores (r = -0.75). It was thus clear from these measures, and that of
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TABLE I. NES Test Scores: Comparison of Exposed and Controls* P
Test
N
Exposed mean (SD)
Controls mean (SD)
C.I. mean difference
Study I SDS Study I1 SDS, resp. timekrial (sec) Study I PM, No. correct Study I1 PM, No. correct Study I SDL, total score Study I1 SDL, total score Study I CFT, resp. time (msec) Study I1 SRT, resp. time (msec)
90
27.9 (9.1)
25.3 (6.8)
0.48 to 4.72
2.42
.02
140”
23.7 (5.9)
22.6 (6.0)
0.46 to 2.68
2.80
,006
88”
12.3 (1.7)
12.4 (1.7)
-0.62 to 0.42
-0.52
.60
140”
12.3 (1.9)
12.5 (1.9)
-0.58 to 0.16
-0.98
.32
88”
9.2 (9.1)
8.1 (5.2)
-0.45 to 2.65
1.51
.I4
140”
6.2 (4.7)
5.6 (4.2)
-0.32 to 1.54
1.31
.I8
90
449.6 (46.4)
443.7 (41.3)
-6.21 to 18.19
0.98
.33
139”
312.7 (64.7)
302.9 (64.8)
-4.15 to 23.77
1.39
.I7
t
value
*In PM, a higher score denotes better performance. In all other tests a higher score denotes a worse performance. ”Some data lost due to computer malfunction.
educational level, that in both studies, the pre-morbid ability of the controls was higher than that of the exposed subjects and would need to be taken into account where any differences in test performance between the two groups were observed. Computer experience. Ratings of computer experience were compared between exposed and control groups using a McNemar test. In Study I, controls appeared to have significantly more computer experience (p = .003). There was no difference in reported computer experience between the exposed and control groups in Study I1 (p = .19). Alcohol consumption. Very few subjects in either study consumed wine or spirits on a regular basis. Alcohol consumption was confined largely to beer. In both studies, the exposed group consumed slightly more pints of beer per week than controls (Study I: exposed 9.8, controls 8.0; Study 11: exposed 7.1, controls 6.5). These differences were not statistically significant. The figures are also well below recommended amounts contained in government health guidance leaflets (i.e., no more than 11 pints, or 22 units of alcohol, per week) suggesting that, even allowing for under-reporting, these were not particularly heavy drinking groups. Immediate influences of test performance. The frequency of occurrence of these factors was extremely low and judged unlikely to significantly affect results. Comparison of Two Groups Initially paired “t” tests were performed on the NES data to compare the performance of the exposed and control groups in both studies (Tables I, 11). In both studies, there was a statistically significant difference between the mean scores of the exposed subjects and the controls in the SDS test, but no significant differences were evident in PM, SDL, CPT,and SRT. With the exception of PM, the scores of participants in Study I1 were generally superior to those in Study I, possibly
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TABLE 11. PAL and ART Scores: Comparisons of Exposed and Controls in Study 11* Test PAL Trial I, No. recalled PAL Trial 2, No. recalled PAL Trial 3, No. recalled ART No. recalled
N
Exposed N = 139 mean (SD)
Controls N = 139 mean (SD)
CI mean difference
t
P value
139”
3.99 (1.76)
4.28 (1.86)
-0.65 to 0.07
- 1.57
.I2
139”
4.59 (2.40)
5.39 (2.12)
-1.29 to -0.31
-3.25
,001
139”
5.47 (2.39)
6.12 (2.27)
-1.15 to -0.17
-2.68
,008
139”
5.40 (2.45)
6.19 (2.20)
-1.30 to -0.28
-3.06
,003
*Note: In PAL and ART, a higher score = better performance. “Some data lost due to computer malfunction.
reflecting the higher pre-morbid ability of the former, as evidenced by vocabulary scores and ratings of educational level. In Study 11, in the PAL test, the exposed subjects learned significantly fewer word pairs over the three trials. The difference between exposed and controls was statistically significant in trials 2 and 3. Both exposed and control groups maintained the level of learning attained in trial 3 when re-tested at the end of the test battery (ART). Mean scores on questionnaire measures were compared between exposed and controls in both studies using paired t-tests (Table 111). There were no significant differences between the mean scores on the GHQ and the CFQ in either study. GHQ scores were low relative to normative data, i.e., the “at risk” threshold for community samples using the GHQ 30 is 4 and using the GHQ-60 is 12. In neither Study I nor Study I1 were there significantly more exposed subjects than controls falling above the “at risk” threshold (McNemar test: p = . 8 5 , p = .19, respectively). Scores on the CFQ were very similar for the two groups across both studies and did not suggest any increase in reported memory problems in the exposed groups. In Study 11, the exposed population appeared to have significantly more symptoms than the controls (Orebro-16 questionnaire). However the mean symptom scores for the exposed group were almost identical for the two studies, the difference in Study I1 resulting from a lower mean score in the control group. Dose-Effect
Exposure assessment. In both studies, duration of exposure in years was used as a measure of “dose.” Industrial hygiene data were unavailable for most of the period covering the working lives of the participants, which in some cases extended over more than 30 years. In Study I, duration in years appeared to represent the most accurate estimate of exposure since this group had homogeneous working conditions, the majority of subjects having worked in the same occupation all their lives carrying out jobs which were very similar in content to one another. The correlation between age and duration of occupation was 0.86. The population in Study I1 was more heterogeneous and an argument may be advanced for attempting a more sophisticated assessment of exposure or “dose” based on information recorded on the occupational history questionnaire. However, for the present purposes, that of directly comparing the two studies, duration of exposure in years was once more used as a surrogate for
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TABLE 111. Questionnaire Measures: Comparison of Exposed and Controls in Studies I & I1 Measure
N
Exposed mean (SD)
Controls mean (SD)
CI mean difference
Study I GHQ-30 Study I1 GHQ-60
90 144
2.54 (4.5) 3.57 (5.78)
90
35.44 (14.50) 35.68 (14.33) 3.42 (3.1) 3.54 (2.62)
1.91 (3.1) 4.81 (8.14) 34.66 (11.01) 33.44 (15.78) 3.12 (2.9) 2.62 (2.72)
-0.51 to 1.76 -0.46 to 2.92 -3.25 to 4.83 -1.00 to 5.48 -0.59 to 1.19 0.30 to 1.54
Study I Study II Study I Study II
CFQ" CFQ" Orebro-16 Orebro-16
144 90 144
P
t
value
1.11 1.44
.27 .15 .70 .17 .49 403
0.39 1.37 0.70 3.00
"Max score 100.
"dose. " In both studies therefore, the population was structured into four exposure groups (group 1 < 10 years, group 2 = 10-20 years, group 3 = 21-30 years, group 4 > 30 years). Analysis of covariance was carried out to assess the effect of exposure on each test performance after adjustment for the following covariates: rating of previous computer experience, pre-morbid ability (vocabulary score), alcohol consumption (pints per week), and time last solvent exposure. These factors were selected a priori on the basis that there are empirical reasons to assume they could influence test performance. In both studies, the results indicated a significant effect of solvent exposure, after adjustment for covariates, on SDS response times only in Exposure Group 4, i.e., those with more than 30 years of occupational exposure. (Results relating to SDS for studies I and 11 are shown in Tables IV and V, respectively.) In Study I1 the results indicate a significant effect of exposure on PAL performance in all groups exceeding 10 years of exposure (Table VI). No significant effects of exposure were noted in response to other test outcomes after adjustment for covariates. DISCUSSION
The results of this investigation give some support to the view that long-term solvent exposure can result in some measure of impairment of cognitive function. In our two studies, a significant effect of exposure on performance was observed in the Symbol-Digit Substitution test. This is a computer adaptation of the Digit Symbol test [Wechsler, 19811 which has been used in other settings as a sensitive screening test for brain damage [Smith, 19821. There are also indications from studies employing both computer-administered and original versions of the test of its sensitivity to the effects of neurotoxicants [Lindstrom, 1980; Lindstrom and Wickstrom, 1983; Fidler et al., 1987; Baker et al., 19881. In our investigation, two studies were carried out employing the same measures and procedures. The fact that a very similar pattern of results was obtained in the two studies adds weight to the view that this is a genuine effect of solvent exposure. Analysis of dose-effect, using years of exposure as a measure for dose, showed that in both studies, after taking into account other possible influences on performance, a significant effect of exposure remained only in those with more than 30 years of exposure. There was also evidence of an effect of exposure on PAL performance in Study 11, in this case occurring in all groups with more than 10 years' exposure. Exposed
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TABLE IV. Analysis of Covariance: Estimates for Mean Differences in SDS Scores in Study I Coefficient Exposure group 1 Exposure group 2 Exposure group 3 Exposure group 4 Covariates Computing experience Pre-morbid ability Alcohol consumption Recent exposure
S.E.
t
0.53 3.16 0.97 4.45
3.90 2.33 2.10 2.13
0.14 1.35 0.46 2.09"
0.45 0.04 -0.36 I .26
1.88 0.10 0.22 1.74
0.24 0.41 - 1.65 0.72
CI -7.23 to 8.29 - I .49 to 7.81 -3.22 to 5.15 0.21 to 8.70 -3.29 -0.16 -0.79 -2.21
to 4. I9 to 0.24 to 0.07 to 4.73
ap < .05.
TABLE V. Analysis of Covariance: Estimates for Mean Differences in the SDS Scores in Study I1 ~
Coefficient Exposure group 1 Exposure group 2 Exposure group 3 Exposure group 4 Covariates Computing experience Pre-morbid ability Alcohol consumption Recent exposure
S.E.
t
1.10 1.14 1.38 3.70
1.27 1.03 1.36 1.35
0.86
-1.99 -0.02 0.01 -1.54
0.84 0.05 0.01 0.95
-2.36 -0.43 0.38 - 1.63
CI
1.10
- 1.42 to 3.62 -0.09 to 3.17
1.02 2.75"
-1.31 t04.06 1.04 to 6.36 -3.65 -0.1 I -0.02 -3.42
to -0.32 to 0.71 to 0.03 to 0.33
"p < .01.
TABLE VI. Estimates for Mean Differences in PAL Scores in Study I1 Exposure group 1 Exposure group 2 Exposure group 3 Exposure group 4 Covariates Computing experience Pre-morbid ability Alcohol consumption Recent exposure
Coefficient
S.E.
t
-1.11 -2.88 -2.12 -1.87
0.83 0.68 0.89 0.88
- 1.34 -4.21" -2.39b -2. 13b
0.55 0.03 0.01 0.62
2.28b 2.19b 0.58 0.33
1.23 0.07 0.01 0.20
CI -2.76 -4.23 -3.88 -3.60
to 0.53 to -1.53 to -0.37 to -0.13
0.16 to 2.33 0.01 to 0.13 -0.01 to 0.02 - 1.02 to 1.42
"p < .001. bp < .05.
subjects learned fewer word pairs overall than controls, although the rate of acquisition after trial I, i.e., a mean of one item per trial, was similar in the two groups. In addition, both groups maintained the learning level acquired at the end of PAL when retested (ART) at the end of the test battery. This suggests that there may be a specific effect on learning processes which requires further investigation, using techniques designed to define more precisely which aspects of learning and memory processes are involved. It is noteworthy that in neither study was there any apparent
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effect on another learning test, SDL, either in terms of the level or the pattern of learning. There are numerous differences between SDL and PAL, for example the use of digits as opposed to words, serial as opposed to paired-associate techniques, and, in this particular test battery, strategy instructions in the case of SDL which were absent in PAL. This last difference (presence or absence of strategy instructions) may also account for the discrepancy between the findings of this study in relation to Serial Digit Learning and those of Bleecker et al. [ 19911 who used the WAIS-R version of the test [Wechsler, 19811 and noted a relationship with solvent exposure. The results of this investigation, therefore, while supporting the view that long-term solvent exposure may damage the central nervous system, appear also to underline the subtlety of these effects and point to the need to investigate their particular nature more closely. While there is clearly a place in these types of studies for tests which are highly sensitive to brain damage, regardless of its location or etiology, there is also a need to develop techniques capable of isolating the particular aspects of cognitive functioning which may be affected. This may involve addressing not only effects on the specific processes involved in, for example, short- and long-term memory storage, but also on other aspects of performance such as the subjects’ ability to employ available strategies and to compensate for any developing difficulties. Such factors may have direct implications for an individual’s everyday functioning. In these two studies, it is important to note that there was no indication that solvent exposed workers were aware of experiencing more memory difficulties than controls nor that they suffered from more psychiatric symptoms. Scores on the GHQ were low in both studies for both groups as compared with data from community samples [Goldberg et al., 19701. Slightly more of the exposed groups had scores above the “at risk” threshold as defined by Goldberg [1978], but the difference between the two groups was not statistically significant. Scores on the symptom questionnaire were also low in both groups for both studies as compared with those reported by Hogstedt for solvent-exposed workers in Sweden [Hogstedt et al., 19841. Although there was a statistically significant difference between the mean symptom of scores of exposed subjects and controls in Study 11, this appeared to be the result of a particularly low score in the control group. Overall, therefore, our data did not provide evidence of a high level of symptom reporting in these solvent-exposed groups. A frequently encountered criticism of cross-sectional studies is the possible existence of a “survivor effect,” i.e., those most severely affected may have left the workforce. It is clearly not possible to address this question fully without long-term follow up of the study participants. However, while this may be a valid criticism where “all or none” effects are under investigation (for example the development of tumors), it is perhaps less tenable in neurotoxicity studies where one might expect a gradation of effect occurring over a long period of time. Given such a situation, one would presumably expect to find a proportion of any exposed workforce suffering from effects of somewhat greater magnitude than those observed here, particularly in relation to psychiatric and other symptomatology. A further question relates to the varying levels of exposure occurring over time. Although the present exposure to solvents of the groups involved was not considered to be above current UK occupational exposure limits, previous exposure may have been higher in some occupational groups. It is possible to argue, therefore, that the effect observed may have related to higher earlier exposures rather than to current
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levels. However, the finding of an effect on PAL after only 10 years of exposure suggests that this is not the case. In conclusion, therefore, the results of our investigation provide some evidence of an effect on cognitive functioning after many years of solvent exposure. This evidence is particularly persuasive in the light of the similar pattern of results obtained in the two comparable studies. The observed effect appears much less severe than that reported in some other studies of solvent-exposed groups, and was not apparently accompanied by any awareness on the part of the subjects of psychiatric difficulties or other symptoms. Because of the apparently subtle nature of those effects, therefore, future work in this area would benefit from the further development of more sophisticated techniques designed to define more precisely the nature of neurotoxic effects in occupational settings. ACKNOWLEDGMENTS
The researchers gratefully acknowledge the support of the U.K. Health and Safety Executive in funding this investigation. Particular thanks are also due to Dr. Ching Aw for his advice during the setting up of the project and to Elaine Baker for her preparation of the manuscript. We are also grateful to the representatives of the various organizations involved, who helped us greatly with administration. Finally, special thanks are due to all those workers who so willingly and cheerfully participated. REFERENCES Baker EL, Letz RE, Eisen EA, Pothier LJ, Plantamura DL, Larson M, Wolford R (1988): Neurobehavioral effects of solvents in construction painters. J Occup Med 30:116-123. Baker EL, Letz R, Fidler A (1985): A computer administered neurobehavioral evaluation system for occupational and environmental epidemiology. J Occup Med 27:206-212. Bleecker ML, Bolla KI, Agnew J, Schwartz BS, Ford DP (1991): Dose-related subclinical neurobehavioral effects of chronic exposure to low levels of organic solvents. Am J Ind Med 19:715-728. Broadbent DE, Cooper PF, Fitzgerald P, Parkes KR (1982): The cognitive failures questionnaire (CFQ) and its correlates. Br J Clin Psycho1 21:l-16. Cherry N. Hutchins H, Pace T, Waldron HA (1985): Neurobehavioral effects of repeated occupational exposure to toluene and paint solvents. Br J Ind Med 42:291-300. Elofsson SA, Gamberale F, Hindmarsh I, Iregren A, Isaksson A, Johnsson I, Knave B, Lydahil E, Mindus P, Persson HE, Philipson B, Steby M, Struwe G , Soderman E, Wernberg A, Widen L (1980): Exposure to organic solvents. A cross-sectional epidemiological investigation on occupationally-exposed car and industrial spray painters with special reference to the nervous system. Scand J Work Environ Health 6:239-273. Errebo-Knudsen EO, Olsen F (1986): Organic solvents and the presenile dementia (The painters syndrome). A critical review of the Danish literature. Science Total Environment 48:45-67. Fidler AT, Baker EL, Letz RE (1987): Neurobehavioral effects of occupational exposure to organic solvents among construction painters. Br J Ind Med 44:292-308. Gade A, Mortensen EL, Bruhn P (1988): Chronic painters syndrome. A reanalysis of psychological test data in a group of diagnosed cases based on comparisons with matched controls. Acta Neurol Scand 77:293-306. Goldberg D (1978): “Manual of the General Health Questionnaire.” Windsor: NFER-Nelson. Goldberg DP, Cooper B, Eastwood MR, Kedward HB, Shepherd M (1970): A standardised psychiatric interview for use in community surveys. Br J Prev SOCMed 24:18-23. Hane M, Axelson 0, Blume J, Hogstedt C, Sundell L, Ydreborg B (1977): Psychological function changes among house painters. Scand J Work Environ Health 3:91-99.
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Hanninen H, Eskelinen MA, Husman KAJ, Nurminen M (1976): Behavioral effects of long-term exposure to a mixture of organic solvents. Scand J Work Environ Health 4:240-255. Hogstedt C, Anderson K, Hane M (1984): A questionnaire approach to the monitoring of early disturbances in central nervous functions. In Aitio A, Riihimaki V, Vaninio H (eds): “Biological Monitoring and Surveillance of Workers Exposed to Chemicals. ” Washington: Hemisphere Pub1 COT, pp 275-287. Iregren A (1982): Effects on psychological test performance of workers exposed to a single solvent (toluene): a comparison with effects of exposure to a mixture of organic solvents. Neurobehav Toxic01 Teratol 4:695 -70 1. Lindstrom K (1980): Changes in psychological performances of solvent-poisoned and solvent-exposed workers. Am J Ind Med 1:69-84. Lindstrom K, Wickstrom G (1983): Psychological function changes among maintenance house painters exposed to low levels of organic solvent mixtures. Acta Psychiatr Scand 67(Suppl 303):81-91. Mikkelsen S, Jorgensen M, Browne E, Gyldensted C (1988): Mixed solvent exposure and organic brain damage. A study of painters. Acta Neurol Scand Vol. 78 (Suppl 118):143. Nelson HE (1982): “ ‘National Adult Reading Test’; “Test Manual.” Windsor: NFER-Nelson. Smith A (1982): “Manual of the Symbol Digit Modalities Test.” Los Angeles: Western Psychological Services. Wechsler D (1981): “WAIS-R Manual.” New York: Psychological Corporation. WHO (1989): Environmental Health Series No. 36. Chronic effects of organic solvents on the central nervous system-core protocol for an international collaborative study.
