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Color vision impairments among shipyard workers exposed to mixed organic solvents, especially xylene
Neurotoxicology and Teratology 37 (2013) 39–43
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Neurotoxicology and Teratology journal homepage: www.elsevier.com/locate/neutera
Color vision impairments among shipyard workers exposed to mixed organic solvents, especially xylene Eun-Hee Lee a, Domyung Paek b, Young Lim Kho c, Kyungho Choi b, Hong Jae Chae d,⁎ a
Department of Visual Optics and Health Science, Graduate School of Health Science, Far East University, Eumsung, Chungbuk, Republic of Korea Department of Environmental Health, Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea School of Human & Environmental Sciences, Eulji University, Sungnam, Kyeonggi, Republic of Korea d Department of Occupational & Environmental Medicine, Chonnam National University Hwasun Hospital, Jeonnam, Republic of Korea b c
a r t i c l e
i n f o
Article history: Received 4 July 2012 Received in revised form 6 February 2013 Accepted 7 February 2013 Available online 16 February 2013 Keywords: Color vision impairments Lanthony D-15 Methylhippuric acid Organic solvents Shipyard workers Urinary metabolite
a b s t r a c t Objectives: We evaluated color vision impairment in workers exposed to organic solvents, especially xylene. Methods: Three groups of subjects, comprising 63 workers occupationally exposed to organic solvents, 122 non-exposed workers in the same industry, and 185 subjects from the general population as controls, were evaluated for color vision. Exposure to solvents was indirectly evaluated by measuring the concentration of a urinary metabolite. Color vision was assessed using the Lanthony Desaturated 15-hue (Lanthony D-15) panel. Results: Color confusion index (CCI) values in the exposed group were significantly higher than in the non-exposed workers or the general population, after adjustment for age and education, and significantly correlated with the concentration of methylhippuric acid. Color vision impairments were detected more frequently among the exposed group, and the most common types were type III and complex impairments. The rate of type III impairments was 9.52% in the exposed group, 1.64% in the non-exposed group, and 1.62% in the general population. Conclusion: Our results support the hypothesis that acquired color vision impairments could be induced by exposure to xylene. Testing for color vision impairment is a relatively simple, non-invasive and sensitive diagnostic method for relatively low-level exposures to xylene. © 2013 Elsevier Inc. All rights reserved.
1. Introduction Shipyard spray painters are exposed to various mixtures of organic solvents such as toluene, ethyl benzene, and xylene (Stellman, 1998). Despite respirators and protective clothing, solvents can enter the body through inhalation and skin contact (Chang et al., 2007a,b), and annual health examinations are provided for screening of adverse health effects for exposed workers in Korea. When compared to non-exposed workers, solvent-exposed workers showed an increase in subjective symptoms and poor performance on neurobehavioral tests; therefore, some battery tests have been suggested for environmental health studies (Anger et al., 1994). However, early detection of health effects related to solvent exposure is difficult in occupational settings. Furthermore, due to the cost and time involved, these tests have not been adopted in occupational health examinations. As a screening test for neurotoxicity, damages to the sensory system, including altered visual acuity (VA) and acquired dyschromatopsia, have been studied extensively. Particularly, acquired color vision impairments have been reported to be early indicators of neurotoxicity
⁎ Corresponding author. Tel.: +82 61 379 7788; fax: +82 61 379 7791. E-mail address: [email protected] (H.J. Chae). 0892-0362/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ntt.2013.02.005
from occupational exposure to organic solvents (Mergler, 1995; Gong et al., 2003; Lee et al., 2007; Attarchi et al., 2010; Guest et al., 2011). Lanthony D-15 color vision tests can be used to evaluate protan, deutan, tritan, and combined forms of deficiency with high sensitivity and specificity, and allow rapid and easy evaluation of congenital or acquired mild to moderate chromatic discrimination losses in color vision (Lanthony, 1978). The Lanthony D-15 test is a component of the adult environmental neurobehavioral test battery (AENTB) recommended by the Agency for Toxic Substances and Disease Registry (ATSDR) for level 1 testing in the sensory domain (Anger et al., 1994), and has been used for the monitoring of workers exposed to organic solvents (Gobba and Cavalleri, 2003). Although convenient, the variability of test results, both within and between studies, has been a source of discussion and concern (e.g., Paramei et al., 2004). This is particularly true for studies that include small sample sizes or inaccurate exposure assessments. In this study, we investigated the usefulness of acquired color vision impairment for assessing solvent-exposed workers along with biological monitoring. The Lanthony D-15 test was administered to three groups of people, solvent-exposed workers in a shipyard, office workers in the same shipyard as the first control group, and general population subjects as the second control group. Color vision in the three groups was compared and analyzed according to the level of
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solvent exposure estimated from the concentration of urinary metabolites.
exposure exceeds 1, the working environment is considered to be over the exposure limit, as defined by the American Conference of Governmental Industrial Hygienists (ACGIH, 2007).
2. Materials and methods 2.3. Biological monitoring 2.1. Subjects Three groups of adult males were recruited for the present study. As a pre-selection criterion, subjects with specific medical history were excluded. Subjects with congenital color vision impairment on the Ishihara test, diabetes mellitus, treatment with neurotoxic medications within the last 6 months, cerebrovascular disease, severe head trauma, a history of ophthalmologic diseases (i.e., glaucoma and cataracts), or when self-reported via questionnaire a current physician diagnosis, or currently under treatment, or not recovered from the related disease, or a low VA on the Snellen (VA > 20/33) and Hans (VA > 0.6) tests, were excluded. The first two groups consisted of 63 spray painters who were exposed to solvents during the work shift and 122 office workers from the same shipyard who were not supposedly exposed to solvents to any significant extent. The spray painters were exposed to various organic solvents, including toluene, xylene, isopropyl alcohol, methyl isobutyl ketone (MIBK), and ethyl benzene (Table 2). Their routine work involved grinding, paint mixing, and spray-painting, which were performed within the painting shop. As a work control group, 122 shipyard office workers who worked in the office building with no direct exposure to organic solvents were selected. As another control, a total of 185 adult males, age (within 5 years)- and sex-matched with the 185 shipyard workers, were selected from 483 males and 508 females (Table 1) who originally participated in a community health survey with 991 participants conducted during a 3-week period. In the survey, subjects provided medical examination information and basic individual information. Prior to the study, the purpose of the research was explained and consent was obtained from all participants. This study, including the protocols involving color vision testing and data confidentiality, was reviewed by the Institutional Review Board of the School of Public Health, Seoul National University, according to the tenets of the Declaration of Helsinki. 2.2. Exposure assessment Evaluation of worksite environmental exposure was performed by air sampling during work hours; the air samples were analyzed by gas chromatography. Time-weighted average (TWA) exposures were calculated for each organic solvent by multiplying concentration (C) by exposure time (T) during an 8-h work day. For complex exposures involving more than two solvents, exposure index (EI) was calculated by the following equation: Exposure Index ðEIÞ ¼
C1 C2 Cn þ þ⋯þ TLV1 TLV2 TLVn
ð1Þ
where Ci is the measured concentration of solvents 1, 2…, n, and TLV is the threshold value for each solvent. When the EI of the complex Table 1 General characteristics of the study subjects. Variables
Exposed worker (n = 63)
Office worker (n = 122)
General population (n = 185)
Mean age (±SD)⁎ Mean years of education (±SD)⁎⁎ Alcohol use (%) Smoking (%) Mean years of work duration (±SD)
37.3 (7.7) 11.4 (1.5) 46 (73.0) 29 (49.1) 8.8 (3.7)
34.0 (6.9) 14.9 (1.6) 92 (75.4) 47 (40.2) 7.8 (4.6)
41.1 (6.8) 13.6 (2.6) 96 (75) 59 (46.1) -
⁎ p b 0.01. ⁎⁎ p b 0.0001.
The methylhippuric acid, a metabolite of xylene (the organic solvent with the highest air concentration) was measured as biological marker of xylene exposures, according to the Korean health examination guidelines (Kang, 2006). For this purpose, urine samples were collected at the end of a work shift and methylhippuric acid was analyzed following the methods outlined in NIOSH 8301 (NIOSH, 2003), with minor modifications. Briefly, 200 μL of urine was added to 1.8 mL of deionized water. The sample was filtered with a nylon syringe filter (Whatman, Kent, UK) after mixing and centrifugation. Filtered samples (20 μL) were injected into a reversed-phase C18 column (5 μm, 4.6× 150 mm, Agilent Technologies, CA, USA) in a highperformance liquid chromatography system (Agilent 1100 series). Methylhippuric acid was then measured using a DAD UV detector at 225 nm after separation by isocratic elution (0.5% acetic acid and 10% acetonitrile in water). 2.4. Color vision impairments Before evaluating the color vision, we tested the VA and interviewed the subjects. The inclusion criteria were Hans (VA b 0.6) or better and absence of known ophthalmologic disease, lenticular opacity, cataract, age-related macular disease, and optic nerve pathology due to associated glaucoma. Monocular vision was tested separately from left to right. Color vision and VA, including corrected vision, were examined using monocular eye tests by an optician. Each eye was tested separately from left to right. Congenital color vision impairment was assessed by the Ishihara test and questionnaire. The Ishihara test was used for the detection of congenital color vision with the Ishihara plates (Ishihara color vision test, Kanehara & Co., Tokyo, Japan). The subject is asked to read the numbers on a plate, with approximately 5 s allowed per page. A subject who made more than three errors and could not read the next plate was judged to have a red/green (R/G) defect (Birch, 1993; Hart, 1987; Ishihara, 1996). We conducted the color vision testing at the beginning of a work shift when the acute effects of solvent exposure were expected to be small due to overnight dissipation. Color vision was assessed by the Lanthony D-15 test under standardized conditions (1500 lx at 30 cm above the task). Color vision was estimated quantitatively using a color confusion index (CCI), which was calculated from the total color distance score (TCDS) as the sum of color differences using the TCDS developed by Bowman (Bowman, 1982; Lanthony, 1986; Geller, 2001). The CCI was calculated by dividing each individual's TCDS by a perfect score. CCI values were presented as the average of values obtained from both eyes. A CCI of 1.0 indicated a perfect score, and subjects with impaired color vision had higher scores. However, some people with clinically normal vision can make small errors and have a score slightly greater than 1.0. Color vision impairments are classified into four types: type I, loss in the red–green range; type II, loss in the red– green and blue–yellow ranges; type III, loss in the blue–yellow range (Verriest, 1963; Geller and Hundell, 1997), and complex type, unclassified color vision loss. The subjects were classified as having color vision loss by the presence of more than two error lines across the results diagram. Subjects with one or two transpositions of adjacent colors were classified as having a minor abnormality, and not color vision loss. 2.5. Statistical analysis Methylhippuric acid data was log transformed. Among other covariates, age and years of education were treated as continuous
E.-H. Lee et al. / Neurotoxicology and Teratology 37 (2013) 39–43
variables. Alcohol use and smoking status were treated as categorical variables (yes or no). To examine whether covariates can be confounders, we first examined the association between independent covariates. Next, as confounders should be independent risk factors, we also investigated the associations of covariates with CCI values or types of dyschromatopsia. CCI values were not normally distributed, and so non-parametric Mann–Whitney U-tests and Kruskal–Wallis tests were used. The χ 2 test and Mantel–Haenszel χ 2 test were used to compare data distribution of categorical variables relevant to color vision impairments. For continuous variables, results were expressed as means (± SD). Group differences for categorical variables were adjusted using the general linear model (GLM). The correlation of education with CCI was tested using Spearman's rank correlation. Exact logistic regressions, after adjustment for age and education, were used to assess the strength of the influence of solvent exposure on acquired dyschromatopsia. All data were analyzed using the SAS (ver. 9.1) software. 3. Results General and behavioral characteristics of the study population are summarized in Table 1. There were statistically significant differences in age and education. Many volatile organic compounds were detected during the work shift, and among them, xylene showed the highest concentration with a geometric mean of 10.7 ppm. The level of urinary methylhippuric acid in the exposed group was 0.13 g/g creatinine, lower than the biological exposure index (BEI) of 1.5 g/g creatinine proposed by ACGIH (Tables 2 and 3), and was not detected among the office workers. Age was positively correlated with CCI (r =0.113, p = 0.028), although the correlation slope was slightly different for the three groups. The CCI showed a tendency to increase with age when all groups were combined, even though the association became non-significant when examined for each group: r = 0.14, p = 0.121 for the exposed group, r = −0.114, p = 0.375 for the work control group, and r = 0.087, p = 0.239 for the general population control group. Education was correlated to the CCI (r = − 0.2064, p b 0.0001), but also differed among the three groups: r = 0.02, p = 0.8864 for the exposed group, r = −0.09, p = 0.3239 for the work control group, and r = − 0.23, p = 0.0016 for the general population control group. Alcohol consumption and smoking showed no significant relationship with the CCI in all groups.
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Table 3 Biological assessments of exposed workers (n = 63). Markers of exposure
GM, g/g cre
BEI, g/g cre
Urinary methylhippuric acid (g/g cre)
0.13
1.5
GM, geometric mean, BEI, biological exposure index; cre, creatinine.
The presence of urinary xylene metabolites was significantly correlated with the CCI and remained significant even after adjustment for age, or age and education. Fig. 1 shows the significant correlations between the levels of methylhippuric acid and the adjusted CCI values for age and education. Table 4 shows differences in the CCI values between the exposed workers, office workers, and the general population. The CCI values of exposed workers were higher than the two control groups with marginal significance (p = 0.0618). The difference became more significant after adjusting for age and education; exposed workers showed significantly higher CCI values compared to the office worker (p = 0.0052) and general population (p =0.0019) controls. Color vision deficiencies were also more prevalent in the exposed workers than in the general population and office workers (Fig. 2). The prevalence of the blue–yellow impairment subtype in the exposed workers was 9.5% (6/63), which was significantly higher than in the office workers (1.6%, 2/122), or in the general population (1.6%, 3/185). Complex-type impairments also showed a higher prevalence in the exposed workers, with three affected subjects (4.76%), than in the general population, with only one affected subject (0.54%), while no affected subjects were identified in the office worker control group. When the presence of color vision impairment was analyzed in the exposed workers, the odds ratio of being color vision impaired tended to increase with increasing methylhippuric acid levels (OR = 2.85; 95% CI: 1.33–6.11). The association between methylhippuric acid and color vision impairment remained significant after adjustment for age and education (Table 5). 4. Discussion In this study, color vision impairments were more frequent in the exposed group, and were also associated with higher concentrations of urinary methylhippuric acid, suggesting an association between color vision impairment and exposure to xylene or mixed organic
Table 2 Environmental solvent concentrations of exposed workers (n = 63). Solvents
Mean (SD), ppm
TLV–TWA, ppm
Ethanol Isopropyl alcohol Propylene glycol monomethylether Cyclohexane Methyl isobutyl ketone Toluene Ethyl benzene Xylene Nonane Cumene (isopropylbenzene) 1-Butanol 2-butoxyethanol n-Hexane Methyl ethyl ketone Chlorobenzene Heptane Methylene chloride 2-ethoxyethanol Ethyl isobutyl ketone Cyclohexanone Exposure Index
6.97 (1.37) 4.53 (1.33) 1.82 (1.91) 2.02 (0.24) 2.50 (1.03) 2.28 (0.75) 6.00 (7.41) 10.67 (9.56) 1.46 (0.14) 2.01 (0.22 7.55 (6.38) 0.32 (0.46) 0.03 2.87 (0.06) 2.54 (0.09) 1.88 3.39 (0.25) 0.69 2.27 0.82 0.83
1000 400 100 300 50 100 100 100 200 50 50 25 50 200 75 400 50 5 50 25 1
TLV, threshold limit value; TWA, time-weighted average.
Fig. 1. Correlation between CCI and methylhippuric acid adjusted for age and education. Of the 63 exposed workers, data from only 26 subjects were plotted. The rest were not detected for methylhippuric acid in the urine samples. r = Pearson's correlation coefficient adjusted for age and education.
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Table 4 Color confusion index (CCI) of exposed workers, office workers, and the general population. Model Crude Exposed workers Office workers General population Adjusted for age and education a Exposed workers Office workers General population a
N 63
Mean (SD) 1.09 (0.14)
122 1.04 (0.06) 185 1.05 (0.06)
Range
p-value Note
Table 5 Logistic regression analysis of the relationship between color vision impairments and solvent exposure in shipyard workers, adjusted for age and education. Exposure Adjusted for age Methylhippuric acid Adjusted for age and education Methylhippuric acid
1.0–1.73 0.0618 1.0–1.39 1.0–1.36
Odds ratio
95% CI
p
2.85
1.33–6.11
0.007
2.45
1.04–5.79
0.041
CI, confidence interval.
4.1. Confounding factors 63
1.08 (0.01) 1.06–1.12
122 1.05 (0.01) 1.03–1.08 0.0052 185 1.04 (0.02) 1.01–1.10 0.0019
Exposed worker vs. Office worker Exposed worker vs. General population
CCI adjusted for age and education by the Tukey–Kramer test.
solvents. Organic solvents can particularly disturb the transmission process in the central visual pathway by altering nerve membrane receptors or by demyelinating the optic nerve (Byun et al., 2001). This study provides additional evidence for the relationship between color vision impairment and organic solvent exposure, especially urinary methylhippuric acid, a xylene metabolite. Previous studies showed that CCI is an important indicator of the preliminary stages of nervous system disorders in workers chronically exposed to a mixture of organic solvents (Attarchi et al., 2010). The results of this study contribute to the postulate that color vision testing is useful in the monitoring of workers exposed to solvents, especially xylene. Our study included two control groups, one from the same occupational setting but not exposed to the solvents, and the other from the general population. In a previous study, Iregren et al. (2002) assessed color vision deficiency in a general population without occupational solvent exposure. Although their study group was comprised of male and female subjects, the age range (26 to 46 years) was comparable to the male subjects (20 to 50 years) from the general population in our study who were age-matched to the exposed workers. Iregren et al. found mean CCIs of 1.2 ± 0.26 (median, 1.2) for the left eyes and 1.3 ± 0.28 (median, 1.2) for the right eyes, higher than the control group value (1.08) reported by Campagna et al. (2001). In the present study, the CCI of the age- and sex-matched controls from the general population (both eyes, 1.04 ± 0.02) and office workers (both eyes, 1.05 ± 0.01) were in the range 1.04 to 1.05. The CCI values in this study are slightly lower than those reported previously; the strict selection criteria applied in this study might have contributed to the difference. As exposure to neurotoxic agents such as alcohol, smoking, medicine, as well as aging, can influence the results, careful examination of potential exposure to neurotoxins is necessary in future comparisons.
Fig. 2. Prevalence of color vision impairments in shipyard workers and the general population. Type III, blue–yellow deficiency; Complex, unclassified deficiency. ⁎ pb 0.05.
In this study, potential confounding factors including age, education, smoking and alcohol drinking were assessed in terms of their association with organic solvent exposure and CCI. The CCI showed a tendency to increase with age when all groups were combined, even though the association became insignificant when examined for each group. This observation is in agreement with Mergler et al. (1987), who indicated that age and organic solvent exposure were important factors affecting the CCI. Schäper et al. (2004) also showed that CCI significantly increased with age in workers exposed to toluene. Age-associated changes in the CCI could be related to changes in the lens or macula (Pokorney et al., 1979; Campagna et al., 1995). Education was inversely associated with increased CCI, but the subjects educated to at least the college level also showed higher CCI values. Among the study population, alcohol consumption and smoking were not associated with color vision impairments or CCI. Conversely, a relationship between alcohol consumption and dyschromatopsia has been reported, where the prevalence of dyschromatopsia increased with alcohol consumption, and dyschromatopsia was localized in the blue– yellow axis (Mergler et al., 1988a). Smoking may be a possible confounder for dyschromatopsia, but tobacco smoking was not associated with color impairment in the present study. Schäper et al. also found that tobacco smoking did not contribute to the prediction of CCI in a toluene exposure study (Schäper et al., 2004; Paramei et al., 2004). 4.2. Solvent exposure Because environmental exposure measurements consisting of regional sampling and personal sampling data were not complete, we could not present the cumulative exposure levels of organic solvent mixtures in this paper. Therefore, we selected biological monitoring rather than environmental exposure measurements for the exposure assessment. This permitted estimation of the amount absorbed by the individual. Additionally, in spite of mixed exposure to organic solvents, we evaluated only methylhippuric acid, which did not reflect overall exposure, thus the cumulative exposure to methylhippuric acid was not evaluated. The CCI was correlated with methylhippuric acid. Zavalic et al. (1998) found similar results in 37 workers at a rotogravure printing press, although the subjects were exposed to different substances than the subjects in our study. They showed a correlation with hippuric acid, after adjustment for age and alcohol use (r = 0.535, p b 0.005). In the present study, the CCI in the exposed workers showed a similar but slightly stronger association (r = 0.867, p b 0.001) with organic solvent exposure. This might be due to the more stringent subject selection criteria and use of biomonitoring instead of air measurement in this study. CCI adjusted for age and education also differed significantly between exposed workers and the two control groups (Table 4). In addition, color vision impairments were more frequent in exposed workers compared to office workers. While blue–yellow impairments in both eyes appeared in two subjects in the work control group (1.64%), six (9.52%) impairments were detected in the exposed group. Regarding complex-type impairments, the exposed group showed the greatest incidence (three subjects, 4.76%). In a similar study (Fallas et al., 1992), blue–yellow deficiency or red–green plus
E.-H. Lee et al. / Neurotoxicology and Teratology 37 (2013) 39–43
blue–yellow deficiency were observed in 32 (53%) of 60 styreneexposed shipyard workers, while in only 20 (33%) of 60 controls (p b 0.05). In the automobile industry in Germany, although exposure to solvent mixtures was below the German TLV, the differences in CCI between the exposed workers and controls were statistically significant (p-values for each eye = 0.0002, 0.0001). Among the 24 exposed workers, five made at least one blue–yellow error with the first or second eye, whereas none of the control subjects made an error (Muttray et al., 1997). An increase in blue–yellow deficiency was reported by most color vision-loss studies of solvent-exposed workers (Gobba et al., 1991; Mergler et al., 1988b). Similar to Mergler et al., our results support the KoÈllner's rule that changes in the blue–yellow range are frequent in solvent-exposed workers, where the early effects reflect changes in the external retinal layers (Mergler et al., 1987; KoÈllner, 1912). 5. Conclusion We found that the probability of acquired color vision impairment was increased in workers exposed to low concentrations of organic solvents, such as xylene, or mixed organic compounds, relative to non-exposed controls or to the general population. Our results support the hypothesis that acquired color vision impairment is induced by low-level exposure to organic solvents such as xylene. As shown in this study, testing for color vision impairment has the potential to make significant contributions to the detection of neurological changes in a relatively simple, non-invasive, and more sensitive manner, while further assessment of color vision in the general population is required to determine the relevant baseline CCI values. Conflict of interest statement No conflict of interest. References ACGIH. Guide to Occupational Exposure Values; 2007. Anger WK, Letz R, Chrislip DW, Frumkin H, Hudnell K, Russo JM, et al. Neurobehavioral test methods for environmental health studies of adults. Neurotoxicol Teratol 1994;16(5):489–97. Attarchi MS, Labbafinejad Y, Mohammadi S. Occupational exposure to different levels of mixed organicsolvents and colour vision impairment. Neurotoxicol Teratol 2010;32(5):558–62. [Sep-Oct]. Birch J. Clinical tests design and examination procedure. Diagnosis of defective color vision. Oxford: Butterworth-Heiniman; 1993. p. 53–70. Bowman KJ. A method for quantitative scoring of the Farnsworth Panel D-15. Acta Ophthalmol 1982;60:907–91. Byun JH, Lee KY, Kim YK, Ko KW, Lee YH. Acquired dyschromatopsia in women workers in shoe manufacturing who were exposed to organic solvents. Korean J Occup Environ Med 2001;13(3):232–41. Campagna D, Mergler D, Huel G, Bélanger S, Truchon G, Ostiguy C, et al. Visual dysfunction among styrene-exposed workers. Scand J Work Environ Health 1995;21(5):382–90. Campagna D, Stengel B, Mergler D, Limasset JC, Diebold F, Michard D, et al. Color vision and occupational toluene exposure. Neurotoxicol Teratol 2001;23(5):473–80.
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Neurotoxicology and Teratology journal homepage: www.elsevier.com/locate/neutera
Color vision impairments among shipyard workers exposed to mixed organic solvents, especially xylene Eun-Hee Lee a, Domyung Paek b, Young Lim Kho c, Kyungho Choi b, Hong Jae Chae d,⁎ a
Department of Visual Optics and Health Science, Graduate School of Health Science, Far East University, Eumsung, Chungbuk, Republic of Korea Department of Environmental Health, Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea School of Human & Environmental Sciences, Eulji University, Sungnam, Kyeonggi, Republic of Korea d Department of Occupational & Environmental Medicine, Chonnam National University Hwasun Hospital, Jeonnam, Republic of Korea b c
a r t i c l e
i n f o
Article history: Received 4 July 2012 Received in revised form 6 February 2013 Accepted 7 February 2013 Available online 16 February 2013 Keywords: Color vision impairments Lanthony D-15 Methylhippuric acid Organic solvents Shipyard workers Urinary metabolite
a b s t r a c t Objectives: We evaluated color vision impairment in workers exposed to organic solvents, especially xylene. Methods: Three groups of subjects, comprising 63 workers occupationally exposed to organic solvents, 122 non-exposed workers in the same industry, and 185 subjects from the general population as controls, were evaluated for color vision. Exposure to solvents was indirectly evaluated by measuring the concentration of a urinary metabolite. Color vision was assessed using the Lanthony Desaturated 15-hue (Lanthony D-15) panel. Results: Color confusion index (CCI) values in the exposed group were significantly higher than in the non-exposed workers or the general population, after adjustment for age and education, and significantly correlated with the concentration of methylhippuric acid. Color vision impairments were detected more frequently among the exposed group, and the most common types were type III and complex impairments. The rate of type III impairments was 9.52% in the exposed group, 1.64% in the non-exposed group, and 1.62% in the general population. Conclusion: Our results support the hypothesis that acquired color vision impairments could be induced by exposure to xylene. Testing for color vision impairment is a relatively simple, non-invasive and sensitive diagnostic method for relatively low-level exposures to xylene. © 2013 Elsevier Inc. All rights reserved.
1. Introduction Shipyard spray painters are exposed to various mixtures of organic solvents such as toluene, ethyl benzene, and xylene (Stellman, 1998). Despite respirators and protective clothing, solvents can enter the body through inhalation and skin contact (Chang et al., 2007a,b), and annual health examinations are provided for screening of adverse health effects for exposed workers in Korea. When compared to non-exposed workers, solvent-exposed workers showed an increase in subjective symptoms and poor performance on neurobehavioral tests; therefore, some battery tests have been suggested for environmental health studies (Anger et al., 1994). However, early detection of health effects related to solvent exposure is difficult in occupational settings. Furthermore, due to the cost and time involved, these tests have not been adopted in occupational health examinations. As a screening test for neurotoxicity, damages to the sensory system, including altered visual acuity (VA) and acquired dyschromatopsia, have been studied extensively. Particularly, acquired color vision impairments have been reported to be early indicators of neurotoxicity
⁎ Corresponding author. Tel.: +82 61 379 7788; fax: +82 61 379 7791. E-mail address: [email protected] (H.J. Chae). 0892-0362/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ntt.2013.02.005
from occupational exposure to organic solvents (Mergler, 1995; Gong et al., 2003; Lee et al., 2007; Attarchi et al., 2010; Guest et al., 2011). Lanthony D-15 color vision tests can be used to evaluate protan, deutan, tritan, and combined forms of deficiency with high sensitivity and specificity, and allow rapid and easy evaluation of congenital or acquired mild to moderate chromatic discrimination losses in color vision (Lanthony, 1978). The Lanthony D-15 test is a component of the adult environmental neurobehavioral test battery (AENTB) recommended by the Agency for Toxic Substances and Disease Registry (ATSDR) for level 1 testing in the sensory domain (Anger et al., 1994), and has been used for the monitoring of workers exposed to organic solvents (Gobba and Cavalleri, 2003). Although convenient, the variability of test results, both within and between studies, has been a source of discussion and concern (e.g., Paramei et al., 2004). This is particularly true for studies that include small sample sizes or inaccurate exposure assessments. In this study, we investigated the usefulness of acquired color vision impairment for assessing solvent-exposed workers along with biological monitoring. The Lanthony D-15 test was administered to three groups of people, solvent-exposed workers in a shipyard, office workers in the same shipyard as the first control group, and general population subjects as the second control group. Color vision in the three groups was compared and analyzed according to the level of
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solvent exposure estimated from the concentration of urinary metabolites.
exposure exceeds 1, the working environment is considered to be over the exposure limit, as defined by the American Conference of Governmental Industrial Hygienists (ACGIH, 2007).
2. Materials and methods 2.3. Biological monitoring 2.1. Subjects Three groups of adult males were recruited for the present study. As a pre-selection criterion, subjects with specific medical history were excluded. Subjects with congenital color vision impairment on the Ishihara test, diabetes mellitus, treatment with neurotoxic medications within the last 6 months, cerebrovascular disease, severe head trauma, a history of ophthalmologic diseases (i.e., glaucoma and cataracts), or when self-reported via questionnaire a current physician diagnosis, or currently under treatment, or not recovered from the related disease, or a low VA on the Snellen (VA > 20/33) and Hans (VA > 0.6) tests, were excluded. The first two groups consisted of 63 spray painters who were exposed to solvents during the work shift and 122 office workers from the same shipyard who were not supposedly exposed to solvents to any significant extent. The spray painters were exposed to various organic solvents, including toluene, xylene, isopropyl alcohol, methyl isobutyl ketone (MIBK), and ethyl benzene (Table 2). Their routine work involved grinding, paint mixing, and spray-painting, which were performed within the painting shop. As a work control group, 122 shipyard office workers who worked in the office building with no direct exposure to organic solvents were selected. As another control, a total of 185 adult males, age (within 5 years)- and sex-matched with the 185 shipyard workers, were selected from 483 males and 508 females (Table 1) who originally participated in a community health survey with 991 participants conducted during a 3-week period. In the survey, subjects provided medical examination information and basic individual information. Prior to the study, the purpose of the research was explained and consent was obtained from all participants. This study, including the protocols involving color vision testing and data confidentiality, was reviewed by the Institutional Review Board of the School of Public Health, Seoul National University, according to the tenets of the Declaration of Helsinki. 2.2. Exposure assessment Evaluation of worksite environmental exposure was performed by air sampling during work hours; the air samples were analyzed by gas chromatography. Time-weighted average (TWA) exposures were calculated for each organic solvent by multiplying concentration (C) by exposure time (T) during an 8-h work day. For complex exposures involving more than two solvents, exposure index (EI) was calculated by the following equation: Exposure Index ðEIÞ ¼
C1 C2 Cn þ þ⋯þ TLV1 TLV2 TLVn
ð1Þ
where Ci is the measured concentration of solvents 1, 2…, n, and TLV is the threshold value for each solvent. When the EI of the complex Table 1 General characteristics of the study subjects. Variables
Exposed worker (n = 63)
Office worker (n = 122)
General population (n = 185)
Mean age (±SD)⁎ Mean years of education (±SD)⁎⁎ Alcohol use (%) Smoking (%) Mean years of work duration (±SD)
37.3 (7.7) 11.4 (1.5) 46 (73.0) 29 (49.1) 8.8 (3.7)
34.0 (6.9) 14.9 (1.6) 92 (75.4) 47 (40.2) 7.8 (4.6)
41.1 (6.8) 13.6 (2.6) 96 (75) 59 (46.1) -
⁎ p b 0.01. ⁎⁎ p b 0.0001.
The methylhippuric acid, a metabolite of xylene (the organic solvent with the highest air concentration) was measured as biological marker of xylene exposures, according to the Korean health examination guidelines (Kang, 2006). For this purpose, urine samples were collected at the end of a work shift and methylhippuric acid was analyzed following the methods outlined in NIOSH 8301 (NIOSH, 2003), with minor modifications. Briefly, 200 μL of urine was added to 1.8 mL of deionized water. The sample was filtered with a nylon syringe filter (Whatman, Kent, UK) after mixing and centrifugation. Filtered samples (20 μL) were injected into a reversed-phase C18 column (5 μm, 4.6× 150 mm, Agilent Technologies, CA, USA) in a highperformance liquid chromatography system (Agilent 1100 series). Methylhippuric acid was then measured using a DAD UV detector at 225 nm after separation by isocratic elution (0.5% acetic acid and 10% acetonitrile in water). 2.4. Color vision impairments Before evaluating the color vision, we tested the VA and interviewed the subjects. The inclusion criteria were Hans (VA b 0.6) or better and absence of known ophthalmologic disease, lenticular opacity, cataract, age-related macular disease, and optic nerve pathology due to associated glaucoma. Monocular vision was tested separately from left to right. Color vision and VA, including corrected vision, were examined using monocular eye tests by an optician. Each eye was tested separately from left to right. Congenital color vision impairment was assessed by the Ishihara test and questionnaire. The Ishihara test was used for the detection of congenital color vision with the Ishihara plates (Ishihara color vision test, Kanehara & Co., Tokyo, Japan). The subject is asked to read the numbers on a plate, with approximately 5 s allowed per page. A subject who made more than three errors and could not read the next plate was judged to have a red/green (R/G) defect (Birch, 1993; Hart, 1987; Ishihara, 1996). We conducted the color vision testing at the beginning of a work shift when the acute effects of solvent exposure were expected to be small due to overnight dissipation. Color vision was assessed by the Lanthony D-15 test under standardized conditions (1500 lx at 30 cm above the task). Color vision was estimated quantitatively using a color confusion index (CCI), which was calculated from the total color distance score (TCDS) as the sum of color differences using the TCDS developed by Bowman (Bowman, 1982; Lanthony, 1986; Geller, 2001). The CCI was calculated by dividing each individual's TCDS by a perfect score. CCI values were presented as the average of values obtained from both eyes. A CCI of 1.0 indicated a perfect score, and subjects with impaired color vision had higher scores. However, some people with clinically normal vision can make small errors and have a score slightly greater than 1.0. Color vision impairments are classified into four types: type I, loss in the red–green range; type II, loss in the red– green and blue–yellow ranges; type III, loss in the blue–yellow range (Verriest, 1963; Geller and Hundell, 1997), and complex type, unclassified color vision loss. The subjects were classified as having color vision loss by the presence of more than two error lines across the results diagram. Subjects with one or two transpositions of adjacent colors were classified as having a minor abnormality, and not color vision loss. 2.5. Statistical analysis Methylhippuric acid data was log transformed. Among other covariates, age and years of education were treated as continuous
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variables. Alcohol use and smoking status were treated as categorical variables (yes or no). To examine whether covariates can be confounders, we first examined the association between independent covariates. Next, as confounders should be independent risk factors, we also investigated the associations of covariates with CCI values or types of dyschromatopsia. CCI values were not normally distributed, and so non-parametric Mann–Whitney U-tests and Kruskal–Wallis tests were used. The χ 2 test and Mantel–Haenszel χ 2 test were used to compare data distribution of categorical variables relevant to color vision impairments. For continuous variables, results were expressed as means (± SD). Group differences for categorical variables were adjusted using the general linear model (GLM). The correlation of education with CCI was tested using Spearman's rank correlation. Exact logistic regressions, after adjustment for age and education, were used to assess the strength of the influence of solvent exposure on acquired dyschromatopsia. All data were analyzed using the SAS (ver. 9.1) software. 3. Results General and behavioral characteristics of the study population are summarized in Table 1. There were statistically significant differences in age and education. Many volatile organic compounds were detected during the work shift, and among them, xylene showed the highest concentration with a geometric mean of 10.7 ppm. The level of urinary methylhippuric acid in the exposed group was 0.13 g/g creatinine, lower than the biological exposure index (BEI) of 1.5 g/g creatinine proposed by ACGIH (Tables 2 and 3), and was not detected among the office workers. Age was positively correlated with CCI (r =0.113, p = 0.028), although the correlation slope was slightly different for the three groups. The CCI showed a tendency to increase with age when all groups were combined, even though the association became non-significant when examined for each group: r = 0.14, p = 0.121 for the exposed group, r = −0.114, p = 0.375 for the work control group, and r = 0.087, p = 0.239 for the general population control group. Education was correlated to the CCI (r = − 0.2064, p b 0.0001), but also differed among the three groups: r = 0.02, p = 0.8864 for the exposed group, r = −0.09, p = 0.3239 for the work control group, and r = − 0.23, p = 0.0016 for the general population control group. Alcohol consumption and smoking showed no significant relationship with the CCI in all groups.
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Table 3 Biological assessments of exposed workers (n = 63). Markers of exposure
GM, g/g cre
BEI, g/g cre
Urinary methylhippuric acid (g/g cre)
0.13
1.5
GM, geometric mean, BEI, biological exposure index; cre, creatinine.
The presence of urinary xylene metabolites was significantly correlated with the CCI and remained significant even after adjustment for age, or age and education. Fig. 1 shows the significant correlations between the levels of methylhippuric acid and the adjusted CCI values for age and education. Table 4 shows differences in the CCI values between the exposed workers, office workers, and the general population. The CCI values of exposed workers were higher than the two control groups with marginal significance (p = 0.0618). The difference became more significant after adjusting for age and education; exposed workers showed significantly higher CCI values compared to the office worker (p = 0.0052) and general population (p =0.0019) controls. Color vision deficiencies were also more prevalent in the exposed workers than in the general population and office workers (Fig. 2). The prevalence of the blue–yellow impairment subtype in the exposed workers was 9.5% (6/63), which was significantly higher than in the office workers (1.6%, 2/122), or in the general population (1.6%, 3/185). Complex-type impairments also showed a higher prevalence in the exposed workers, with three affected subjects (4.76%), than in the general population, with only one affected subject (0.54%), while no affected subjects were identified in the office worker control group. When the presence of color vision impairment was analyzed in the exposed workers, the odds ratio of being color vision impaired tended to increase with increasing methylhippuric acid levels (OR = 2.85; 95% CI: 1.33–6.11). The association between methylhippuric acid and color vision impairment remained significant after adjustment for age and education (Table 5). 4. Discussion In this study, color vision impairments were more frequent in the exposed group, and were also associated with higher concentrations of urinary methylhippuric acid, suggesting an association between color vision impairment and exposure to xylene or mixed organic
Table 2 Environmental solvent concentrations of exposed workers (n = 63). Solvents
Mean (SD), ppm
TLV–TWA, ppm
Ethanol Isopropyl alcohol Propylene glycol monomethylether Cyclohexane Methyl isobutyl ketone Toluene Ethyl benzene Xylene Nonane Cumene (isopropylbenzene) 1-Butanol 2-butoxyethanol n-Hexane Methyl ethyl ketone Chlorobenzene Heptane Methylene chloride 2-ethoxyethanol Ethyl isobutyl ketone Cyclohexanone Exposure Index
6.97 (1.37) 4.53 (1.33) 1.82 (1.91) 2.02 (0.24) 2.50 (1.03) 2.28 (0.75) 6.00 (7.41) 10.67 (9.56) 1.46 (0.14) 2.01 (0.22 7.55 (6.38) 0.32 (0.46) 0.03 2.87 (0.06) 2.54 (0.09) 1.88 3.39 (0.25) 0.69 2.27 0.82 0.83
1000 400 100 300 50 100 100 100 200 50 50 25 50 200 75 400 50 5 50 25 1
TLV, threshold limit value; TWA, time-weighted average.
Fig. 1. Correlation between CCI and methylhippuric acid adjusted for age and education. Of the 63 exposed workers, data from only 26 subjects were plotted. The rest were not detected for methylhippuric acid in the urine samples. r = Pearson's correlation coefficient adjusted for age and education.
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Table 4 Color confusion index (CCI) of exposed workers, office workers, and the general population. Model Crude Exposed workers Office workers General population Adjusted for age and education a Exposed workers Office workers General population a
N 63
Mean (SD) 1.09 (0.14)
122 1.04 (0.06) 185 1.05 (0.06)
Range
p-value Note
Table 5 Logistic regression analysis of the relationship between color vision impairments and solvent exposure in shipyard workers, adjusted for age and education. Exposure Adjusted for age Methylhippuric acid Adjusted for age and education Methylhippuric acid
1.0–1.73 0.0618 1.0–1.39 1.0–1.36
Odds ratio
95% CI
p
2.85
1.33–6.11
0.007
2.45
1.04–5.79
0.041
CI, confidence interval.
4.1. Confounding factors 63
1.08 (0.01) 1.06–1.12
122 1.05 (0.01) 1.03–1.08 0.0052 185 1.04 (0.02) 1.01–1.10 0.0019
Exposed worker vs. Office worker Exposed worker vs. General population
CCI adjusted for age and education by the Tukey–Kramer test.
solvents. Organic solvents can particularly disturb the transmission process in the central visual pathway by altering nerve membrane receptors or by demyelinating the optic nerve (Byun et al., 2001). This study provides additional evidence for the relationship between color vision impairment and organic solvent exposure, especially urinary methylhippuric acid, a xylene metabolite. Previous studies showed that CCI is an important indicator of the preliminary stages of nervous system disorders in workers chronically exposed to a mixture of organic solvents (Attarchi et al., 2010). The results of this study contribute to the postulate that color vision testing is useful in the monitoring of workers exposed to solvents, especially xylene. Our study included two control groups, one from the same occupational setting but not exposed to the solvents, and the other from the general population. In a previous study, Iregren et al. (2002) assessed color vision deficiency in a general population without occupational solvent exposure. Although their study group was comprised of male and female subjects, the age range (26 to 46 years) was comparable to the male subjects (20 to 50 years) from the general population in our study who were age-matched to the exposed workers. Iregren et al. found mean CCIs of 1.2 ± 0.26 (median, 1.2) for the left eyes and 1.3 ± 0.28 (median, 1.2) for the right eyes, higher than the control group value (1.08) reported by Campagna et al. (2001). In the present study, the CCI of the age- and sex-matched controls from the general population (both eyes, 1.04 ± 0.02) and office workers (both eyes, 1.05 ± 0.01) were in the range 1.04 to 1.05. The CCI values in this study are slightly lower than those reported previously; the strict selection criteria applied in this study might have contributed to the difference. As exposure to neurotoxic agents such as alcohol, smoking, medicine, as well as aging, can influence the results, careful examination of potential exposure to neurotoxins is necessary in future comparisons.
Fig. 2. Prevalence of color vision impairments in shipyard workers and the general population. Type III, blue–yellow deficiency; Complex, unclassified deficiency. ⁎ pb 0.05.
In this study, potential confounding factors including age, education, smoking and alcohol drinking were assessed in terms of their association with organic solvent exposure and CCI. The CCI showed a tendency to increase with age when all groups were combined, even though the association became insignificant when examined for each group. This observation is in agreement with Mergler et al. (1987), who indicated that age and organic solvent exposure were important factors affecting the CCI. Schäper et al. (2004) also showed that CCI significantly increased with age in workers exposed to toluene. Age-associated changes in the CCI could be related to changes in the lens or macula (Pokorney et al., 1979; Campagna et al., 1995). Education was inversely associated with increased CCI, but the subjects educated to at least the college level also showed higher CCI values. Among the study population, alcohol consumption and smoking were not associated with color vision impairments or CCI. Conversely, a relationship between alcohol consumption and dyschromatopsia has been reported, where the prevalence of dyschromatopsia increased with alcohol consumption, and dyschromatopsia was localized in the blue– yellow axis (Mergler et al., 1988a). Smoking may be a possible confounder for dyschromatopsia, but tobacco smoking was not associated with color impairment in the present study. Schäper et al. also found that tobacco smoking did not contribute to the prediction of CCI in a toluene exposure study (Schäper et al., 2004; Paramei et al., 2004). 4.2. Solvent exposure Because environmental exposure measurements consisting of regional sampling and personal sampling data were not complete, we could not present the cumulative exposure levels of organic solvent mixtures in this paper. Therefore, we selected biological monitoring rather than environmental exposure measurements for the exposure assessment. This permitted estimation of the amount absorbed by the individual. Additionally, in spite of mixed exposure to organic solvents, we evaluated only methylhippuric acid, which did not reflect overall exposure, thus the cumulative exposure to methylhippuric acid was not evaluated. The CCI was correlated with methylhippuric acid. Zavalic et al. (1998) found similar results in 37 workers at a rotogravure printing press, although the subjects were exposed to different substances than the subjects in our study. They showed a correlation with hippuric acid, after adjustment for age and alcohol use (r = 0.535, p b 0.005). In the present study, the CCI in the exposed workers showed a similar but slightly stronger association (r = 0.867, p b 0.001) with organic solvent exposure. This might be due to the more stringent subject selection criteria and use of biomonitoring instead of air measurement in this study. CCI adjusted for age and education also differed significantly between exposed workers and the two control groups (Table 4). In addition, color vision impairments were more frequent in exposed workers compared to office workers. While blue–yellow impairments in both eyes appeared in two subjects in the work control group (1.64%), six (9.52%) impairments were detected in the exposed group. Regarding complex-type impairments, the exposed group showed the greatest incidence (three subjects, 4.76%). In a similar study (Fallas et al., 1992), blue–yellow deficiency or red–green plus
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blue–yellow deficiency were observed in 32 (53%) of 60 styreneexposed shipyard workers, while in only 20 (33%) of 60 controls (p b 0.05). In the automobile industry in Germany, although exposure to solvent mixtures was below the German TLV, the differences in CCI between the exposed workers and controls were statistically significant (p-values for each eye = 0.0002, 0.0001). Among the 24 exposed workers, five made at least one blue–yellow error with the first or second eye, whereas none of the control subjects made an error (Muttray et al., 1997). An increase in blue–yellow deficiency was reported by most color vision-loss studies of solvent-exposed workers (Gobba et al., 1991; Mergler et al., 1988b). Similar to Mergler et al., our results support the KoÈllner's rule that changes in the blue–yellow range are frequent in solvent-exposed workers, where the early effects reflect changes in the external retinal layers (Mergler et al., 1987; KoÈllner, 1912). 5. Conclusion We found that the probability of acquired color vision impairment was increased in workers exposed to low concentrations of organic solvents, such as xylene, or mixed organic compounds, relative to non-exposed controls or to the general population. Our results support the hypothesis that acquired color vision impairment is induced by low-level exposure to organic solvents such as xylene. As shown in this study, testing for color vision impairment has the potential to make significant contributions to the detection of neurological changes in a relatively simple, non-invasive, and more sensitive manner, while further assessment of color vision in the general population is required to determine the relevant baseline CCI values. Conflict of interest statement No conflict of interest. References ACGIH. Guide to Occupational Exposure Values; 2007. Anger WK, Letz R, Chrislip DW, Frumkin H, Hudnell K, Russo JM, et al. Neurobehavioral test methods for environmental health studies of adults. Neurotoxicol Teratol 1994;16(5):489–97. Attarchi MS, Labbafinejad Y, Mohammadi S. Occupational exposure to different levels of mixed organicsolvents and colour vision impairment. Neurotoxicol Teratol 2010;32(5):558–62. [Sep-Oct]. Birch J. Clinical tests design and examination procedure. Diagnosis of defective color vision. Oxford: Butterworth-Heiniman; 1993. p. 53–70. Bowman KJ. A method for quantitative scoring of the Farnsworth Panel D-15. Acta Ophthalmol 1982;60:907–91. Byun JH, Lee KY, Kim YK, Ko KW, Lee YH. Acquired dyschromatopsia in women workers in shoe manufacturing who were exposed to organic solvents. Korean J Occup Environ Med 2001;13(3):232–41. Campagna D, Mergler D, Huel G, Bélanger S, Truchon G, Ostiguy C, et al. Visual dysfunction among styrene-exposed workers. Scand J Work Environ Health 1995;21(5):382–90. Campagna D, Stengel B, Mergler D, Limasset JC, Diebold F, Michard D, et al. Color vision and occupational toluene exposure. Neurotoxicol Teratol 2001;23(5):473–80.
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