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Congener profiles of occupational PCB exposure versus PCB exposure from fish consumption
Chemosphere 69 (2007) 435–443 www.elsevier.com/locate/chemosphere
Congener profiles of occupational PCB exposure versus PCB exposure from fish consumption Sally Freels a,*, Lin Kaatz Chary b, Mary Turyk a, Julie Piorkowski a, Katherine Mallin a, John Dimos c, Henry Anderson d, Ken McCann e, Virlyn Burse f, Victoria Persky b a
b
Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, 1603 West Taylor Street Room 953 (M/C 922), Chicago, IL 60612, USA Great Lakes Centers for Occupational and Environmental Safety and Health, School of Public Health, University of Illinois at Chicago, IL, USA c Division of Environmental and Occupational Health Sciences, School of Public Health, University of Illinois at Chicago, IL, USA d Wisconsin Division of Public Health, Bureau of Environmental Health, Madison, WI, USA e Division of Environmental Health, Illinois Department of Public Health, Springfield, IL, USA f Centers for Disease Control and Prevention, Atlanta, GA, USA Received 6 September 2006; received in revised form 10 April 2007; accepted 26 April 2007 Available online 20 June 2007
Abstract The composition of polychlorinated biphenyl (PCB) congeners in serum samples is compared between a cohort previously exposed to PCBs from working at a capacitor plant (n = 180) and a cohort of Great Lakes sport-caught fish eaters (n = 217). Fourteen congeners were measured in both samples. A multiple logistic regression model differentiating the two groups as a function of relative proportions amongst congeners 74, 138, 153, 180, and 201 correctly classifies more than 99% of the people (395/397); higher proportions of congeners 74, 153, and 201 characterize capacitor plant workers, while higher proportions of congeners 138 and 180 characterize fish eaters. The pattern is driven by the relative amounts of 74 + 153 + 201 compared to 138 + 180; all of the fish eaters, but only 5% of the capacitor plant workers, have a greater percent of 138 + 180 than 74 + 153 + 201. Consideration of combinations of congener levels and their relative proportions is relevant to tracking route of exposure and may also be relevant to modeling effects on health outcomes. Ó 2007 Elsevier Ltd. All rights reserved. Keywords: PCBs; Congeners; Occupational exposure; Fish consumption; Logistic regression
1. Introduction Polychlorinated biphenyls, or PCBs, are synthetic chemicals designed to be extremely stable and easily soluble in most organic solvents. PCBs were first introduced to the electrical industry in 1929. Their use in the manufacturing of electrical capacitors and transformers was widespread until 1978, when production and use of PCBs was banned in the US because of concerns about effects of PCB exposure on human health and the environment (ATSDR, 1993). PCBs persist in the environment to the extent that
*
Corresponding author. Tel.: +1 312 996 4763; fax: +1 312 996 0064. E-mail address: [email protected] (S. Freels).
0045-6535/$ - see front matter Ó 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.chemosphere.2007.04.087
all geographic areas contain some background exposure levels (Hansen, 1987; UNEP, 1998). Routes of exposure beyond background levels include exposure to a single high dose of PCBs as a result of an accident (Murai et al., 1987; Hsieh et al., 1996; Guo et al., 1997; Osius et al., 1999; Lung et al., 2005; Hsu et al., 2005); exposure by working directly with PCBs, in an occupational setting (Brown and Jones, 1981; Wolff et al., 1982; Phillips et al., 1989; Kimbrough et al., 1998); and exposure through consumption of contaminated food, particularly fish (Maack and Sonzogni, 1988; Fitzgerald et al., 1998; Hanrahan et al., 1999; Turyk et al., 2006). The presence of PCBs in serum has been studied as the total of all detectable congeners, or total PCBs, and in more recent years as levels of specific congeners. Capacitor
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plant workers were exposed directly to the original Aroclor mixtures via dermal exposure and/or inhalation and ingestion (Jones, 1977; NIOSH, 1977a,b; Lees et al., 1987). PCBs released into the environment make their way to rivers and lakes and concentrate in the fat tissue of fish (James, 2001). Due to the transformation of PCBs as they move through the environment, a different distribution of congeners is expected in individuals exposed to PCBs through fish consumption compared with capacitor plant workers exposed in an occupational setting. This analysis uses data from two different studies to compare the composition of PCB congeners in serum between those with occupational versus fish consumption exposure. One study includes serum samples from a cohort of capacitor plant workers in LaSalle, Illinois, where PCBs were used from 1952 until 1978. The second study includes serum samples from a cohort who were heavy consumers of sport-caught fish from the Great Lakes, where bioaccumulation of PCBs in fish has been well documented. 2. Methods: cohort selection Two cohorts were selected for comparison, one representing occupational exposure and one representing exposure from a common contaminated food source. The LaSalle Electrical Utilities Company (EUC) used PCBs to manufacture electrical capacitors from 1952 until PCBs were banned in 1978. After EUC closed in 1981, it was listed on the National Priorities List for cleanup and became a Superfund site because of PCB contamination. In 1996, as a follow-up to the Superfund remediation, a cross-sectional health effects study was undertaken by the University of Illinois at Chicago School of Public Health under the auspices of the Agency for Toxic Substances and Disease Registry (ATSDR) and the Illinois Department of Public Health. The study sample was assembled from former EUC workers and community residents who had not worked in the plant. The sample for this analysis consisted of 180 people who worked at the EUC in 1952 or later, when PCBs were being used, and who are known, based on survey data, to have been exposed to PCBs at work. A control group of non-workers was excluded to create a group who were all occupationally exposed to PCBs. In 1993, the Consortium for the Health Assessment of Great Lakes Sport Fish Consumption conducted a study on a sample of charter boat captains on Lakes Michigan, Huron, and Erie, and a sample of Wisconsin anglers. Information about fish consumption habits and demographics were obtained from a telephone survey, and serum samples were drawn. A detailed description of the full study protocol has been previously published (Anderson et al., 1996). The sample used here is from a study of hormones performed on a subset of the original sample. Details of the hormone study have been published elsewhere (Persky et al., 2001). The sample for this analysis consists of 217 people who ate Great Lakes sport-caught fish (GLSCF) in the past year before the survey. A group who ate fish
from smaller lakes in the area was excluded to create a group that consumed from the same contaminated food source. All available PCB mixtures, known as Aroclors, were used at the LaSalle utilities plant, and all Aroclors were potentially released into the Great Lakes environment. Differences in congener profiles between the two cohorts cannot be attributed to different Aroclor mixtures.
3. Methods: congener analysis Serum samples from the LaSalle study were sent to the US Centers for disease control and prevention (CDC) in Atlanta for analysis. A capillary gas chromatographic method provided concentration levels for 38 individual PCB congeners (28, 52, 60, 66, 74, 99, 101, 105, 110, 118, 130, 137, 138, 146, 149, 153, 156, 157, 167, 170, 171, 172, 177, 178, 180, 183, 187, 189, 191, 193, 194, 195, 201, 203, 205, 206, 208 and 209). Serum pools made from bovine serum, which contained in vivo PCBs as Aroclor 1242 or Aroclor 1260 derived from goats fed these technical materials, were used as quality control materials (Burse et al., 1990; Burse et al., 2000; Korrick et al., 2000). These pools were characterized through repetitive analysis (n = 20) for individual congeners setting mean, 95%, and 99% control limits. Pools analyzed with unknown samples had to meet quality control limits before data were reported. Samples from the fish eaters study were analyzed for PCB congeners at the Wisconsin State Laboratory of Hygiene (Madison, Wis.) and the Michigan Department of Community Health (Lansing, Mich.). The PCB congeners were represented by 62 peaks using capillary column gas chromatography with electron capture detection. Prior to laboratory analysis, both laboratories participated in a quality assurance/laboratory standardization protocol. Each laboratory had to process two standards of both high- and low-level concentration. Analysis of the subject’s samples did not begin until the results of both standards were comparable between both laboratories. The percent recovery of 89 congeners represented by 62 chromatographic peaks ranged from 68% to 104%. The percent duplication for the most common congeners (118; 132/153/ 105; 138/163; 182/187; 180; and 170/190) ranged from 2% to 13%. Co-elution occurred between congener groups 138 and 163; 132, 153, and 105; 182 and 187; and 170 and 190. Relevant to this analysis are the first two groups, so that 138 and 163 could not be differentiated and 132, 153, and 105 could not be differentiated. It is assumed that 138/163 consists mostly of 138 and that 132/153/105 consists mostly of 153. In both cohorts, values below the limit of detection were assumed to be zero. Limits of quantification were not utilized in assigning or imputing values. We used the IUPAC numbering system (ATSDR, 1993) to represent structures of chlorine substitutions. The following are the structures for the congeners of focus in our results: #74 (2,4,4 0 ,5); #138 (2,2 0 ,3,4,4 0 ,5); #153 (2,2 0 ,
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4,4 0 ,5,5 0 ); #180 (2,2 0 ,3,4,4 0 ,5,5 0 ); and #201 (2,2 0 3,3 0 , 4,5 0 ,6,6 0 ). Serum samples from both cohorts were analyzed using capillary column gas chromatography and both used adequate quality control measures. There is no evidence of systematic differences between the cohorts due to differences between methods of congener detection. 4. Methods: statistical analysis Congener profiles were compared between the two cohorts using multiple logistic regression with an indicator for the capacitor plant workers versus the fish eaters as the dependent variable and proportion of the total PCBs accounted for by each congener as independent variables. Forward and backward selection procedures were used to select the best subset of congeners from all of those that accounted for 5% or more of total PCBs, on average, in either cohort. Once this subset of congeners was identified, a model was chosen based on relative proportions amongst only the selected congeners. Within the total of k congeners, each subject has a set of k proportions that are not independent because they must sum to unity. A regression model with no intercept and k parameters for the effect of each of the k proportions is equivalent to a model with an intercept and a parameter for each of k 1 out of k proportions, and does not require the arbitrary choice of a reference group. Therefore, models with all k proportions and no intercept were considered. Likelihood ratio tests were used to compare nested models and find the most efficient grouping of the selected congeners. Effects of age, gender, body mass index (BMI), the total of all 14 congeners and the total of the subset of selected congeners also were considered as additional independent variables in the final model. The predicted log-odds from the selected model are continuous scores reflecting estimated likelihood of occupational exposure as opposed to exposure through consumption of fish. These scores were examined separately within each cohort for association with amount of exposure. If the scores reflect a continuum of type of PCB exposure, from the highest level of occupational exposure at one extreme to the highest level of exposure through fish eating at the other extreme, we would expect to see scores positively correlated with amount of exposure in the capacitor plant workers and negatively correlated with amount of exposure in the fish eaters. Amount of exposure was measured as total quarters worked at the plant for the capacitor plant workers and as number of years eating sportcaught Great Lakes fish for the fish eaters. 5. Results Fourteen congeners were measured in both cohorts; 52, 74, 99, 101, 118, 138, 146, 153, 177, 178, 180, 183, 194 and 201. These 14 congeners account for an average of 80.7% of total PCBs in the fish eaters cohort, and 78.4% of total
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Table 1 Characteristics of the two study cohorts Capacitor plant workers: (n = 180)
Fish eaters: (n = 217)
Age: mean ± SD
59.2 ± 12.8 (n = 179)
49.1 ± 8.7 (n = 215)
BMI: mean ± SD
29.5 ± 6.8 (n = 179)
27.3 ± 4.4 (n = 214)
34.1% (61/179)
72.3% (157/217)
Total PCBs (ppb): Mean ± SD Minimum Maximum
7.39 ± 10.33 0.26 92.33
5.03 ± 4.27 0.52 22.86
Exposure history: Mean ± SD Minimum Maximum
Quarters worked 33.5 ± 33.7 1 145
Years eating GLSCFb 26.9 ± 14.6 1 88
Percent male (n/N) a
a Total PCBs = sum of 14 congeners measured in both cohorts (52, 74, 99, 101,118, 138, 146, 153, 177, 178, 180, 183, 194, and 201). PCBs were measured as ppb on a fresh weight basis. b GLSCF = Great Lakes sport-caught fish.
PCBs in the capacitor plant workers cohort. Total PCBs across the 14 congeners is higher in capacitor plant workers than in fish eaters (Table 1); the mean and the variance are both significantly higher in the capacitor plant workers (t = 2.72, p = .0070 and F = 5.81, p < .0001, respectively). The cohort of capacitor plant workers tends to be older (t = 8.97, p < .0001), have higher BMI (t = 3.85, p = .0001), and has fewer males (chi-square = 58.1, p < .0001) than the cohort of fish eaters. Table 2 shows mean proportions of the total PCB level for each congener in each of the two cohorts. The most striking difference between cohorts is a much higher proportion for congener 74 in the capacitor plant workers; also apparent are lower proportions of 138, 153 and 180 in the capacitor plant workers, which may simply be a result of higher levels of 74. Congeners which accounted for an average of 5% or more of total PCBs across all 14 congeners in either group were selected for analysis – these were 74, 99, 118, 138, 153, 180 and 201. Both forward and backward selection procedures chose five of the seven congeners (74, 138, 153, 180 and 201) as the best set of independent variables predicting capacitor plant workers versus fish eaters. Models based on proportions within the total across the five selected congeners were then examined. Table 3 shows summary statistics for models grouping the five congeners in various ways. Model 1 is selected as the most efficient, based on three proportions across the five congeners – 74 alone, 138 + 180, and 153 + 201. The model using five parameters to estimate a unique coefficient for each of the five congener proportions (Model 2) is not a significant improvement in fit; combining congener 74 with 153 and 201 (Model 3) results in a significantly worse fit. The estimated probabilities of being a capacitor plant worker versus a fish eater are remarkably consistent with actual cohort membership. Using an estimated probability of 0.5 to define the cutpoint for a classification criteria, 99.5% of the sample (395/397) is correctly classified; all
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Table 2 Proportions of Total PCBsa for 14 congeners Congener
Capacitor plant workers: (n = 180)
52 74 99 101 118 138 146 153 177 178 180 183 194 201 a
Fish eaters: (n = 217)
Mean
SD
Minimum
Maximum
Mean
SD
Minimum
Maximum
0.001 0.33 0.06 0.001 0.09 0.16 0.02 0.19 0.002 0.003 0.10 0.01 0.02 0.03
0.005 0.19 0.03 0.003 0.055 0.06 0.03 0.07 0.003 0.02 0.06 0.01 0.02 0.03
0 0 0 0 0 0.03 0 0 0 0 0.003 0 0 0
0.05 0.87 0.19 0.03 0.28 0.35 0.34 0.40 0.02 0.19 0.33 0.05 0.15 0.22
0 0.04 0.03 0.003 0.07 0.29 0.02 0.24 0.004 0.004 0.22 0.01 0.03 0.05
0 0.03 0.03 0.02 0.05 0.06 0.02 0.06 0.01 0.01 0.06 0.01 0.02 0.04
0 0 0 0 0 0 0 0.15 0 0 0.12 0 0 0
0 0.12 0.12 0.15 0.23 0.47 0.07 0.43 0.03 0.04 0.61 0.04 0.08 0.15
Total PCBs = sum of 14 congeners measured in both cohorts (52, 74, 99, 101, 118, 138, 146, 153, 177, 178, 180, 183, 194, and 201).
Table 3 Logistic multiple regression modelsa predicting capacitor plant workers (n = 180) versus fish eaters (n = 217) as a function of congener proportions Proportionb for congener(s)
Estimated coefficient
2 log(L)
Comparison to Model 1
Model 1
74 138 + 180 153 + 201
+36.2 77.9 +96.3
28.4
–
Model 2
74 138 153 180 201
+33.4 81.1 +108.2 85.2 +85.1
25.6
X2 = 2.8 v22
74 + 153 + 201 138 + 180
+45.5 42.4
40.0
Model 3
Table 4 Predicted log-odds of being a capacitor plant workers versus a fish eater Predicted log-odds = +36.2{74/subtotala} 77.9{(138 + 180)/ subtotala} + 96.3{(153 + 201)/subtotala}
Mean ± SD Minimum Maximum Less than zero a
X2 = 14.4 v21
a Each model, based on k proportions which must sum to unity, includes a parameter for all k proportions and no intercept. b Proportion out of the sum of congeners 74, 138, 153, 180, and 201.
of the 217 fish eaters have predicted probabilities less than 0.5, and 178 of the 180 capacitor plant workers have estimated probabilities greater than 0.5. The estimated logodds of being a capacitor plant worker, or the linear part of the regression model, can be interpreted as a score reflecting type of exposure (Table 4). A predicted log-odds of zero corresponds to a predicted probability of 0.5; positive scores suggest occupational exposure and negative scores suggest exposure through fish consumption. Correlations of the score with amount of exposure within each type of exposure are shown in Fig. 1. The scores are significantly positively correlated with number of quarters worked in the capacitor plant workers (r = +.37, p < .0001). In the fish eaters, however, there is no apparent association between the estimated score and number of years eating GLSCF (r = +.05, p = .4722) or number of fish eaten per year (r = .04, p = .5115). The estimated score seems to work better as a measure of occupational
Capacitor plant workers: (n = 180)
Fish eaters: (n = 217)
+15.9 ± 8.5 6.0 +41.7 1.1% (2/180)
12.9 ± 7.1 32.8 0.5 100% (217/217)
Subtotal = 74 + 138 + 153 + 180 + 201.
exposure than a measure of exposure through fish consumption. Also apparent in Fig. 1 is the clear separation between groups; all except two capacitor plant workers have a positive score, and all fish eaters have a negative score. Other variables known to differ between the two cohorts were explored as possible confounders. The effect of total PCBs across the 14 congeners as an additional independent variable in the model is not significant, and adjustment for total PCBs does not substantially alter estimated effects of the five congener proportions. The same is true using the subtotal across the five congeners used in the model. In the slightly smaller sample with age, gender and BMI measurements available (179 capacitor plant workers and 212 fish eaters), the addition of the three variables did not significantly improve the model and did not substantially alter the original estimated effects. In addition to consideration of congener proportions, multiple logistic models were examined using the congener levels. Since original levels of congeners 138 and 153 were too highly correlated for their independent effects to be estimated, models were considered using 138 without 153, 153 without 138, and the sum of the two. Levels were analyzed as the original values, as natural logarithms of the original values, and as the ranks of the original values.
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Log-odds = +36.2{ 74/Subtotal* } – 77.9{ (138+180)/Subtotal* }+ 96.3{ (153+201)/Subtotal* } Capacitor Plant Workers (N=180)
Fisheaters (N=217)
Quarters Worked
Years Eating GLSC Fish r = +.049 (p=.4722)
r = +.371 (p<.0001) *Subtotal = 74 + 138 + 153 + 180 + 201.
Fig. 1. Predicted log-odds of occupational exposure by amount of exposure.
All three approaches led to a model with five congeners – 74, 118, 153, 180, and 201, with positive coefficients for 74, 153, and 201 and negative coefficients for 118 and 180. The best of these models, using the original values, did not perform as well as our model using congener proportions. A model was fit using the ranks for the proportions rather than the original values in order to assess the robustness of the model. Results are similar, with a negative intercept estimate and highly significant positive coefficients for proportions of 74 and proportions of 153 + 201. The model based on ranks also classifies the two groups fairly well (375/397 or 94.4%), though not as well as the model based on the original proportions. The predicted log-odds of being a capacitor plant worker is essentially a weighted comparison between a weighted sum of proportions for congeners with positive coefficients (74, 153 and 201) and the sum of proportions for congeners with negative coefficients (138 and 180), where the weights are determined by the estimated regression coefficients. Logistic regression has provided a tool for identifying the optimal weights to best differentiate the two groups. If congeners with positive coefficients and congeners with negative coefficients are weighted equally, the comparison amounts to whether or not the proportion of 74 + 153 + 201 out of 74 + 138 + 153 + 180 + 201 is greater than 0.5. Table 5 shows summary statistics across both cohorts for proportion of the total across the five selected congeners consisting of 74, 153 or 201. This proportion can correctly classify a substantial proportion of the sample, although not as well as the weighted score from the logistic regression model. All of the 217 fish eaters have a higher amount of 138 and 180 combined than 74, 153, and 201 combined, or a proportion less than 0.5 in Table 5; 95% of the 180 capacitor plant workers (172/180) have a higher amount of 74, 153 and 201 combined than
Table 5 Proportions of the sum of congeners 74, 138, 153, 180, and 201 consisting of 74, 153, and 201
Mean ± SD Minimum Maximum Less than 0.5
Capacitor plant workers: (n = 180)
Fish eaters: (n = 217)
0.68 ± 0.12 0.42 0.95 4.4% (8/180)
0.39 ± 0.05 0.26 0.49 100% (217/217)
138 and 180 combined, or a proportion greater than 0.5 in Table 5. Patterns in combinations of congener proportions are driven by relationships amongst the proportions. Scatterplots and correlations for pairs of congener proportions are shown in Fig. 2 for capacitor plant workers and Fig. 3 for fish eaters. In capacitor plant workers, there is a strong negative correlation between 74 and all other congeners. This could be due to 74 coming from a unique source, which would result in no association between levels of 74 and other congeners (DeVoto et al., 1997) and a negative association between proportions, as an increase in 74 necessarily decreases proportions of other congeners. Another possibility is that other congeners are dechlorinating into 74 (Kinney et al., 1997); one congener transforming into another would create a negative association between the two levels and the two proportions. The other four congeners besides 74 are positively correlated with one another, especially 138 and 153. Also apparent from the scatterplot for 138 and 153 is a tendency for higher amounts of 153 than 138, or points below the diagonal. In the fish eaters, proportions of 74 are much lower, including many zeroes, and are negatively correlated with 153 and 180. There is no association between 138 and 153, and a tendency towards higher levels of 138 than 153, or points above the diagonal. Congeners 138 and 180 are
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#74 r = -.82 (p=<.0001)
r = -.95 (p<.0001)
r = -.80 (p<.0001)
r = -.51 (p=<.0001)
r = +.85 (p<.0001)
r = +.38 (p<.0001)
r = +.04 (p=.6059)
#138
#153 r = +.62 (p<.0001)
r = +.31 (p<.0001)
#180 r = +.67 (p<.0001)
#201 Fig. 2. Pairwise relationships between PCB congener proportions in capacitor plant workers (n = 180).
#74 r = +.06 (p=.3538)
r = -.55 (p<.0001)
r = -.47 (p<.0001)
r = +.11 (p=.1208)
r = -.68 (p<.0001)
r = -.47 (p<.0001)
r = +.14 (p=.0353)
r = -.51 (p<.0001)
#138 r = -.07 (p=.3210)
#153
#180 r = -.03 (p=.6775)
#201 Fig. 3. Pairwise relationships between PCB congener proportions in fish eaters (n = 217).
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negatively associated in fish eaters, but positively associated in capacitor plant workers. 6. Discussion Our results suggest that relative proportions of PCB congeners may be better predictors of source of exposure than absolute levels of PCBs. If capacitor plant workers simply had higher levels of all congeners than fish eaters with similar distributions across congeners, one would expect proportions of total for specific congeners to be similar between the two cohorts. Instead, analysis of five of the most prevalent congeners reveals distinct patterns of proportions in the two cohorts. Adjusting for the pattern of congener proportions, the overall total amount does not further differentiate the two cohorts. Similarly age, gender and BMI do not additionally discriminate the two cohorts adjusted for the pattern of congener proportions, in spite of clear differences in these variables between the two cohorts. The pattern revealed in the logistic multiple regression analysis, or in examination of relative levels between 74 + 153 + 201 and 138 + 180, is not apparent from the marginal summary statistics for each congener alone, which are shown in Table 2. Higher proportions for congener 74 and lower proportions for congeners 138 and 180 in the capacitor plant workers are consistent with marginal means shown in Table 2. The marginal mean proportions for congeners 153 and 201, however, are both higher in the fish eaters, while in the multiple logistic model, higher proportions for congeners 153 and 201 count towards predicting capacitor plant workers. The mean tendency towards more of 74 + 153 + 201 than 138 + 180 in capacitor plant workers and less of 74 + 153 + 201 than 138 + 180 in fish eaters could be derived from Table 2 (proportion for 74 + 153 + 201 and 138 + 180, respectively, are .33 + .19 + .03 = .55 and .16 + .10 = .26 in capacitor plant workers; .04 + .24 + .05 = .33 and .29 + .22 = .51 in fish eaters). The information presented in Table 2, however, does not provide information on the variation around the mean in the difference between combined proportions. In this case, the observed distributions in the two groups are well separated, with an overlap of only eight individuals. The National Health and Nutrition Examination (NHANES) provides levels of PCB congeners at the individual level for a random sample of the US population, so the distribution of relative proportions of congeners can be examined and compared to the two exposed samples analyzed here. Data from the NHANES survey cycle conducted in 2001–2002 were obtained from the publicly accessible internet site (CDC, 2006). Data are anonymous and were collected following human subjects research guidelines. Observations were excluded if they were outside the range of age (24–86) or BMI (17–58) observed in the two study samples pooled, and estimates are weighted to represent the US population. Congener levels below limits of detection are estimated to zero for consistency with the study samples. The mean sum of the 14 congeners
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described in Table 1 is 1.5 ppb in the NHANES sample, considerably lower than the capacitor plant workers (7.4) or the fish eaters (5.0). Fig. 4 shows the distributions of the proportion of total congener levels across congeners 74, 138, 153, 180, and 201 consisting of 74, 153, and 201, for both exposed study samples and for the NHANES sample. The distribution in the NHANES sample overlaps the distinct distributions in the two exposed samples, suggesting perhaps a mixture of exposures in the population. Results from other studies reporting specific congeners typically provide summary statistics for the marginal distribution of each congener, comparable to Table 2. Generally, the very highly chlorinated congener 201 appears in small amounts or is not mentioned. Congener 74 has been identified as a marker of occupational exposure (Wolff et al., 1982; Luotamo et al., 1991). It has been shown that congener 153 is especially persistent (Braunberg et al., 1976; Fait et al., 1989; Kinney et al., 1997), and that
Fig. 4. Distributions of proportion of the sum of congeners 74, 138, 153, 180, and 201 consisting of 74, 153, and 201. *NHANES weighted population sample from 2001–2002 selected with age 24–86 and BMI 17– 58.
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generally higher chlorinated congeners are slower to be metabolized and eliminated than lower chlorinated congeners (Phillips et al., 1989; Garner and Matthews, 1998). The persistence of 74, a lower chlorinated congener, is an exception. Wolff et al. (1992), in a study looking at changes across a three-year period in capacitor manufacture workers, reports an increase in levels of 74 and 153 and a decrease in levels of 138 and 180. This pattern would suggest that the ratio of 74 + 153 to 138 + 180 will increase across time in persons with occupational exposure. Wolff suggests the particular configuration of congener 74 makes the molecule resistant to metabolism; and also congener 74 may be a result of dechlorination of higher chlorinated congeners. A few studies have directly addressed correlations between congeners in addition to describing marginal distributions. High correlations found between 138 and 153 render separation of the two difficult (Luotamo et al., 1991; DeVoto et al., 1997). DeVoto et al. (1997) suggest exploring the use of ratios between congener levels, using a similar rationale to methods of analyzing macronutrient effects in nutritional epidemiology (Wacholder et al., 1994). Our findings suggest ratios between congeners, in our case 74 + 153 + 201 and 138 + 180, may be key in tracking the route of exposure. It is possible ratios between congeners also relate to different effects on health outcomes. Other approaches to the problem of comparing congener patterns, while accounting for correlations between congeners include fingerprinting methods which are based on weighted Euclidean distance between individual profiles and standard profiles derived from the original Aroclor mixtures (Dunn et al., 1984) or from samples of contaminated food (Hwang et al., 2001). How to apply the same methodology to a comparison between two groups of profiles, without reference to a standard profile, presents an interesting methodology problem for future research. Another approach is the application of factor analysis to identify subgroups based on congener patterns and their relative contributions to total PCBs (DeCaprio et al., 2005). This method is not appropriate for our problem where subgroups are already identified, but may provide an interesting validation analysis for future research. Multivariate regression modeling has been used to simultaneously predict a set of congener levels as dependent variables given a set of independent variables (Schaeffer et al., 2006). A limitation of our study is the confounding factor of time since exposure. For the fish eaters cohort, there was a considerable time lag between the PCBs in their original form and the exposure due to their bioaccumulation in fish, followed by a short time lag between that exposure and the measurement used in this analysis. All members of the fish eaters cohort had eaten sport-caught Great Lakes fish during the past year before their serum was taken. For the capacitor plant workers, however, occupational exposure ended in 1978, or earlier if a worker terminated employ-
ment before 1978, creating a time lag of at least 22 years between exposure and measurement before serum was taken in 1996. The differences in congener composition between the two cohorts might be affected by changes in which congeners remain in the body across time in addition to the difference in route of exposure. Another limitation of our study is the fact that only 14 congeners were measured in both cohorts. As stated earlier, these 14 congeners account for 80.7% of the total across all 62 congeners measured in the fish eaters cohort and 78.4% of the total across all 38 congeners measured in the capacitor plant workers cohort. We may be missing important elements of congener patterns due to other congeners that we are not able to analyze in these studies. In summary, our results suggest relative proportions of different congeners are key in tracking route of exposure. Different routes of exposure do not appear to be related to the total of all 14 congeners after relative proportions are taken into account. While total PCBs may be related to health outcomes, we suggest relative proportions of different congeners within the total also be taken into consideration when analyzing effects of PCB exposure on health outcomes. Acknowledgements This research was funded by the Agency for Toxic Substances and Disease Registry, cooperative agreement number U50/ATU502923 (capacitor plant workers study) and Grant number H75/ATH598322 (fish eaters study). We thank Daniel Hryhorczuk for his assistance with the collaboration, and we thank Susan Schantz and Mary Wolff for their valuable input. The protocol for the fish eaters study was reviewed and approved by the University of Wisconsin-Madison Medical School Human Subjects Committee and University of Illinois-Chicago Internal Review Boards; the protocol for the capacitor plant workers study was reviewed and approved by the University of IllinoisChicago Internal Review Board. References Agency for Toxic Substances and Disease Registry (ATSDR), 1993. Toxicological Profile for Polychlorinated Biphenyls. US Department of Health and Human Services, Public Health Service, Atlanta. Anderson, H., Falk, C., Fiore, B., Hanrahan, L.P., Humphrey, H.E.B., Kanarek, M., et al., 1996. Consortium for the health assessment of Great Lakes sport fish consumption. Toxicol. Ind. Health 12, 369–373. Braunberg, R.C., Dailey, R.E., Brouwer, E.A., Dasza, L., Blaschka, A.M., 1976. Acute, subacute, and residual effects of polychlorinated biphenyl (PCB) in rats. I. Biologic half-life in adipose tissue. J. Toxicol. Environ. Health 1, 683–688. Brown, D.P., Jones, M., 1981. Mortality and industrial hygiene study of workers exposed to polychlorinated biphenyls. Arch. Environ. Health 36 (3), 120–129. Burse, V.W., Groce, D.F., Korver, M.P., McClure, P.C., Head, S.L., Needham, L.L., et al., 1990. Use of reference pools to compare the qualitative and quantitative determination of polychlorinated biphenyls by packed and capillary gas chromatography with electron capture detection. Part 1 serum. Analyst 115, 243–251.
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Congener profiles of occupational PCB exposure versus PCB exposure from fish consumption Sally Freels a,*, Lin Kaatz Chary b, Mary Turyk a, Julie Piorkowski a, Katherine Mallin a, John Dimos c, Henry Anderson d, Ken McCann e, Virlyn Burse f, Victoria Persky b a
b
Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, 1603 West Taylor Street Room 953 (M/C 922), Chicago, IL 60612, USA Great Lakes Centers for Occupational and Environmental Safety and Health, School of Public Health, University of Illinois at Chicago, IL, USA c Division of Environmental and Occupational Health Sciences, School of Public Health, University of Illinois at Chicago, IL, USA d Wisconsin Division of Public Health, Bureau of Environmental Health, Madison, WI, USA e Division of Environmental Health, Illinois Department of Public Health, Springfield, IL, USA f Centers for Disease Control and Prevention, Atlanta, GA, USA Received 6 September 2006; received in revised form 10 April 2007; accepted 26 April 2007 Available online 20 June 2007
Abstract The composition of polychlorinated biphenyl (PCB) congeners in serum samples is compared between a cohort previously exposed to PCBs from working at a capacitor plant (n = 180) and a cohort of Great Lakes sport-caught fish eaters (n = 217). Fourteen congeners were measured in both samples. A multiple logistic regression model differentiating the two groups as a function of relative proportions amongst congeners 74, 138, 153, 180, and 201 correctly classifies more than 99% of the people (395/397); higher proportions of congeners 74, 153, and 201 characterize capacitor plant workers, while higher proportions of congeners 138 and 180 characterize fish eaters. The pattern is driven by the relative amounts of 74 + 153 + 201 compared to 138 + 180; all of the fish eaters, but only 5% of the capacitor plant workers, have a greater percent of 138 + 180 than 74 + 153 + 201. Consideration of combinations of congener levels and their relative proportions is relevant to tracking route of exposure and may also be relevant to modeling effects on health outcomes. Ó 2007 Elsevier Ltd. All rights reserved. Keywords: PCBs; Congeners; Occupational exposure; Fish consumption; Logistic regression
1. Introduction Polychlorinated biphenyls, or PCBs, are synthetic chemicals designed to be extremely stable and easily soluble in most organic solvents. PCBs were first introduced to the electrical industry in 1929. Their use in the manufacturing of electrical capacitors and transformers was widespread until 1978, when production and use of PCBs was banned in the US because of concerns about effects of PCB exposure on human health and the environment (ATSDR, 1993). PCBs persist in the environment to the extent that
*
Corresponding author. Tel.: +1 312 996 4763; fax: +1 312 996 0064. E-mail address: [email protected] (S. Freels).
0045-6535/$ - see front matter Ó 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.chemosphere.2007.04.087
all geographic areas contain some background exposure levels (Hansen, 1987; UNEP, 1998). Routes of exposure beyond background levels include exposure to a single high dose of PCBs as a result of an accident (Murai et al., 1987; Hsieh et al., 1996; Guo et al., 1997; Osius et al., 1999; Lung et al., 2005; Hsu et al., 2005); exposure by working directly with PCBs, in an occupational setting (Brown and Jones, 1981; Wolff et al., 1982; Phillips et al., 1989; Kimbrough et al., 1998); and exposure through consumption of contaminated food, particularly fish (Maack and Sonzogni, 1988; Fitzgerald et al., 1998; Hanrahan et al., 1999; Turyk et al., 2006). The presence of PCBs in serum has been studied as the total of all detectable congeners, or total PCBs, and in more recent years as levels of specific congeners. Capacitor
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plant workers were exposed directly to the original Aroclor mixtures via dermal exposure and/or inhalation and ingestion (Jones, 1977; NIOSH, 1977a,b; Lees et al., 1987). PCBs released into the environment make their way to rivers and lakes and concentrate in the fat tissue of fish (James, 2001). Due to the transformation of PCBs as they move through the environment, a different distribution of congeners is expected in individuals exposed to PCBs through fish consumption compared with capacitor plant workers exposed in an occupational setting. This analysis uses data from two different studies to compare the composition of PCB congeners in serum between those with occupational versus fish consumption exposure. One study includes serum samples from a cohort of capacitor plant workers in LaSalle, Illinois, where PCBs were used from 1952 until 1978. The second study includes serum samples from a cohort who were heavy consumers of sport-caught fish from the Great Lakes, where bioaccumulation of PCBs in fish has been well documented. 2. Methods: cohort selection Two cohorts were selected for comparison, one representing occupational exposure and one representing exposure from a common contaminated food source. The LaSalle Electrical Utilities Company (EUC) used PCBs to manufacture electrical capacitors from 1952 until PCBs were banned in 1978. After EUC closed in 1981, it was listed on the National Priorities List for cleanup and became a Superfund site because of PCB contamination. In 1996, as a follow-up to the Superfund remediation, a cross-sectional health effects study was undertaken by the University of Illinois at Chicago School of Public Health under the auspices of the Agency for Toxic Substances and Disease Registry (ATSDR) and the Illinois Department of Public Health. The study sample was assembled from former EUC workers and community residents who had not worked in the plant. The sample for this analysis consisted of 180 people who worked at the EUC in 1952 or later, when PCBs were being used, and who are known, based on survey data, to have been exposed to PCBs at work. A control group of non-workers was excluded to create a group who were all occupationally exposed to PCBs. In 1993, the Consortium for the Health Assessment of Great Lakes Sport Fish Consumption conducted a study on a sample of charter boat captains on Lakes Michigan, Huron, and Erie, and a sample of Wisconsin anglers. Information about fish consumption habits and demographics were obtained from a telephone survey, and serum samples were drawn. A detailed description of the full study protocol has been previously published (Anderson et al., 1996). The sample used here is from a study of hormones performed on a subset of the original sample. Details of the hormone study have been published elsewhere (Persky et al., 2001). The sample for this analysis consists of 217 people who ate Great Lakes sport-caught fish (GLSCF) in the past year before the survey. A group who ate fish
from smaller lakes in the area was excluded to create a group that consumed from the same contaminated food source. All available PCB mixtures, known as Aroclors, were used at the LaSalle utilities plant, and all Aroclors were potentially released into the Great Lakes environment. Differences in congener profiles between the two cohorts cannot be attributed to different Aroclor mixtures.
3. Methods: congener analysis Serum samples from the LaSalle study were sent to the US Centers for disease control and prevention (CDC) in Atlanta for analysis. A capillary gas chromatographic method provided concentration levels for 38 individual PCB congeners (28, 52, 60, 66, 74, 99, 101, 105, 110, 118, 130, 137, 138, 146, 149, 153, 156, 157, 167, 170, 171, 172, 177, 178, 180, 183, 187, 189, 191, 193, 194, 195, 201, 203, 205, 206, 208 and 209). Serum pools made from bovine serum, which contained in vivo PCBs as Aroclor 1242 or Aroclor 1260 derived from goats fed these technical materials, were used as quality control materials (Burse et al., 1990; Burse et al., 2000; Korrick et al., 2000). These pools were characterized through repetitive analysis (n = 20) for individual congeners setting mean, 95%, and 99% control limits. Pools analyzed with unknown samples had to meet quality control limits before data were reported. Samples from the fish eaters study were analyzed for PCB congeners at the Wisconsin State Laboratory of Hygiene (Madison, Wis.) and the Michigan Department of Community Health (Lansing, Mich.). The PCB congeners were represented by 62 peaks using capillary column gas chromatography with electron capture detection. Prior to laboratory analysis, both laboratories participated in a quality assurance/laboratory standardization protocol. Each laboratory had to process two standards of both high- and low-level concentration. Analysis of the subject’s samples did not begin until the results of both standards were comparable between both laboratories. The percent recovery of 89 congeners represented by 62 chromatographic peaks ranged from 68% to 104%. The percent duplication for the most common congeners (118; 132/153/ 105; 138/163; 182/187; 180; and 170/190) ranged from 2% to 13%. Co-elution occurred between congener groups 138 and 163; 132, 153, and 105; 182 and 187; and 170 and 190. Relevant to this analysis are the first two groups, so that 138 and 163 could not be differentiated and 132, 153, and 105 could not be differentiated. It is assumed that 138/163 consists mostly of 138 and that 132/153/105 consists mostly of 153. In both cohorts, values below the limit of detection were assumed to be zero. Limits of quantification were not utilized in assigning or imputing values. We used the IUPAC numbering system (ATSDR, 1993) to represent structures of chlorine substitutions. The following are the structures for the congeners of focus in our results: #74 (2,4,4 0 ,5); #138 (2,2 0 ,3,4,4 0 ,5); #153 (2,2 0 ,
S. Freels et al. / Chemosphere 69 (2007) 435–443
4,4 0 ,5,5 0 ); #180 (2,2 0 ,3,4,4 0 ,5,5 0 ); and #201 (2,2 0 3,3 0 , 4,5 0 ,6,6 0 ). Serum samples from both cohorts were analyzed using capillary column gas chromatography and both used adequate quality control measures. There is no evidence of systematic differences between the cohorts due to differences between methods of congener detection. 4. Methods: statistical analysis Congener profiles were compared between the two cohorts using multiple logistic regression with an indicator for the capacitor plant workers versus the fish eaters as the dependent variable and proportion of the total PCBs accounted for by each congener as independent variables. Forward and backward selection procedures were used to select the best subset of congeners from all of those that accounted for 5% or more of total PCBs, on average, in either cohort. Once this subset of congeners was identified, a model was chosen based on relative proportions amongst only the selected congeners. Within the total of k congeners, each subject has a set of k proportions that are not independent because they must sum to unity. A regression model with no intercept and k parameters for the effect of each of the k proportions is equivalent to a model with an intercept and a parameter for each of k 1 out of k proportions, and does not require the arbitrary choice of a reference group. Therefore, models with all k proportions and no intercept were considered. Likelihood ratio tests were used to compare nested models and find the most efficient grouping of the selected congeners. Effects of age, gender, body mass index (BMI), the total of all 14 congeners and the total of the subset of selected congeners also were considered as additional independent variables in the final model. The predicted log-odds from the selected model are continuous scores reflecting estimated likelihood of occupational exposure as opposed to exposure through consumption of fish. These scores were examined separately within each cohort for association with amount of exposure. If the scores reflect a continuum of type of PCB exposure, from the highest level of occupational exposure at one extreme to the highest level of exposure through fish eating at the other extreme, we would expect to see scores positively correlated with amount of exposure in the capacitor plant workers and negatively correlated with amount of exposure in the fish eaters. Amount of exposure was measured as total quarters worked at the plant for the capacitor plant workers and as number of years eating sportcaught Great Lakes fish for the fish eaters. 5. Results Fourteen congeners were measured in both cohorts; 52, 74, 99, 101, 118, 138, 146, 153, 177, 178, 180, 183, 194 and 201. These 14 congeners account for an average of 80.7% of total PCBs in the fish eaters cohort, and 78.4% of total
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Table 1 Characteristics of the two study cohorts Capacitor plant workers: (n = 180)
Fish eaters: (n = 217)
Age: mean ± SD
59.2 ± 12.8 (n = 179)
49.1 ± 8.7 (n = 215)
BMI: mean ± SD
29.5 ± 6.8 (n = 179)
27.3 ± 4.4 (n = 214)
34.1% (61/179)
72.3% (157/217)
Total PCBs (ppb): Mean ± SD Minimum Maximum
7.39 ± 10.33 0.26 92.33
5.03 ± 4.27 0.52 22.86
Exposure history: Mean ± SD Minimum Maximum
Quarters worked 33.5 ± 33.7 1 145
Years eating GLSCFb 26.9 ± 14.6 1 88
Percent male (n/N) a
a Total PCBs = sum of 14 congeners measured in both cohorts (52, 74, 99, 101,118, 138, 146, 153, 177, 178, 180, 183, 194, and 201). PCBs were measured as ppb on a fresh weight basis. b GLSCF = Great Lakes sport-caught fish.
PCBs in the capacitor plant workers cohort. Total PCBs across the 14 congeners is higher in capacitor plant workers than in fish eaters (Table 1); the mean and the variance are both significantly higher in the capacitor plant workers (t = 2.72, p = .0070 and F = 5.81, p < .0001, respectively). The cohort of capacitor plant workers tends to be older (t = 8.97, p < .0001), have higher BMI (t = 3.85, p = .0001), and has fewer males (chi-square = 58.1, p < .0001) than the cohort of fish eaters. Table 2 shows mean proportions of the total PCB level for each congener in each of the two cohorts. The most striking difference between cohorts is a much higher proportion for congener 74 in the capacitor plant workers; also apparent are lower proportions of 138, 153 and 180 in the capacitor plant workers, which may simply be a result of higher levels of 74. Congeners which accounted for an average of 5% or more of total PCBs across all 14 congeners in either group were selected for analysis – these were 74, 99, 118, 138, 153, 180 and 201. Both forward and backward selection procedures chose five of the seven congeners (74, 138, 153, 180 and 201) as the best set of independent variables predicting capacitor plant workers versus fish eaters. Models based on proportions within the total across the five selected congeners were then examined. Table 3 shows summary statistics for models grouping the five congeners in various ways. Model 1 is selected as the most efficient, based on three proportions across the five congeners – 74 alone, 138 + 180, and 153 + 201. The model using five parameters to estimate a unique coefficient for each of the five congener proportions (Model 2) is not a significant improvement in fit; combining congener 74 with 153 and 201 (Model 3) results in a significantly worse fit. The estimated probabilities of being a capacitor plant worker versus a fish eater are remarkably consistent with actual cohort membership. Using an estimated probability of 0.5 to define the cutpoint for a classification criteria, 99.5% of the sample (395/397) is correctly classified; all
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Table 2 Proportions of Total PCBsa for 14 congeners Congener
Capacitor plant workers: (n = 180)
52 74 99 101 118 138 146 153 177 178 180 183 194 201 a
Fish eaters: (n = 217)
Mean
SD
Minimum
Maximum
Mean
SD
Minimum
Maximum
0.001 0.33 0.06 0.001 0.09 0.16 0.02 0.19 0.002 0.003 0.10 0.01 0.02 0.03
0.005 0.19 0.03 0.003 0.055 0.06 0.03 0.07 0.003 0.02 0.06 0.01 0.02 0.03
0 0 0 0 0 0.03 0 0 0 0 0.003 0 0 0
0.05 0.87 0.19 0.03 0.28 0.35 0.34 0.40 0.02 0.19 0.33 0.05 0.15 0.22
0 0.04 0.03 0.003 0.07 0.29 0.02 0.24 0.004 0.004 0.22 0.01 0.03 0.05
0 0.03 0.03 0.02 0.05 0.06 0.02 0.06 0.01 0.01 0.06 0.01 0.02 0.04
0 0 0 0 0 0 0 0.15 0 0 0.12 0 0 0
0 0.12 0.12 0.15 0.23 0.47 0.07 0.43 0.03 0.04 0.61 0.04 0.08 0.15
Total PCBs = sum of 14 congeners measured in both cohorts (52, 74, 99, 101, 118, 138, 146, 153, 177, 178, 180, 183, 194, and 201).
Table 3 Logistic multiple regression modelsa predicting capacitor plant workers (n = 180) versus fish eaters (n = 217) as a function of congener proportions Proportionb for congener(s)
Estimated coefficient
2 log(L)
Comparison to Model 1
Model 1
74 138 + 180 153 + 201
+36.2 77.9 +96.3
28.4
–
Model 2
74 138 153 180 201
+33.4 81.1 +108.2 85.2 +85.1
25.6
X2 = 2.8 v22
74 + 153 + 201 138 + 180
+45.5 42.4
40.0
Model 3
Table 4 Predicted log-odds of being a capacitor plant workers versus a fish eater Predicted log-odds = +36.2{74/subtotala} 77.9{(138 + 180)/ subtotala} + 96.3{(153 + 201)/subtotala}
Mean ± SD Minimum Maximum Less than zero a
X2 = 14.4 v21
a Each model, based on k proportions which must sum to unity, includes a parameter for all k proportions and no intercept. b Proportion out of the sum of congeners 74, 138, 153, 180, and 201.
of the 217 fish eaters have predicted probabilities less than 0.5, and 178 of the 180 capacitor plant workers have estimated probabilities greater than 0.5. The estimated logodds of being a capacitor plant worker, or the linear part of the regression model, can be interpreted as a score reflecting type of exposure (Table 4). A predicted log-odds of zero corresponds to a predicted probability of 0.5; positive scores suggest occupational exposure and negative scores suggest exposure through fish consumption. Correlations of the score with amount of exposure within each type of exposure are shown in Fig. 1. The scores are significantly positively correlated with number of quarters worked in the capacitor plant workers (r = +.37, p < .0001). In the fish eaters, however, there is no apparent association between the estimated score and number of years eating GLSCF (r = +.05, p = .4722) or number of fish eaten per year (r = .04, p = .5115). The estimated score seems to work better as a measure of occupational
Capacitor plant workers: (n = 180)
Fish eaters: (n = 217)
+15.9 ± 8.5 6.0 +41.7 1.1% (2/180)
12.9 ± 7.1 32.8 0.5 100% (217/217)
Subtotal = 74 + 138 + 153 + 180 + 201.
exposure than a measure of exposure through fish consumption. Also apparent in Fig. 1 is the clear separation between groups; all except two capacitor plant workers have a positive score, and all fish eaters have a negative score. Other variables known to differ between the two cohorts were explored as possible confounders. The effect of total PCBs across the 14 congeners as an additional independent variable in the model is not significant, and adjustment for total PCBs does not substantially alter estimated effects of the five congener proportions. The same is true using the subtotal across the five congeners used in the model. In the slightly smaller sample with age, gender and BMI measurements available (179 capacitor plant workers and 212 fish eaters), the addition of the three variables did not significantly improve the model and did not substantially alter the original estimated effects. In addition to consideration of congener proportions, multiple logistic models were examined using the congener levels. Since original levels of congeners 138 and 153 were too highly correlated for their independent effects to be estimated, models were considered using 138 without 153, 153 without 138, and the sum of the two. Levels were analyzed as the original values, as natural logarithms of the original values, and as the ranks of the original values.
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Log-odds = +36.2{ 74/Subtotal* } – 77.9{ (138+180)/Subtotal* }+ 96.3{ (153+201)/Subtotal* } Capacitor Plant Workers (N=180)
Fisheaters (N=217)
Quarters Worked
Years Eating GLSC Fish r = +.049 (p=.4722)
r = +.371 (p<.0001) *Subtotal = 74 + 138 + 153 + 180 + 201.
Fig. 1. Predicted log-odds of occupational exposure by amount of exposure.
All three approaches led to a model with five congeners – 74, 118, 153, 180, and 201, with positive coefficients for 74, 153, and 201 and negative coefficients for 118 and 180. The best of these models, using the original values, did not perform as well as our model using congener proportions. A model was fit using the ranks for the proportions rather than the original values in order to assess the robustness of the model. Results are similar, with a negative intercept estimate and highly significant positive coefficients for proportions of 74 and proportions of 153 + 201. The model based on ranks also classifies the two groups fairly well (375/397 or 94.4%), though not as well as the model based on the original proportions. The predicted log-odds of being a capacitor plant worker is essentially a weighted comparison between a weighted sum of proportions for congeners with positive coefficients (74, 153 and 201) and the sum of proportions for congeners with negative coefficients (138 and 180), where the weights are determined by the estimated regression coefficients. Logistic regression has provided a tool for identifying the optimal weights to best differentiate the two groups. If congeners with positive coefficients and congeners with negative coefficients are weighted equally, the comparison amounts to whether or not the proportion of 74 + 153 + 201 out of 74 + 138 + 153 + 180 + 201 is greater than 0.5. Table 5 shows summary statistics across both cohorts for proportion of the total across the five selected congeners consisting of 74, 153 or 201. This proportion can correctly classify a substantial proportion of the sample, although not as well as the weighted score from the logistic regression model. All of the 217 fish eaters have a higher amount of 138 and 180 combined than 74, 153, and 201 combined, or a proportion less than 0.5 in Table 5; 95% of the 180 capacitor plant workers (172/180) have a higher amount of 74, 153 and 201 combined than
Table 5 Proportions of the sum of congeners 74, 138, 153, 180, and 201 consisting of 74, 153, and 201
Mean ± SD Minimum Maximum Less than 0.5
Capacitor plant workers: (n = 180)
Fish eaters: (n = 217)
0.68 ± 0.12 0.42 0.95 4.4% (8/180)
0.39 ± 0.05 0.26 0.49 100% (217/217)
138 and 180 combined, or a proportion greater than 0.5 in Table 5. Patterns in combinations of congener proportions are driven by relationships amongst the proportions. Scatterplots and correlations for pairs of congener proportions are shown in Fig. 2 for capacitor plant workers and Fig. 3 for fish eaters. In capacitor plant workers, there is a strong negative correlation between 74 and all other congeners. This could be due to 74 coming from a unique source, which would result in no association between levels of 74 and other congeners (DeVoto et al., 1997) and a negative association between proportions, as an increase in 74 necessarily decreases proportions of other congeners. Another possibility is that other congeners are dechlorinating into 74 (Kinney et al., 1997); one congener transforming into another would create a negative association between the two levels and the two proportions. The other four congeners besides 74 are positively correlated with one another, especially 138 and 153. Also apparent from the scatterplot for 138 and 153 is a tendency for higher amounts of 153 than 138, or points below the diagonal. In the fish eaters, proportions of 74 are much lower, including many zeroes, and are negatively correlated with 153 and 180. There is no association between 138 and 153, and a tendency towards higher levels of 138 than 153, or points above the diagonal. Congeners 138 and 180 are
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#74 r = -.82 (p=<.0001)
r = -.95 (p<.0001)
r = -.80 (p<.0001)
r = -.51 (p=<.0001)
r = +.85 (p<.0001)
r = +.38 (p<.0001)
r = +.04 (p=.6059)
#138
#153 r = +.62 (p<.0001)
r = +.31 (p<.0001)
#180 r = +.67 (p<.0001)
#201 Fig. 2. Pairwise relationships between PCB congener proportions in capacitor plant workers (n = 180).
#74 r = +.06 (p=.3538)
r = -.55 (p<.0001)
r = -.47 (p<.0001)
r = +.11 (p=.1208)
r = -.68 (p<.0001)
r = -.47 (p<.0001)
r = +.14 (p=.0353)
r = -.51 (p<.0001)
#138 r = -.07 (p=.3210)
#153
#180 r = -.03 (p=.6775)
#201 Fig. 3. Pairwise relationships between PCB congener proportions in fish eaters (n = 217).
S. Freels et al. / Chemosphere 69 (2007) 435–443
negatively associated in fish eaters, but positively associated in capacitor plant workers. 6. Discussion Our results suggest that relative proportions of PCB congeners may be better predictors of source of exposure than absolute levels of PCBs. If capacitor plant workers simply had higher levels of all congeners than fish eaters with similar distributions across congeners, one would expect proportions of total for specific congeners to be similar between the two cohorts. Instead, analysis of five of the most prevalent congeners reveals distinct patterns of proportions in the two cohorts. Adjusting for the pattern of congener proportions, the overall total amount does not further differentiate the two cohorts. Similarly age, gender and BMI do not additionally discriminate the two cohorts adjusted for the pattern of congener proportions, in spite of clear differences in these variables between the two cohorts. The pattern revealed in the logistic multiple regression analysis, or in examination of relative levels between 74 + 153 + 201 and 138 + 180, is not apparent from the marginal summary statistics for each congener alone, which are shown in Table 2. Higher proportions for congener 74 and lower proportions for congeners 138 and 180 in the capacitor plant workers are consistent with marginal means shown in Table 2. The marginal mean proportions for congeners 153 and 201, however, are both higher in the fish eaters, while in the multiple logistic model, higher proportions for congeners 153 and 201 count towards predicting capacitor plant workers. The mean tendency towards more of 74 + 153 + 201 than 138 + 180 in capacitor plant workers and less of 74 + 153 + 201 than 138 + 180 in fish eaters could be derived from Table 2 (proportion for 74 + 153 + 201 and 138 + 180, respectively, are .33 + .19 + .03 = .55 and .16 + .10 = .26 in capacitor plant workers; .04 + .24 + .05 = .33 and .29 + .22 = .51 in fish eaters). The information presented in Table 2, however, does not provide information on the variation around the mean in the difference between combined proportions. In this case, the observed distributions in the two groups are well separated, with an overlap of only eight individuals. The National Health and Nutrition Examination (NHANES) provides levels of PCB congeners at the individual level for a random sample of the US population, so the distribution of relative proportions of congeners can be examined and compared to the two exposed samples analyzed here. Data from the NHANES survey cycle conducted in 2001–2002 were obtained from the publicly accessible internet site (CDC, 2006). Data are anonymous and were collected following human subjects research guidelines. Observations were excluded if they were outside the range of age (24–86) or BMI (17–58) observed in the two study samples pooled, and estimates are weighted to represent the US population. Congener levels below limits of detection are estimated to zero for consistency with the study samples. The mean sum of the 14 congeners
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described in Table 1 is 1.5 ppb in the NHANES sample, considerably lower than the capacitor plant workers (7.4) or the fish eaters (5.0). Fig. 4 shows the distributions of the proportion of total congener levels across congeners 74, 138, 153, 180, and 201 consisting of 74, 153, and 201, for both exposed study samples and for the NHANES sample. The distribution in the NHANES sample overlaps the distinct distributions in the two exposed samples, suggesting perhaps a mixture of exposures in the population. Results from other studies reporting specific congeners typically provide summary statistics for the marginal distribution of each congener, comparable to Table 2. Generally, the very highly chlorinated congener 201 appears in small amounts or is not mentioned. Congener 74 has been identified as a marker of occupational exposure (Wolff et al., 1982; Luotamo et al., 1991). It has been shown that congener 153 is especially persistent (Braunberg et al., 1976; Fait et al., 1989; Kinney et al., 1997), and that
Fig. 4. Distributions of proportion of the sum of congeners 74, 138, 153, 180, and 201 consisting of 74, 153, and 201. *NHANES weighted population sample from 2001–2002 selected with age 24–86 and BMI 17– 58.
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generally higher chlorinated congeners are slower to be metabolized and eliminated than lower chlorinated congeners (Phillips et al., 1989; Garner and Matthews, 1998). The persistence of 74, a lower chlorinated congener, is an exception. Wolff et al. (1992), in a study looking at changes across a three-year period in capacitor manufacture workers, reports an increase in levels of 74 and 153 and a decrease in levels of 138 and 180. This pattern would suggest that the ratio of 74 + 153 to 138 + 180 will increase across time in persons with occupational exposure. Wolff suggests the particular configuration of congener 74 makes the molecule resistant to metabolism; and also congener 74 may be a result of dechlorination of higher chlorinated congeners. A few studies have directly addressed correlations between congeners in addition to describing marginal distributions. High correlations found between 138 and 153 render separation of the two difficult (Luotamo et al., 1991; DeVoto et al., 1997). DeVoto et al. (1997) suggest exploring the use of ratios between congener levels, using a similar rationale to methods of analyzing macronutrient effects in nutritional epidemiology (Wacholder et al., 1994). Our findings suggest ratios between congeners, in our case 74 + 153 + 201 and 138 + 180, may be key in tracking the route of exposure. It is possible ratios between congeners also relate to different effects on health outcomes. Other approaches to the problem of comparing congener patterns, while accounting for correlations between congeners include fingerprinting methods which are based on weighted Euclidean distance between individual profiles and standard profiles derived from the original Aroclor mixtures (Dunn et al., 1984) or from samples of contaminated food (Hwang et al., 2001). How to apply the same methodology to a comparison between two groups of profiles, without reference to a standard profile, presents an interesting methodology problem for future research. Another approach is the application of factor analysis to identify subgroups based on congener patterns and their relative contributions to total PCBs (DeCaprio et al., 2005). This method is not appropriate for our problem where subgroups are already identified, but may provide an interesting validation analysis for future research. Multivariate regression modeling has been used to simultaneously predict a set of congener levels as dependent variables given a set of independent variables (Schaeffer et al., 2006). A limitation of our study is the confounding factor of time since exposure. For the fish eaters cohort, there was a considerable time lag between the PCBs in their original form and the exposure due to their bioaccumulation in fish, followed by a short time lag between that exposure and the measurement used in this analysis. All members of the fish eaters cohort had eaten sport-caught Great Lakes fish during the past year before their serum was taken. For the capacitor plant workers, however, occupational exposure ended in 1978, or earlier if a worker terminated employ-
ment before 1978, creating a time lag of at least 22 years between exposure and measurement before serum was taken in 1996. The differences in congener composition between the two cohorts might be affected by changes in which congeners remain in the body across time in addition to the difference in route of exposure. Another limitation of our study is the fact that only 14 congeners were measured in both cohorts. As stated earlier, these 14 congeners account for 80.7% of the total across all 62 congeners measured in the fish eaters cohort and 78.4% of the total across all 38 congeners measured in the capacitor plant workers cohort. We may be missing important elements of congener patterns due to other congeners that we are not able to analyze in these studies. In summary, our results suggest relative proportions of different congeners are key in tracking route of exposure. Different routes of exposure do not appear to be related to the total of all 14 congeners after relative proportions are taken into account. While total PCBs may be related to health outcomes, we suggest relative proportions of different congeners within the total also be taken into consideration when analyzing effects of PCB exposure on health outcomes. Acknowledgements This research was funded by the Agency for Toxic Substances and Disease Registry, cooperative agreement number U50/ATU502923 (capacitor plant workers study) and Grant number H75/ATH598322 (fish eaters study). We thank Daniel Hryhorczuk for his assistance with the collaboration, and we thank Susan Schantz and Mary Wolff for their valuable input. The protocol for the fish eaters study was reviewed and approved by the University of Wisconsin-Madison Medical School Human Subjects Committee and University of Illinois-Chicago Internal Review Boards; the protocol for the capacitor plant workers study was reviewed and approved by the University of IllinoisChicago Internal Review Board. References Agency for Toxic Substances and Disease Registry (ATSDR), 1993. Toxicological Profile for Polychlorinated Biphenyls. US Department of Health and Human Services, Public Health Service, Atlanta. Anderson, H., Falk, C., Fiore, B., Hanrahan, L.P., Humphrey, H.E.B., Kanarek, M., et al., 1996. Consortium for the health assessment of Great Lakes sport fish consumption. Toxicol. Ind. Health 12, 369–373. Braunberg, R.C., Dailey, R.E., Brouwer, E.A., Dasza, L., Blaschka, A.M., 1976. Acute, subacute, and residual effects of polychlorinated biphenyl (PCB) in rats. I. Biologic half-life in adipose tissue. J. Toxicol. Environ. Health 1, 683–688. Brown, D.P., Jones, M., 1981. Mortality and industrial hygiene study of workers exposed to polychlorinated biphenyls. Arch. Environ. Health 36 (3), 120–129. Burse, V.W., Groce, D.F., Korver, M.P., McClure, P.C., Head, S.L., Needham, L.L., et al., 1990. Use of reference pools to compare the qualitative and quantitative determination of polychlorinated biphenyls by packed and capillary gas chromatography with electron capture detection. Part 1 serum. Analyst 115, 243–251.
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