Document N2jD7anBB81g8zd9YR4m53Dk8

TO: FROM: SUBJECT STJOE. ZINC SMELTING DIVISION MONACA, PENNSYLVANIA 1S06I CONFIDENTIAL R. A. Kurey and G. E. Welch J. A. Morgan EPA/CDC Survey for Heavy Metal Absorption by Children Living Near Smelters , cc: CAC CDH JDJ JRKe JHK RAK REL WFM WRM JAM-3 SJO RGR WHS GEW ADZ R/S-2 DATE: June 29, 1976 Document No. : 10410 Project No.: 8029 ABSTRACT This memo reports on a statistical analysis of blood and hair samples from children living close to nonferrous smelters. Included in this study are the assays of FEP (free erythrocyte protoporphyrin), Cd, Cu, Pb, and Zn in blood and As, Cd, and Pb in hair. By the EPA's definition, Herculaneum is an area where "a serious prob lem of heavy metals absorption" exists. Monaca is not. However, Hercu laneum does not show significantly higher average blood Pb or Cd values than Perryville, a control location in Missouri. Herculaneum does show a significantly higher FEP average than does Perryville. Of the smelter locations tested, only Bartlesville, Oklahoma appears to have a really serious problem of heavy metals absorption. Blood EPA Hair Heavy Metals s. 2 INTRODUCTION Recently the Environmental Protection Agency (EPA) in conjunction with the Center for Disease Control (CDC) completed a sampling study on children living close to nonferrous smelters. The object of the study was to deter mine if such children showed evidence of undue heavy metal absorption. Involved in the study were approximately 2250 children, 5 years of age and under, from 24 locations--4 control locations, 3 lead smelter locations, 5 zinc smelter locations, and 12 copper smelter locations. One control location and one copper smelter location are in Mexico. The rest are in the U.S. ,0f course, the study includes the areas surrounding St. Joe's Josephtown zinc smelter and Herculaneum lead smelter. We report here on a statistical analysis of the data from blood and hair specimens. We do not report on urine specimens since none were taken (or at least none were reported) from the lead or zinc smelter locations. The assays reported, and here analyzed, are: FEP (free erythrocyte protoporphyrin), Cd, Cu, Pb, and Zn in blood; and As, Cd, and Pb in hair. The blood assays are in pg per 100 ml of blood. The hair assays are in pg per g of hair. CONCLUSIONS 1. Neither the as-received data nor the logarithms of those data fit a normal distribution function very well--though, in general, the log arithms fit a normal distribution better than do the as-received data. 2. There are substantial differences in averages and in variation both between the control groups and between the smelter groups. 3. The data are influenced by some factor or factors unknown to us. The effect of those factors is to distort the probabilities associated with the usual statistical tests. Such factors must be identified and cor rected for before we can make valid statistical tests. 4. Herculaneum is, by the EPA definition, an area where "a serious prob lem of heavy metals absorption" exists, in that 15% of the children tested in the area have FEP values greater than 50 pg/100 ml blood or Pb values greater than 30 pg/100 ml of blood, and in that the Pb in hair values are more than twice as high for those living within 1 mile of the smelter as for those living further away. 5. Of the blood assays, only FEP is "significantly" higher for Herculaneum and Monaca than in Perryville, Missouri (the control group most similar to Herculaneum and Monaca). 6. Hair Pb and Cd are significantly higher for both Herculaneum and Monaca than for Perryville. 7. Of the smelters tested, only Bartlesville, Oklahoma appears to represent a genuine problem area. DR 3403015 4 3 8. A number of correlations exist between the various components tested. Generally, these are weak and lack predictive capability. However, Pb in hair vs Cd in hair stands out as one correlation that is exceptionally strong. SUMMARY STATISTICS Tables A through H (at the end of this report) display the summary statis tics for each of the assays, for each of the sampling locations. These tables contain statistics for the untransformed (as-received) data and for the log arithmically transformed data. The statistics presented are: N - the number of reported assays X - the average of the reported assays S(X) - the estimated standard deviation of the assays P(X) - a probability value associated with the reported assays (discussed below) High - the largest reported assay for the group Low - the smallest reported assay for the group log X - the average of the natural logarithms of the data S(log X) - the estimated standard deviation of the log transformed data P(log X) - a probability value associated with the log data (see below) Geo. Mean - the geometric mean of the data, which is the anti log of log X. The probabilities values P(X) and P(log X) indicate how well the untrans formed data or the transformed data, respectively, fit a normal probability distribution. A value of less than 0.05 indicates that the data are not likely to have come from a normal distribution. Assumptions Implicit in"Statistical Tests At this point it is worthwhile to review the assumptions that underlie most statistical tests, and discuss the effect of violating those assumptions--because the EPA/CDC data do violate those assumptions. The assumptions concern the deviation of individual elements of data from estimated means or regression lines, and they are: 1. The deviations are normally distributed 2. The deviations come from distributions which have the same standard deviation, and 3. The deviations are independent of each other. i DR 3403016 ^ 4 Table 1 contains data which comment on how much the first two assumptions are violated. TABLE 1: Comparisons of Data Distributions BLOOD HAIR FEP Cd Cu Pb Zn As Cd Pb Number of groups Number of groups for which P(X) >0.05 Number of groups for which P(log X) >0.05 Untransformed Data: Ratio of largest to smallest std deviation Largest yi Smallest yi Largest Y2 Smallest Y2 Log Transformed Data: Ratio of largest to smallest std deviation Largest yi Smallest yi Largest Y2 Smallest Y2 24 1 10 9.0 5.5 0.3 39.2 -1.0 2.6 2.0 -0.1 7.1 -1.5 12 0 5 8.4 6.7 1.1 51.9 2.0 3.0 1.3 -0.9 6.0 -0.7 16 13 9 5.4 7.1 -0.3 60.0 -0.6 2.3 2.5 -2.5 13.4 -0.6 24 8 18 5.2 3.6 -0.1 20.7 -0.8 3.0 0.7 -2.8 15.4 -0.6 21 13 14 4.3 7.4 -0.7 63.5 -0.9 1.9 1.6 -3.1 17.3 -0.4 16 24 12 15 22 447 27.1 (37)* 5.7 6.2 0.5 0.9 42.1 46.7 -0.8 -0.7 2.1 1.9 1.8 -0.9 5.1 -0.8 1.0 -0.8 3.8 -1.4 24 5 21 18.4 4.2 0.2 19.8 -1.4 1.6 0.7 -1.1 3.0 -1.4 *The number in parentheses excludes Anaconda data. The Anaconda data look suspiciously as though they suffer from a misplaced decimal point. Failure to Fit a Normal Distribution The data presented in Table 1 consistently show that they log transformed data fit the first two assumptions better than do the untransformed data. But, at least for some purposes, the fit is still inadequate. Of the 161 total groups of assays, 43 (27%) of the untransformed groups are fitted adequately by a normal distribution while 114 (71%) of the log transformed groups are adequately fitted by the normal. OR 3403017 'i 5 We will be looking at two general types of statistical tests--those that seek to compare averages and those that seek to compare variation. Deviations from the underlying assumptions influence these two types of tests differently. The general shape of a probability distribution is quantified by two statistics: yi - the coefficient of skewness, and Y2 - the coefficient of kurtosis. yi measures the tendency of the distribution to be non-symmetric. A positive value of yi indicates a long tail to the right of the mean, while a negative value indicates a long tail to the left. Y2 is a measure of concentration of the distribution. A negative value indicates a large cen tral mass with small or nonexistent tails, while a positive value indicates little central concentration and heavy tails. For statistical tests concerning averages, the value of Y2 seems unimportant--if the sample size is at least 10. However, large values for skewness (yi) indicate serious distortions in probability of ordinary tests unless the sample size is large. A sample size of 10 is "large" for a dis tribution whose Yi is less in magnitude than 1. A sample size of 30-50 is "large" if yi is less in magnitude than 3, but only a sample size in the range of 100-200 can be considered large for yi of magnitude 5.1 Since we have only 15 groups (8%) with sample sizes less than 30, and of those the largest value of yi is 1.8 for log transformed data, we con clude that the shape of the distributions will not be an important factor for the tests of averages of the log transformed data. The same cannot be said for the untransformed data. For statistical tests concerning variation between or within samples, Yi is unimportant, but Y2 has great importance. This is because the stan dard deviation of squared sample standard deviations is:2 where N is the sample size, and a is the true population standard devia tion. Since the usual tests for differences in variation depend on the underlying distribution being normal (Y2 = 0), and since, even for the log transformed data we have many large positive values for Y2 tests comparing variation can be very misleading. The tendency will be to show many "significant" results when none really exist. Unequal Standard Deviations As a result of the factors discussed above, we have no very good method to test if the standard deviations for an element vary from group to group. The usual tests give highly "significant" results. But, as explained above, the level of significance is likely overstated. However, with the ratios of largest to smallest standard deviations (for the log transformed data) ranging from 1.6 to 3.0, we must conclude the differences probably do exist between the standard deviations of the groups. DR 3403018 6 Such differences in standard deviations can have serious impact on the validity of comparisons of the averages between groups. If, in comparing such averages, the number of samples in each group is approximately equal, there is no serious problem. If, however, the group sizes differ by a factor of 2, and the ratio of standard deviations is about 2.2, then a test at the nominal 5% probability level has a true associated probability of 12% if the larger group has the smaller standard deviation, or 1.4% if the larger group has the larger standard deviation. 2 This discussion is appropriate basically to between-group comparisons. Presumably the standard deviation within a group is constant. Lack of Independence of Deviations The third assumption listed above is that the deviations are independent of each other. We have strong, though indirect, evidence that this assump tion is violated also. In one series of calculations, to test the effect of distance from the smelter on heavy metal absorption, we assumed that sample sequence numbers were indicative of distance (we had no other information on distance at that time). We then divided each group into two halves based on the sequence numbers, and compared the averages for these two halves (on the log trans formed data). Table 2 contains a summary of those comparisons. TABLE 2: "Significant" Differences Between First and Second Halves of the Groups Number (%) of Number (%) of Positive Negative Results Results Total Number of Tests ALL CHILDREN Around Smelters Control Groups Total 12 (9.6) 1 (3.1) 13 (8.3) 14 (11.2) 5 15.6) 19 12.1) 26 (20.8) 6 (18.8) 32 (20.4) 125 32 157* ONE CHILD PER FAMILY Around Smelters " 11 (8.8) Control Groups 2 (6.3) Total 13 (8.3) 11 ( 8.8) 6 (18.8) 17 (10.8) 22 (17.6) 8 (25.0) 30 (19.1) 125 32 157* *The total number of tests is less than 161 because, for one smelter (Corpus Christi), there were no blood samples among the first half groups. In the above table, we list the number of times (and in parentheses, the percentage of times) the average level of an element tested signifi cant by the usual t test at the 5% probability level. If there are no real differences, we would expect 2.5% positive results and 2.5% negative results due to chance causes. The positive results indicate that the children in the first half groups (presumably those closest to the smelters) have higher levels than those in the second half groups. Negative results indicate the opposite. DR 3403019 4 '4 7 Without the large number of negative results and without the large number of "significant" results among the control groups, the large number of positive results around the smelters would indicate potentially serious problems. But the number of negative results exceeds the number of positive results, and it just doesn't make sense that children exposed to signifi cantly higher concentrations of one element would be exposed to significantly lower concentrations of another. Also, we have roughly 20% "significant" results from the control groups. Thus, we must conclude that something about the data seriously distorts the probabilities of the tests. According to earlier discussion, the shape of the sampling distribution should not have much effect on the probabilities providing that the numbers in the groups are large. (Of the groups that showed "significant" differences, the smallest contained 47 values.) To check on this, however, we performed similar tests except that the samples were assigned randomly to one of the two half groups, and repeated this procedure 10 times on both the transformed and untransformed data, giving 20 sets of 161 tests. The percentages of "significant" results ranged from 1.9% to 8.9% in the 20 sets, and averaged 4.5% for the untransformed data and 5.3% for the transformed data. We thus conclude that the shape of the distribution curves was not the cause of the distortion in probabilities. We are thus left with non-independence of the data as the likely cause of the probability distortion. Unfortunately, we do not have sufficient data to allow a detailed exam ination of sources of this non-independence. For the most part, we can only speculate on the causes. There is, however, one possible source we can check: differences in variation between children within a family versus children from different families. We performed the usual analysis of variance for this effect, and found 59 (36.6%) of the 161 groups showed "significantly" more variation between children of different families than between children within a family. However, because of the points made in the discussion of Y2* these 59 "significant" results are open to question. But, as a further check, we simply performed the first half groups versus second half group t tests using only one assay per family for each element. The summary of those t tests is included in Table 2. The results using only one child per family do not differ appreciably from the results using all children per family. We thus conclude that differences in variation between the children is not the major cause of the probability distortions. We have exhausted the possibilities that we can examine with the data available to us, and can only speculate as to other possible causes. One possible cause could be some sort of experimental drift or source of variation. For instance, an electronic instrument for automated analysis subject to electronic drift could be the explanation: a drift of less than 0.5 standard deviation could cause results similar to those reported here. A value of 0.5 standard deviation for Pb in blood, for instance, is equiv alent to about 4 yg/100 ml of blood. Such a drift could be undetected by usua-1 laboratory quality control procedures. DR 3403020 8 Another possible cause is some sort of racial, ethnic, socio-economic, dietary, or other such drift among the children sampled. Given other well known and documented physiological differences between various racial and ethnic groups, it is not unreasonable to assume some racial and ethnic differences in the absorption and elimination of heavy metals. Also, dif ferent racial and ethnic groups tend to have different dietary habits, and various foods contain differing amounts of heavy metals. The sampling was supposed to take place in a spiral pattern outward from the smelters. So, given the general tendency of neighborhoods to be segregated, it is very likely that the first halves of groups have substantially different racial or ethnic compositions than the second halves of groups. To sum up, we have strong indications of serious problems with the data. We have insufficient information to pinpoint the causes of those problems. And, these problems cause us to question the results of any statistical tests performed with these data. If the indicated drift is experimental, then it will not be possible to ever make valid statistical tests. If the drift is racial, ethnic, etc., then knowledge of the causal variables and correction for them will allow valid tests. STATISTICAL COMPARISONS In the following, we present results as though there were no statistical problems with the data. But bear in mind that we cannot say conclusively what is significant and what is not. Average Concentrations The average concentrations for each location are shown in Tables A-H in the appendix. These averages show no consistent patterns. Comparing either arithmetic or geometric means, for blood samples there is at least one smelter area that has a lower average than any of the control groups, and for hair samples there is at least one smelter area that has a lower average than at least one of the control groups. Table 3 gives the F test results for differences in averages between various combinations of groups. F values of 3.1 (for the Pb smelters) to 1.6 (for all groups) would be significant if there were no data problems. All the F values reported are above the critical values for the usual sig nificance level. TABLE 3: F Values for Tests of Differences in Group Averages - Log Transformed Data BLOOD HAIR FEP Cd Cu Pb Zn As Cd Pb Control Groups Pb Smelters Zn Smelters Copper Smelters All Groups 17.7 4.3 4.9 16.1 11.8 13.9 14.3 39.7 26.6 30.2 57.3 53.1 5.6 12.2 10.9 25.4 18.9 3.7 56.8 23.0 27.1 92.0 324.8 325.1 3.1 4.5 23.5 9.8 35.. 1 4.5 16.1 20.4 13.7 34.3 * DR 3403021 9 Percentages of Groups Beyond Cut Limits Part of the EPA's definition of "a serious problem of heavy metal absorption" is that 10% of the children tested exhibit "undue absorption." And "undue absorption" for the elements reported on here is defined as blood Pb level >30 yg/100 ml and/or FEP level >50 pg/100 ml or Cd blood level >1.0 ppm. The limit on Cd in blood gives us some reason to question the data presented. If the assays are truly in pg/100 ml, then the largest reported value (3.79) converts to approximately 0.038 ppm. Thus, none of the samples exceed 1.0 ppm. In Table 4, we present the percentages of each group which exceed the EPA's stated limits, except for Cd in blood, where we presume that the real limit is 1.0 in whatever units the data are presented in. Also included in Table 4 is the fraction in each group that exceeds 40 pg Pb/100 ml blood (the more traditional indication of excess Pb absorption). As can be seen from the table, only one smelter has more than 10% beyond the presumed Cd limit (Bartlesville). But 11 of the 20 smelters and 2 of the 4 control groups exceed 10% on the combined FEP-Pb limit--including Herculan eum, but not including Monaca. The high variation between control groups (particularly with FEP) indi cates strong influences of socio-economic/cultural/environmental differences. Unless a control group can be readily matched with a smelter group according to such factors, comparisons are meaningless. The percentage of Pb in blood samples beyond 30 and beyond 40 yg/100 ml indicate a serious problem only at Bartlesville. A few other smelters (not including Herculaneum or Monaca) may be moderate problem areas. But even Bartlesville does not approach the magnitude of a problem indicated by the 1974 samples from Kellogg, Idaho where 87% of the children living within 2-1/2 miles of the smelter had blood Pb values greater than 40 yg/100 ml.^ Approximate Distance from the Smelter Another part of the EPA's definition of "a serious problem of heavy metal absorption" is "when there is a two-fold decrease of that metal in any sample (blood, urine, or hair) from the children living closest to smelter to those living furthest away." As of this writing, we have actual distance information only for the Pb smelters--and that will be discussed in a later section. Here we show the results of dividing the groups into halves via sequence numbers. Table 5 shows the ratio of the geometric means of the first half group versus the second half group. The underlined values are those for which the t tests were "significant." DR 3403022 i 10 TABLE 4: Percentages of Children in Each Group Beyond Limits FEP >50 Pb >30 FEP >50 or Pb >30 Cd >1.0 Pb >40 Perryville, Mo. Nogales, Mexico Safford, Ariz. Albuquerque, N. Mex. All Control Groups 1.2 17.9 3.3 6.0 7.6 Herculaneum, Mo. Glover, Mo. Bixby, Mo. All Lead Smelters 10.8 8.7 16.7 12.1 Monaca, Pa. Amarillo, Tex. Bartlesville, Okla. Corpus Christi, Tex. Palmerton, Pa. All Zinc Smelters 1.6 8.4 6.7 15.4 15.0 9.1 Copperhill, Tenn. Hayden, Ariz. Anaconda, Mont. McGill, Nev. Hurley, N. Mex. Douglas, Ariz. White Pines, Mich. San Manuel, Ariz. Miami, Ariz. Morenci, Ariz. Aqua Prieta, Mexico Ajo, Ariz. All Copper Smelters 1.1 11.9 3.1 0 18.4 12.5 0 3.0 7.1 4.0 18.8 ' 0.9 6.8 All Groups .>7.9 4.7 2.8 3.3 4.8 3.8 9.9 0 0 5.6 3.2 15.8 39.1 0 4.4 15.1 5.7 9.9 3.1 0 12.2 12.5 5.8 3.0 6.1 2.0 5.2 0.9 5.5 7=0 5.8 19.8 6.5 10.7 11.1 14.7 8.7 16.7 14.5 3.2 22.1 38.9 15.4 15.9 20.9 6.9 18.8 6.2 0 20.4 19.8 5.8 5.9 12.1 5.0 19.8 1.9 10.2 12.8 2.3 0.9 1.1 0 l-1 2.0 0 0 0.8 1.6 0 10.4 0 3.5 3.6 2.1 2.4 0.9 0 0 0.8 5.5 0 0 3.1 0 4.2 21.8 0 0.9 6.5 1.1 3.0 1.5 0 6.1 2.1 1.4 0 1.0 0 2.1 0 1.4 2.4 DR 3403023 i 4 11 TABLE 5: Approximate Effect of Distance Ratios of average concentration in the first half group to average concentration in the second half group Controls Perryville Nogales Safford Albuquerque BLOOD HAIR FEP Cd Cu Pb Zn As Cd Pb 1.05 1.20 0.97 1.10 0.74 0.86 0.94 0.88 1.00 0.98 1.04 0.99 0.92 0.98 0.98 0.84 1.03 1.00 1.09 0.98 0.72 0.79 0.85 0.85 0.85 1.19 0.82 0.93 0.70 1.44 0.66 1.01 Pb Smelters Herculaneum Glover Bixby 1.29 0.79 1.26 1.56 1.42 1.04 - 1.14 0.93 1.35 -- - 1.47 1.45 - 1.08 1.12 - 0.92 0.89 Zn Smelters Monaca Amarillo Bartlesville Corpus Christi Palmerton 0.91 0.90 1.38 * 1.07 1.45 0.93 0.51 * 0,77 - 1.06 1.10 2.34 * 1.06 1.03 1.09 0.92 it 1.00 - 0.91 1.22 1.44 1.22 1.70 1.09 0.72 1.23 1.07 1,61 Copper Smelters Copperhill Hayden Anaconda McGill Hurley Douglas White Pines San Manuel Miami Morenci Aqua Prieta Ajo 0.92 0.83 1.03. 0.95 0.91 1.18 " 0.82 0.90 1.11 0.75 0.89 1.00 - 0.95 0,87 0.98 0.91 1.06 0.97 0.92 0.96 1.01 0,94 0.96 1.04 0.96 0.87 1.35 1.02 0.86 1.31 1.00 0.92 1.08 0,78 0.76 0.94 0.98 0.84 1.00 1.01 0.98 0.91 0.95 1.02 1.07 1.07 1.00 0.99 0.93 1.18 0.90 1.69 0.83 0.99 1.04 1.01 1.07 0.71 0.74 1.06 1.15 0.98 0.79 1.71 0.84 1.10 1.65 0.70 0.91 1.10 0.52 1.04 1.24 1.06 1.09 1.68 1.00 1.22 1.31 0.51 0.91 0.90 0.65 0.79 No blood samples in the first half group. DR 3403024 12 Only one group shows a two-fold decrease between the first half group and the second: Pb in blood at Bartlesville. Interestingly, the same loca tion shows almost a two-fold increase in Cd in blood between the first and second half groups. That the division of groups into halves gives an approximate distance relationship is demonstrated by the Pb smelter groups. Table 6 shows how the first and second half groups were actually divided according to distance. TABLE 6: Distance versus Sequence Numbers First Half Group Second Half Group Herculaneum* Glover Bixby <1.0 mile 32 <2.0 mile 4 11 >1.0 mile 24 >2.0 mile 14 16 <1.0 mile 3 <2.0 mile 3 1 >1.0 mile 49 >2.0 mile 16 27 *1 sample from Herculaneum was unidentified as to distance and 3 were subsequently identified as coming from the persons taking the samples. Glover and Bixby are, of course, sparsely populated areas, and Glover does not exhibit a good distance-sequence number correlation. However, Herculaneum, and Bixby do exhibit good distance-sequence number correlations. Actual Distance from the Smelter As mentioned previously, we do have actual distance data for the Pb smelters. Table 7 gives the ratio of geometric means and associated t values for the difference in means for various possible distance comparisons. TABLE 7: Actual Effect of Distance for Pb Smelters BLOOD Herculaneum FEP Cd Pb <1 m vs >1 m Ratio t '*' 1.65 3.74 1.96 2.60 1.42 3.71 <l*i m vs >1% m Ratio t 1.39 3.24 1.64 1.16 1.16 1.72 Glover <2 m vs >2 m Ratio t 1.64 2.21 1.03 0.08 1.55 1.56 Bixby <2 in vs >2 in Ratio t 1.45 0.67 1.87 -1.73 1.29 1.05 HAIR Cd Pb 1.12 0.77 0.84 -0.77 2,11 4.01 1.42 2.00 1.09 0.20 1.10 0.29 0.86 0.93 -0.32 -0.14 DR 3403025 13 The only ratios which show close to a two-fold decrease are the <1 m vs >1 m comparisons for Herculaneum. Cd in blood is nearly two-fold; Pb in hair is slightly more than twofold. The t values greater than 2.0 are usually considered significant. Correlations Between Assays Table 8 contains the correlation coefficients and associated t values for correlations between different types of assays. These were calculated for the log transformed data. The first five columns are within group com parisons, adjusted for group to group differences in averages. The last column is correlations between groups. The degree of correlation indicated is quite consistent for the different groupings of locations. Out of the 102 correlations reported, two show a significant negative value--about the expected result from chance causes. Many positive significant correlations show up, but these generally are rather weak and lack predictive power. (After all, given enough data extremely weak correlations will show up as significant.) One set of correlations stands out as highly predictive: Cd in hair vs Pb in hair. One other is at an intermediate predictive level: As in hair vs Pb in hair. Why these hair results should be so strong when all the others are weak is difficult to explain unless the hair results are more in dicative of exposure to the heavy metals than absorption of the heavy metals. Of the between group correlations, only Zn in blood vs Cu in blood, As in hair vs Cd in hair, and Cd in hair vs Pb in hair are significant. Herculaneum and Monaca Compared to Perryville Perryville, a small town in southeastern Missouri, is the control group which probably matches both Herculaneum and Monaca best. Table 9 compares the data from Perryville with the data from Herculaneum and Monaca. Blood FEP is significantly higher at both Monaca and Herculaneum than at Perryville, while blood Cd is significantly lower at Monaca than Perryville. The hair data for both Herculaneum and Monaca are significantly higher than Perryville for both Pb and Cd. Concerning the portion of samples exceeding certain threshold limits, Monaca is significantly lower in the portion of samples that exceed 30 yg/ 100 ml Pb in blood than Perryville, while Herculaneum is significantly higher than Perryville in the portion of samples that exceed 50 yg/100 ml FEP in blood. DR 3403026 * 14 c 0 0 O. *3 Po 0P CQ P 5* in rH rH o 0) 3P U pH 0) S CO p in 00 to o to N*- rH IN CM o *fr Cl o o rH o H o rH o Hf to n 00 rH '0- r* a in vO rH o CM o to rH to Ooo oo oo *H in 00 to rH o VO CM 00 o to rH rH rH rH vO i rH 1 to 00 to O rH CM m rH to rf Tf tn n* o rH CM o o o rH o o o oo o o 11 rH in to to VO CM 0- to so CN 1 rj* 00 rH rH o HJ- rH vO rv to O 0- in rr *3* CM in rH CM O o o rH oo oo o 1t GO tn in NO 00 ''fr to vO o rH rH CM o o 03 rH N- o CM 03 m CM CM 00 rH o oOoo oo o to to to vO o o rH in CM to o CM o rH H o 1 to o vO r^o rH rH m CN o o o rH o ooa O oo i 1 1i 1 1 1 rH in rH to to in o rH tO rH rH CM o X to to CM to 00 tO N* to to o o to to in Nin m *H rH OY o o O rH 1 i OY CM in Csl CM t1 CM rH Ht *H in CM to NIs* 00 O rH rH to I*'- rH CM CM CN O O to NO CM tn o CO CM o rH to to to 00 CM rH rH rH CM oOQ 1 rH N- CM to in CM N' rH 00 00 to rH CM rH CM CM ooo Tf rH to Tf N> rH in N. in CM CM tn in CM CM rH CM o oo in to to vO 00 rH rH rH o ^3* in CO to to to to to r- *H rH 111 to in in o 1ti rH rH rH LO rH rH rH 111 CM in to in 11i CM CM to (N CM in 00 o hN* O N- rH to CM 00 CM to Oo o CN in to rH in CM o CM HJ* O 00 m CM 00 o 00 to to o to CM (A P G> GP M i--H <s> e C/J p p in p 0 Xp Cu tH 0 S CO p p rH o in 5* P. P3 3O op p 5h o in 00 to * vO o in o 1 MO CN VO rH CM CM to CN rH o in to rH rH VO in VO cm n* to CN VO o CM o rH rH 1 * 1 * ft o Oo oo t in to 0- 00 VO CN o 00 oo rH o 1 ft 1 oo o CM CM rH l 1 rH o CN o ft to CM in m 1 1 rH rH *3- to | O t1 't rH rH rH rH to 1 1 oo CN 00 GO 1 CM CM o,, CN <* rH i o 1 in to 1 oft oo i1 CM in rH 00 h- vO in in CM rH o 00 o rH CM CM CM o O to 11 rH Hj* Tj* to 00 o to to r-r o o rH rH o i 0% c- Ht in CM in N- rH to rH o rH o rH rH rH o O CM OO ooOO 1 o to in O c** rH CN n* rH CM in o o o tH o o o oo o ii T5 3 X c in 0 XI u u 0* M > a. a. w cu CP u. ~a 0 oo oo rH rH CO CQ 3 X c <n 0 X u cp CM > 00 uu 0 "0 Oo oo rH rH CO CO t11 11 11 1 I 1 t1 t 1 t 11 1 1 1 m CM in CM oo to 00 Nvo m rH 11 CM CM in *H CN m CM to CM rH oo o o 1 X c <n a X a ns > 3D Uu T3 T3 OO oO rH rH CQ CQ CM 00 1 to VO NO vO N* NO HJ- to to 1 o 00 rH t 1 rH CM Tf vO 00 rH 1 1 rH CM 00 00 rH oo to to to 'O- rH to to CM to to CM CM CM o c tn *0 X M < O CP -0 ou o H rH 0 CQ X in in >> X Cl, cu *0 *0 OO Oo rH rH CQ CQ N- to rH o 1 00 o o f 1 vO to o CM i1 vO vO vO CM O rH Oo 11 in rO et M *0 O o rH CQ N TJ* to Tf ^r CM CN CM *0 u CP p 0 X tn > tn P 0 X to C". 00 rH O o to rH CM 00 LO o CP p *H a: tn > 0 P X /V. 4oV PD O V OD QT Q TABLE 8: C o rre la tio n s between Assays 15 TABLE 9: Comparisons of Herculaneum and Monaca to Perryville, Missouri Assay Blood FEP Blood Cd Blood Pb Blood Zn Hair Cd Hair Pb Geometric Means Perryville Herculaneum Monaca t Values for Difference Between Perryville and: Herculaneum Monaca 19.97 0.196 15.83 367. 0.67 9.80 22.78 0.227 17.12 - 3.04 46.1 25.05 0.164 13.76 342. 1.46 13.9 2.20 1.00 1.33 9.94 12.62 5.30 -1.79 -2.20 -1.85 5.27 2.58 Blood Pb >30 FEP >50 Blood Pb >30 or FEP >50 Blood Pb >40 Blood Cd >1.0 Percent of Samples Beyond Limits 4.7 9.9 3.2 1.2 10.8 1.6 5.8 14.7 3.2 2.4 5.5 0 2.3 2.0 1.6 t Values for Difference 1.31 2.69 1.97 -2.23 0.22 -0.75 1.06 -0.12 -1.20 -0.32 OR 3403028 \ 16 REFERENCES 1. Barrel, J, P, and L. Goldsmith, "When is N Sufficiently Large?," The American Statistician, Vol. 30, No. 2, May 1976, pp. 67-70. 2. Scheffe, H., The Analysis of Variance, J. Wiley Sons, 1959, pp. 331-369. 3. ILZRO "Morbidity and Mortality Weekly Report," September 14, 1974. dr 3403029%^ 17 TABLE A: FEP in Blood - Summary S t a t is t ic s 0 0 Hf r--j 00 00 v to 0 M3 to tn to Cs- tn Cl 01 00 pH in in O 00 O 00 0 Ol 1--t to CM CM CM CM CM CM ai 00 to CM rH CM CM LO in to to 0 M3 CM CM CM CM to CM M3 00 00 MD vO CM rH O 0 to rH CM CM pH CM CM rH CM CM CM to CM CM to CM O to s X 00 rH O O rH 0 OOOO rH * OOOO a* r-H X CM LO CTi tn in OO v v vO rH 0 CM tn to to Hj* rH W O000O to O CM O0 O O0 O 01 00 O rH CM c^ to tn tj- tn in 00 0 0 O O to O m 0 O rH O 00 OO O 00 to O' to Tf vO Cl 0 0* CM in 0* O0 O 00 0 O00 O O 00 to 0 0 O O O CM 000 OOOO O' in O' to vO O vO Cl Cv CM O' 00 in CM O' to CM in 0* CM O00O 0 00 X 00 to to rH 06 CT> 01 vD 00 Ol to O rH rH r-3 CM to to to to vO rj* rH vD CM vO rH 0 to rH to CM to to rH O 0 in Cl CM in rr rH vO CM CM rH CM rf CM to to to to to to vO vO c- Ol CM to CM Cv 0 to vO CM 00 CM CM Cl to CM 00 CM to to CM to to CM rH TJ- O CM 0 O Cl to 0 tO CM O Tf rH O Cl Cl CM O 00 rH rH 0 to CM rH CM rH a* 0 rH at V0 CM CM rf in CM Cl Cl o- CM to rH O -3 rH rH rH rH rH rH rH rH rH rH rH rH rH rH rH rH rH rH o tO orL^O to CM CM o to"- Hm CM CM 00 tO CM o Cl OO-^trtO O) N O O OOOOt^OO OOOOOMOOWtTOOOOOO o 5 O 00 01 rH 00 CM to tn in Cl CM h- tn tn in rH O 0 VO rH O to VO Cl VO 00 H 00 o- GO Cl 0* 01 vO CM CM in CM O in 00 OO in Cl 0 to 0 to Cl CM O to Cl 33 to to rH rH pH rH pH pH rH pH rH rH rH rH rH to /--1s O 0 0 0 X O000 a. d 0 0 d 000 000 d00 CM O O O O O O O pH O OOOOO O O O rC O O CM O O O O O OOOOOOO OO OO O 0OOOOOOOO OO O O0 rH 0 d0 to tn VO 00 vO 00 00 to 00 O to CM 00 00 r^. 01 to pH vO 0 c- to 00 O to O in to CO 00 pH CM CM 00 to O' Cl CO to pH rH CM pH rH CM rH c*. O' in CO in 00 to 0* to Cl O' rH in to O' O in 00 00 H pH pH CM pH pH rH CM rH rH rH rH CM pH rH rH to in inCl pH CM rH to 00 CM a>' CM Ol 00 m vO 00 CO pH rH O' ao pH f'. 00 pH Ol rH rH Tf dIX to vO r-* CM to CM CM CM vO CM to 00 CM CM to CM in CM 00 CM V0 CM 00 CM itno Cl CM 00 O vO Cl rl* O r- to to in CM in pH to CM rH to to pH CM CM CM to CM CM CM to rH 2: v00 vOO ooi T00f S\DO CN to 00 to ro lo O to ro tt 'O Cl C) H H N t'HiflHCi'OClH^O\0\00 OOO'Olfl^ClvOOftOcHON in to rH to rH tO *H rH rH rH o 01 X 03 </) 0 s B3* 0 5S -0XH -NH 2: + ISDH 4> S 1/1 T3 6) fH 0c 3truO U C8 4-4 3 t-i M<X A pH mom rH rH 0. z Cfl < < to U 0 0) s <4 pHM g 3 * O cBn 4) C p<Hfl 2 4 u 5 * -o cO 03 3 r4 0 M4> > 0 rH XXH) rH rH X CO CO < X QO 4) rH pX H to u cti X 4) O A 0) H +UJ) H rH pH H (H {C * Bcf.l r<0HM) 0) * CBO c CO u CGO O O f--t H w s >to p0H) VCW3 00 <A hM 3 IaT 43-)i 0 0 GH M pH pH < CO u a. < O to a G C 0) *> HHtM 3SO*3 rH rH U < <4 pH d pU3 * G *G0 0) O P*T3 U P* X d Odd > z. -*Wx* O O 0 *H X4> N 3E S *H . <M I0fl 2 .Xe HXISaX0)0f+cJ h 3'H 3 0i 6 tM H fn < * r-H 03 3 d G d N H <5 &. E d *h tM H <5 H U e0) MO OH X03 s: * d M OpH *tHM Ih N< d 3O* oph fH 03 4H rH 03 B CO M 03 PPHU O O rH rH u s < zsqS co s: < < < 1Q0< O O rpHH < M to 03 0M0 Jd (0 pp0HH3 d B CO "4 DR 3403030 18 TABLE B: Cd in Blood - Summary S t a t is t ic s sO 00 oo 00 cm LO SO 00 pH CN r--4 rH CM o oo oO g oo sO CM CM CM rH o pH o o O Hfr LO 00 to LO to \0 pH O CM to LO rH tv CM r*H bd o o o o M pH sO CM O pH O O oo o 'tf pH to pH o o o tv Hf to o o pH to d MO CO O06 3e 3 00 00 00LO 00s> CM c-h oo o 00to Cv CM <<dr sO tv sO sO oo o o fV Tf pH pH PM to CM CM to sO to tv tv 00sO sO CM in tv to fv sO LO 1 1i-H pH pH pH tI c- o sO o ion in o oo oo 00pH CM in CM CM Hf to 1pH CM CM rH t tt pH CM pH pH o ooo CM t^ CM in 00 in pH C- co to pH CM 1 1 1pH CM pH pH pH pH t tI pH pH in pH 0 o pH O' o 5h X vXh Cu X CO o pH in o CM CM m CM oCM pH CM pH CM pH pH to SO to to OpH pH 3 to CO in tv < * to tv tv CM CM to to oo o oo o oo o 00o to o oCM CM CM pH pH pH oo oo o rH . 00to tv to pH so pH CM pH pH o o LO o * 00tv tn CM to Mr *v to in to m to dod O CM to c- in 00 pH to to tv 00 . O vt> CM CM to inCM rH pH CM pH PH to in totx CM CM pH CM CM pH pH CM CM rH pH CM o o o dooo CM CO to 00 pH to. in |V to to pH :2 00 00 in cm <T CM rH pH to topH pH pH CT) 00 00 CM rH to oo ttoj* SO SO o LO 1 o o to LO o 00 to to CM LO cr> cm lo o cm lo oo O to LO H 00 pH X 0) </l X 04 3 *o o o o x x 2 H tM X *H * 0) x h< 0 rH 3O pH pH * or x xx pH V) 0 pH X O J3j O or u X X 00 4h 3 X* pH 0 O (0 pH pH Cu X LO < < m *h o 2 +J fH % 4) 1 30 0 W ccd Sfl_ x ~cad -> X 3 XJ u h > O wa X >-i P^ aua< X cd V pH H to M O <* X d) *H X X * x cd pH 0 0> V) sx H pH rt 4) a Cd XpH * w 0* * iH rC 0 * roH dH >to o u to o X x o 3r^ (J 'H H m xx 3 0M p- i c 6 X pH pH 135 O U Cd U pH < o to ux * 3 -C UN H X 40H 3* ^ H C MO *H 'H x X H nH 2 -rt 0 N . H pH 4) 5 to H 2 > M V) N U & O <1 0> *"" -->' < H < cdZ 2 .h3 t3> <H J3 'T3 "vU10G X M C C X cd 3 u 400>-t'-l2`rt (X'O U .H -H 0t g &,XUH3-Mc3 ocdco3ojfl-H 3 0 X X (U p| X a, cd "I N H X < o X 0 & o pH pH , t/i Qu 3 o X pH pH U2H2SQ*W2 << < (/) 0 X 3 Sm allest 23 0.116 0.064 0.00 -2.352 0.321 0.00 0.095 OB5 3403031, 19 TABLE C: Cu in Blood - Summary S t a t is t ic s 4.272 0.135 0.00 QO vO N O Cft H -sd" t"- o oo o n cn cn o g X Ctf o rH w CU O rH CO rH o o to o oooo X lO to VO o rH c^ CM 'D* o CM <M CM CM CM w o oo oO to X r*** rH to LT> Tf ci CM rH o hO vO to LO to 5 "D- sf to rH to to to 3s q to ci to lo to r4 *D* to CM CM OlHONMJltOiNHCOOJrf r^ Cl CM rH GltOe&Glt>*ClOOCMOClOO Cl to c- CO OOHWj-HOlftK)OH oOOO'O^OOOOOOOO oo r^ o to o c- CM rH *-h CM to oooooooooooooo o CO to n vO o CM to NO O HOOl/)U)HHinTl,OOK)l/)tO to N H 1^ H to I*"* 75.1 14.2 0.00 to rH O vO rH to CM to to CM rH CM rH rH CM CM O CM X rH o CM CM w Cu o o O O rH to Oi Cl X w o to o 00 o V) CM CM CM rH CM to o rH to CM r- Cl to IX O o Cl Cl rH MD *0 (N fO N CO O Ci 00 \Q rH tO vD to Oi v0 CM CM CM to TT to 00 to to to rf to to tO vO vO to to to Tf HJ* rH 00 rH rH' rH rH rH CM rH rH rH CO to 00 o 00 CM. rl* to o rH C- CM Cl to o to to to vO rr o rH o to to o o ooo O o o o o o o LO vD o to rH rr to O' CM to to CM vO to to rH VO c** rH CO to Tf* oo 00 00 Ht to vO o co C-. rH CM rH CM rH rH rH CM rH CM rH to CM c- 00 o OOH. vO CM CM rH CM to to 00 o o o >10 in vO vO vO vO to to to o Cl VO ci a- Cl O O CM o Cl o o o VO rH rH rH rH rH rH rH rH rH N h I/JH \0 Ol H Oi o \fl \0 o COOvOfeO^OvvOOClOOlOCN rH rH rH rH O r- vD 00 o tO r--t 49 X 4) V) o ou S *H X o s: * S* z8 o r-( 3O <r x H W T3 (-i +j c ?>Xh *-C4hD) 4bOh 3O cru 3 U &04h XI -H o cd **1 --I CU S CO < < in o P 4) s 3 0 -CO 4) 2 O c 2 -d efl eO h M 4) 3O U > * u> X <M CD rH c 4> to CU 0) H rH vS rH a, < H 4 o rH > in H u 6 a CO o u> & CD rH 4) to M H u H rH Uv 6 0M p, a a co o co h < ca o a. t x ON oo to *H H 0) X O U X .2 M H G 4) N < NO 2 -H H 2 > h l * N U C5/2 r.-eh <--! -H < * Z Z SO 4) N 6 x(HH ctCC3O *-*t X mc*fl o*H. 8e3 0&.4T3) OU*i*4lH4) i--D1O 4-4>) X H oH a. < a o u in 9* O $u3 Wto 4> on uOo. Xxca rc5t Oxu Ma o3 q -XSh S.3 W2 3 O. <or-<i-n . u 3> Sm allest OR 3403032 20 TABLE D: Pb in Blood - Summary S t a t is t ic s 2.111 0.285 0.00 9 00 rf N 00 o H vO VO fO 00 O H O) 00 o h O H Tf ^ H K) CO vO CO pH pH pH rH pH CM CM pH pH pH WOlOtO^OOCOMWO^tONH wOHootooNNintNcoHir) vO X co cm oGO M vO ^ M ooo o Cu OMVO ^ H vO oo 04 PH vO to pH pH 00 O oo o o toiowhOioiwocoHur phoooph^tqcmOvoocm *.......................................... .......... OOOOOOOOOO VO 00 o to co 00 to bO LO tt Tf CM o to to rr to to vO to pH CM C* 00 to Tf LO LO Tf CM LO C- 00 c- to Tf to 00 CM to C Tf 00 to CM CM to pH pH Tf c*. 00 00 to to to CM to to Tf Tf o* (N NO 00 oo o oO Ooo oooOoo o U3 x CM O c* NO pH to CM CM pH ttt oo LO LO Tf in LO 00 to Tf CM Tf CM 00 Tf CM Tf Tf to pH CM pH 00 pH o- pH LO to pH Tf o CM pH to 00 Tf Tf r-. to pH 00 00 c- c- c-. CM Tf 2 CM CM CM CM CM CM CM CM CM CM to to CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM v> 3c vO 'O N CO N S vo tn n rr IA Oi K) to C^ 00 00 sohoo vO to H O H t OOHffirtH ^ co to rj'OHCO'OvOtNMMtOtOOH tOCn-^NHNH\)OOHTfK5Ty 10 'O o o m h ol vo o rr h tr o 0.00 18 3.6 5 00 pH 00 Tf pH 00 rv 00 pH Tf CM pH in pH HH s Tf Tf CM1 Tf Tf Tf 00 Tf Tf CM CM M1 r- r>. 00 CM Tf 00 in CM CM 00 Tf Tt pH in in tt in (PH Tf pH X oo W a. o CM tn Tt o C" CM o 00 oo a CM o Tf CM pH pH pH o ooooo 00 X 00 co CM O r-H Tf r>. pH NO CM Tf CM CM o C-S w NO NO 00 sO ih SQ co pH pH pH pH SO CO C" pH CO SO pH Tf sO 00 pH CM 00 pH 00 - Ch Tf sO Tf CM Tf pH pH SO 00 Tf BX SO c- sO CO CM CM tH pH sO pH co CO c- CM sO pH pH pH pH pH pH pH pH pH pH CM CM pH pH CM pH CM pH pH CM pH pH pH pH pH pH pH pH CM SC SO CM SO 00 00 SO pH 00 CM CM Tf SO OoM- 00 pH pH Q C> C-. 00 pH O o r=H Tf SO o pH o VO O CM oo pH rH pH pH pH pH pH pH pH pH 9.1 13 X tf tf) s fr 3 o o o o 55 h 2 pM N X H * tf H tf pH 2< 3 O a* m k * U <M Pi tf) TJ tf a & tf N 3 o pH O or u tf <4H 3 tf tf* OO 4m pO rH 0 pH pH a. sc < < tf) M o tf s M pH B 9 <2 *5 e rt X A tf pH u 3 4) X pJ O > XI u O X pH 0) *rl pH Xo< X td +J w pH a> w a. d> H B tf *--l X ^ a. h b o >U o U (A V tf tf lTM( U V) M H o H x 3 M tf X t* 5.1 3 Q S 1 H kH pH O rt pH 2 < co u a. < o a . ptf H tf c U tM X -M c H H tf pH w x p2 m e2 tf H *C tM < tM N O 2 *H * a -H S > -< X < tf) O T tM H H H < tf <-> < * z 2 tf 0) M tf tM tf h J= x cd r.H 3 < H H -0 i VI Q. C c e -i X tf tf Jh ^ A U a, < PS4 o M 0 --1 0) PH tf 2 H tf CJ tfCk.13 O -H pH 00 V 1 0) tf . 0. X a) U O (3 u usSi h 3*H C 5 or n *H xS 2 M 2 3 < O < pH pH < , tf) Q* 3 o M pH pH < 4J tf) tf DO *t3f Sm allest dr 3403033 21 TABLE E: Zn in Blood - Summary S t a t is t ic s Mo 5.671 0.168 0.00 290 vO CM CM o '0* to LO o to to to to to s X 00 00 rH CM m H LO pH o * * PH o o o o LO 00 to O an 00 pH to pH o pH CM CM *H CM SH o o o o CO ftX cf LO pH o to pH C LO <50 00 oo 00 00 3 LO LO LO LO LO 3: LO 01 LO Tfr s rH h- 00 rH r* CM pH pH CM pH X3 pH to CM to to vO oo to rH 00 *H LO LO X rH CM 00 00 X rf W ** O* PH X o to oo w vO oo 00 CO to oo oo ex LO LO to to to to to CM to r^> Z oo 00 pH to rr CM o pH o LO 00 o o rH CM r^ 00 CM CM tO "^3*L0 LO 00 to to r^ to LO CM o vO vO to to LO CM to to to to to to to to to to to to to to O^O CM C-. ooooo tnoNo w to to to O LO O M H H CM pH pH O O O PH oooooooooooo 00 o oo tHn oOoJ nCi mH TTff CM tn H H CM CM oooooo I/) 00 rf h Ol to to in o> n o in CO 00 CM 00 in in vo in m m h in h to in h N Oi to O M M H H tO (N M H r** to 00 pH to pH CM CM Hf 00 LO vO CM to LO rf CM CM CM CM CM CM *H CM to CM CM CM CM CM to oooooO to Tf pH 00 to CM pH o* to pH pH 00 to CM 00 00 00 00 r- 00 00 oo CM LO LO LO LO LO LO LO LO LO LO LO LO vO CM *<* o to VO CM rf* to r-N r^- LO CM pH CM pH pH pH pH pH Tf vO VO 00 LO 8 pH 00 to 00 to oo pH pH o CM to pH oo CM pH pH to CM to to LO CM o CM to LO \> LO CO LO LO LO pH CM LO o o o LO oo 00 o LO pH pH pH pH pH o oo oo o OO nO CM C0^0O rt \D vOpH to pH pH pH to LO pH O *fr00 LO LO pH 00 00 pH rr r- 00 00 to pH pH pH pH pH CM *H CM ~ CM pH CM LO to LO LO LO to to LO CM to pH oo CM to oo to "*r 00 CM Hf CM LO CO to CM to CM r*> to to to to to to to to to to Cl CM r^. lo to lo r-.2- to to CM O 04 oo pH rH pH LO pH rH oo o LO M* cm LO pH pH to pH pH pH fv. tH 56 0.00 13 295 Xo> in 2 g* u o oa 2 H o 2; No X *rt o* k o <IS p 0) PH 3O pH pH p p cr u kw *H tn *T3 QJ G o pH u o 3O a- o H cd 3 k QQHH H 0) o m pH H O- 2S CO < < V) u o h o X pH pH *H pH X a oa <; cd 4> pH H m pX k .o P H H pH H S cd &. p cd . pH *H O> to 0) k 6 W * CO u M 3 M pH u H pH ced 5 U -M IaS M cd &3 3o Nl pH O H IS 2 SQ U a. < PM . . H <D G G o H pH XV <D pH V k X IS 5k s 0) H 3 03 N Ns N O S *H p e H p CO 'H s: > k in - (- < o r-l < *H p 03 X M - T3 p c p H * in Cu X G C pH 5x cd o O pH 4) pH d> P.T3 u pH H p k cd < ^pH pH 0) 3 * ^ pH CQ p H a t-H d g; a id N *?H k o* Qo D< X cd k 3 pH G O U cd X G < a 3 3 O Q a U5 pH 2 M o 3cr* Op fpH4 c<< g. o k * pH pH < 4H m Q on k 3 Sm allest 0B 3403034 'L 22 TABLE F: As in H a ir - Summary S t a t is t ic s o to to on Oh- Hto O O pHH o o oo o g X o LO CM VO o o to O WrH o O O o tX i s~*\ X to vO on vO CM bo roH CM to o CM vOa vO *r to LO o oo oo C/3 X rH r>. o vO rH vO tn 00 t"v to 00 VO -H to to pH 5 CMI rHI ONI CMI CM too o00^o rofr oto o oo o o o d o oooo 00 H 00 O H 5 o in h so w H-i H CM O CM X CM wX o o o o a. o o o o N'OOOtN *Xw CO tn tn ^ h o H to* O H M ooooo rf h o M rr IX OOl Otoi O rH H r--I 00 rH o oo o o s0o0 Oso Nl/) t(nN (NN CM rH CM to *<fr rH to CM to CM rH vO rH to to to CvOM on 00 to o to to VrHO to CO 00 to LO to o o o o o o o o O o rH o o rH o to CM rH CM vO tH to TT rr to oo rr vO M' to to oo o OO o o o o LO o oo o oo o 00 CO o 00 00 to r* rH vD CM to vD 00 to CM CM VO o to vO Os vO vO to vD pH OS vO os vO vO VD 00 on o oooOoooOOoOo O o d to CM on vD to o to CM as Tt* oo on to 00 CM 00 rH 00 OS oo CM to to ^3* OS 00 to rH vD vO vO -cf Os CM OS vO rH VO VO o CM *H 1 pH 1 o i pH I rH 1 o 1 rH 1 o 1 o O o 1 CM 1 CM t o Tf* o o vO o to o o to o o vO O o o o 00 o o Is*. o o vO o o on o o pH CM O to o o H o o o o o o o o O o o to o o o tooo o o o to to poH to o TJto o CM on o to to o *3* CM o o OS o rH on o CM O o o o o CM rH rH o rH to o to CM to 00 o CM rH o o o CoM rH o o o o o o o o CM O o o pH CM o o o o o o o o oo oo ooo o o o o o CM o Oo 00 00 TJ* 00 00 00 V0 as CM to o pH pH CM to CM 00 CpHM o vO *'3* 00 rH to o to o on CM VO rH an 00 oo 00 00 o o rH rH O o O o o O o o pH to o rH vD O 00 Tf pH 00 to to rH hpH to CM pH CM o> 00 rH O *3* to to to 00 o LO o o on oo otjn* o to o 00 pH **t OS o CM o CM o o o O o O o o rH CM CM O CM o to O 00 rH on Tf on 00 rH 00 Os tro- V0 oo LTJ on CM rH to o pH *<t rH X <D vs s * o o oo * ' s H N u X 0 -H M <h a> pH 0) S < 3 o &rH rH t VI TJ cr u (H <ap an m 3 O N *00<42-4 X_<3JT U -4 OO H rH a. tz; w < < VI so h O M pH 0) B cn "O n) 3o h<>U JX3 NOX sac is so < cd an pH H VI rX O > M O H M X * M cd pH an 0) VI a* an acd. H B w OO IcOcdd rMHH c cd 3 c.s tr i~t i-t O Cj rt U G. < 0 t/J u (-t c rC ON H K M c 0 4-> H C X s k oN < 1 N 0a s*Jh3 NBTzBOc3O*HzC>D s z H *u< W 0 O r-4 O c-l 0 ssssisgaaifisPewXa au) tC3ihM 3&o --mH *H tn 3 H 4 CO 40<*>> w h 0 < > *h -x &, Uh HR B0 BM CO <M ^ o< u N3O W o M V) <&0/0* prH0H) h 2 cd S CO 403035 DP 3 23 TABLE G: Cd in H a ir - Summary S t a t is t ic s 2 \Qw VO *f to vO to VO Hf CO to 00 00 m mvO vO vO to o VO CM o o tO vO o to vO CM vO h- to vO Hf o CO to Hf o to oo Hf to o o CM cm CM to CM to vO to pH o Hf vO CM o Hf vO ht Hf vO o to Hf ht rH to vO oo to **4 3o O o o o o to to to pH CM Hf " - CM pH rH rH o P"* pH o o rH pH --i CM t-- pH to o x Gd Oi O 'O H oooo o oooo a, \Q rH pH Hf Hf ooo K1 \0 to 1/5 tN vO v LO vO tO o oo o o in cm 00 O CO vO vO c- o c- 00 CM vD to O to o Hf pH C ooo oooooooo CM O 00 o oo X vO GO 00 00 00 \Qto to sD pH to r>. pH LO tO rH Lf) CM r- oo Tflrt'Tf O Hf Hf v pH vO to r*^ to to pH to CM Hf to (N c- CO vO c-* CM oo o 00 00 00 00 00 00o vO oo vO oo oo a o vO oo SO Cs MO VQ CO o LO to o o o O O o o o o o pH pH O O o pH o o O o o o o o O o O o o pH o X 00 0vO pH CM 00 00o vO Hf LO LO I GO \0ht to ht pH o LO vD pH CO o pH c* to o vo to to vO vO oo pH O s to fs to to o Hf pH o o o to LO Cn vO V to to GO vO pH to o Hf LO Hf Hf to to Hf o CM pH pH to Hf to CM to LO oo CM 15 o o o O o 1 1 1i I i pH pH pH pH o O PH o pH pH oOo oo Ooooooo o I pH ht o VO Hf Hf pH to pH pH pH o o oo 00Hf f** to ht Hf o ooo to pH Hf to C* to pH JO pH to to pH o od o o o 00pH pH o to LO CM CM to LO vO o pH to pH CM pH CM pH to CM to CM LO pH ooOooOoooOoo o o Hf Hf Hf s to pH CM to >H ^f Hf pH X 00 o o CM CM CM 00LO a> to Ht pH CM Hf 3o O O pH o pH pH CM * * CM 3I"** HJ* V? O HJ* VO pH CM M vO 3 to CM to pH to H * CM sO rf vO Hf CM CM pH to to Hf o 00 00 CM vO to vO vO sO to to CM sO vO /--s o o o X oOoo V--> o. o o o o CM to o pH pH o o o o o ooo oooo o o pH O pH ooO oo oooo LO o rH o Oi 00vO Hf o pH to to CO O Hfr H}* pH Hf* r** vO LO Hf Hf to LO o 00 00 00vO Hf CM LO LO 00 00X pH C-. O to pH pH to pH pH to CO to o o to CM to vO Hf pH vO oo CM to to oo to to vO pH CM vO vO to Hf Cv to to sO oo to to w/ 3CO pH o rH o o vO to LO CM * - CD CM vO HT pH pH pH pH pH pH pH pH pH pH to 01 00 00 rH c- to to to CM O to sO vO pH to to Hf r^- O to LO to Cv 00Hf oo c- oo CM t-* to sO ` to sO to to Hf pH pH sO vO Hf CM o to VO vO c- sO 00 00 00IX o Hf to sO pH LO to CM CM r-* Hf c- Hf vD oo vO Ht pH o 00 00sO to CM to CM to CM pH pH o pH pH pH pH pH pH CM pH CM 00 00 00so vO CM to C00 vO LO CM CM vO sO C-- to CM CM LO Hf so V Hf to C-* CM LO c- r^- Hf Hf Hf c- to ^o to o oo Hf c*. pH r- oo Hf Hf LO Hf pH CM pH CM pH LO pH X ft) V) S g* u o ou o z z; H N *X H u <0 rl* X 3Q> < O pH Up-H > Vt XI 3pH cr sm * +J e J h O u i--I as 0lH )O 32O cr u S f--< a. Z CO < < m N o z o c Z TJ rteft > upH > O H!h -H ft) t --i X um< o to uN * JG H ft) G G ft) M O tM H H X X u X * ft) X M pH ft) ZH . G a> n < tM tM o `H + .fM A a CO X> tf) eft pH < <pH 68 -M S eft a G* X eft U 3 x e n 3 O pH O U eft X 5 u X 3 ao *p-i pH << < pH 1' pH < 0$ pH M eft 3 aCO OP3^3036 Si V 24 TABLE H: Pb in H a ir - Summary S t a t is t ic s g 00 00 rH o. to "T rH r*H rH r*4 rH s ,-s CO 00 r-H o00 o in rH m * rH o w U fh to CM CM M3 Tf to to CM in rH rH 00 CM * in c* to CO to c- vO 00 in v CM to 00 00 to in CM SO to CM C* in rH to to tO to CM 00 CM o *"H m CM c- Tf oo rH CM CM rH rH CM rH CM rH rH Cn to CM rH CM in m CM to rH o o o CM v v CM C- CM to rH CM in CM rH 'C.f VP VO to o o o o c*. CM v O X o c- t^. in 00 o tTov. oo m vO in in in to vh o o o C/3 vO 00 to CM rH 00 c* 00 oo oo X CM in in CM00 VO rH 00 m CM vO CM CM CM CM CM tj* vO 00 to rH rH to in 00 to to rj* to to CM in C- to s *t rH <r O to CM vO CM CM 00 VO in in in rH 00 CM rH to C- rH o oo m vO 00 VO in vO rH rH oo 00 CM CM 00 vO rH Tf to vO CM in 00 00 SO vO C* c- 00 C- in m so c*. s o r^. in o o o o o o o o rH 00 rH M3 CM rr 00 rH in v in CM CM 00 CM 00 vO c*. SO *0' SO vO in to to CM in in rH SO to 00 in rH c- CM in to V 00 oo V CM CM tO to to to to CM to to CM CM to CM CM to CM CM CM CM CM CM to CM to CM rH r*-. C*S o C* CM 00 vo o00 to to to CM cc*. to LO to c* rH to s in c*. oo to r- CM to to to CM o to vO to in to to Cv Tf 00 00 s CM to in in rfr*H in in to in in rH to rH vO v to rH in in oo CM CM rH CM Tf- CM rH CM ^3* CM to *3* CM tn CM 00 C% fH c* so c*fr sO C00 in CM SO rH CO CM 00 in vO rH rH rH rH o sO in o o CM X a. rr to CM o oo rH CM O o rH rH to *H rH o to o oo o o o O o to o r-H tn CM rH 00 in X w <7l O N h CO rH rH rH o CM C* NO N M N c- in sO 00 CM CM in CM o o to vO rH in 00 00 ****** * N H M N vO Tf o i--I M h M to t H H rl H rl H r--4 r-H -H r~* -H fNJ K) rH C- in m C-s in C- cm in rH to rH rH rH rH rH vO sO CM to c00 sO in CM CM CM vO LO SO CM in vO Tf vO crH M3 sO to CM CM rH to ^ CM sO Tf "3* CM CM c- vO rH rH c- LO r- 00 C- in rH CM sO in to in rH t^. to 00 CM oo rH tO in rf* CM CM CM rH CM CM rH rH K) rH CM rH CM CM rH rH 00iiTO 00 00 vO ""fr c- to m CM LO c* 00 C> 00 c- rH 00 r- t"O'k to vO LO rr to in rH CM rH in rH rH >< 10 *o s Bp* o O o 2 I* X2 H tM *H 4> *xs h< rH a V rH Po- o u rH * a fH +M H 1/) TJ 0) P au0pu.) & r0OHS6 O 2 OM 4canms Po g'U J3p rH rH rH << * 10 U o 0) 2 <M rH k 0) 3I s tn V 5a rH 3 uaO> i i5 *3 N iy >o rwXO- as *H-3 raH fiHQ r<H X PS rH E- 10 o * rH os a> V) Cl. 0> cn H rH H a rH U - Qw * *H is B O as rH rH uC3 UH G as > 16 0) rH fM N uo +J IA M 3a, 2i uOH >ac-S.l u G CHM rH rH < o tft oM X X *H 0) B oN p B* 4) *-> X s*H H <y *2 rH 03 H B 0) N < N O 5 *fM * N e can -rt S > p V) tM u G 2 G*H M --< He > 25 < rH *H H (U) N 0) to & H Bj * *H 3 < t H Gm 4S T) U B B O OB*.TXJ BU > * (0 <r-i XG 0) rH O *OH rH N &0P 3 *H tG3n s3 s H UPGa> M eu G 3 < oSh P-t < ^ CJ O rrHH <c ' po p rH rH rH rH G 5 can DR 3403037 *