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**& Mr.kt m *** ESTABUSKEDIBtt E. I. Du Po n t d e Ne mo u r s & Co mp a n y INCORPORATED Wil min g t o n , De l a w a r e 19898 ENGINEERING DEPARTMENT LOUVIERS BUILDING BCC: E. S. Jacobs R. W. Kennard D. W. Marquardt IC 31 - Applied Statistics December 18, 1981 Ms. Yvonne D. Curry Editorial Assistant Environmental Science & Technology 1155 Sixteenth Street, N.W. Washington, DC 20036 Dear Ms. Curry: Enclosed are two copies of the revised paper, "Development of an Air Quality Standard for Lead from Community Studies", and a black and white glossy print of the figure in the paper. As you re quested, I've revised the text so that the tables are numbered in the order that they are mentioned in the text. I believe that the paper is now ready to go to press. I look forward to receiving the galley proofs. Very truly yours, ENGINEERING SERVICE DIVISION R. D. Snee Consultant Supervisor Applied Statistics Group RDS:cak Enc H42424 TEH 0470060 DEVELOPMENT OF AN AIR QUALITY STANDARD FOR LEAD FROM COMMUNITY STUDIES Ronald D. Snee Engineering Department E. I. du Pont de Nemours $ Co. Wilmington, DE 19898 ABSTRACT A methodology for the development of an air quality standard (AQS) for lead is presented. It is shown that the results of community studies can be used to calculate the air lead level at which the cumulative frequency distribution of blood lead values of a population will meet a biological guideline for blood lead. The procedure is illustrated using the data on the relationship between blood lead and air lead obtained in two well-known epidemiological studies. A variety of analyses, involving different blood lead-air lead models, blood lead frequency distributions, and data bases, are included to study the sensitivity of the methodology to variations in assumptions and calculation procedures. The proposed method ology is general and can be used in the development of any AQS for which the appropriate biological guideline is expressed in the form of a cumulative frequency distribution. TEH 0470069 DUP050082889 N42424.01 1* Introduction In 1974 Zielhuis (1) proposed a biological guideline for blood lead. This guideline provides for the protection of public health by specifying a desirable distribution of blood lead values. It is therefore proposed that the air quality standard (AQS) for lead be determined by calculating the air lead level at which Zielhuis' guideline will be met. The methodology for making these calculations and developing the AQS is described. It is shewn that blood lead values from several populations can be combined to give an accurate estimate of the within-population distribution of blood lead values. The data collected by Azar, et al (2, 3) and Tapper and Levin (4) are used to illustrate the procedure and to develop an AQS for lead. These results are also compared with the standard adopted by the United States Environmental Protection Agency (5). The approach is general and can be used in the development of an AQS for any pollutant for which a biological guideline similar to that of Zielhuis is appropriate. Any group of subjects exposed to a given air lead level will have a distribution of true blood lead values because of biological differences between the subjects and differences in lead exposures from sources other than air lead. The distribution will be further broadened due to blood lead measurement variation. As the air lead level of the group is increased the corresponding blood lead distribution will shift upwards. This suggests that an air quality standard for lead could be determined by finding the air lead level TEH 0470070 DUP050082890 -2at which the upper portion of the predicted blood lead distribution will be equal to that of Zielhuis' biological guideline distribution. A schematic of this procedure is shown in Figure 1. In order to make the calculations described above it is necessary to have a model for the relationship between blood lead and air lead and data on the within-population variation in blood lead values. The best-available data on the blood lead-air lead relationship for adults is that published by Azar, et al (2, 3), In this study air lead and blood lead measurements were obtained on 150 subjects over a 2- to 4-week period. The air lead was continuously measured 24 hours per day during the test period using personal monitors. Two to eight blood samples were taken from each subject and duplicate lead determinations were made on each sample. This is the only study of nonoccupationally-exposed subjects whose air lead exposure was monitored continuously by personal air monitors. The Seven Cities Survey (4) contains a large amount of data on within-population variation in blood lead values. The blood lead levels of 2,015 subjects from 12 populations (80-219 subjects/population) were collected in this study. This study is important because a large sample size is required to get a precise estimate of the within-population distribution of blood lead values. The use of the data from the Azar study and Seven Cities Survey in the development of an AQS for lead is described in the following paragraphs. TEH 0470071 DUP050082891 -3- 2. Biological Guideline for Lead After an extensive review of the literature, Zielhuis (1) concluded that the following blood lead distribution was an acceptable biological guideline for the protection of public health. Percentile 50 90 98 Blood Lead (pg/dl) 20 30 35 This guideline has been widely accepted and has been adopted by the European Economic Commission (6). This distribution will be used to determine an AQS for lead by first calculating blood lead levels associated with percentiles of interest and then calculating air lead levels which would raise these blood leads to those of the zielhuis distribution. We concentrated on matching the 90 and 98 percentiles, since individuals at the upper end of the distribution are at greater risk. Results for the 50th percentile are included, however, for comparative purposes. It is important to recognize that, in terms of observed and theoretical distributions of blood lead data, the 50th percentile of the Zielhuis distribution is not consistent with the 90 and 98 percentiles. If we assume that blood lead levels are lognormally distributed then the 90 per centile of 30 and the 98 percentile of 35 are consistent with a 50 percentile of 23.2 yg/dl. In the TEH 0470072 DUP050082892 -4- unlikely event that blood lead levels are normally distributed, the 90 and 98 percentiles o the Zielhuis distribution are consistent with a 50 percentile of 21.7. It is concluded that the 50 percentile of the Zielhuis distribution is low by approximately 3 jig/dl. 3, Relationship Between Blood Lead and Air Lead To determine the air lead level at which the blood lead distribution of a normal population was consistent with the Zielhuis distribution, it was necessary to know the relation ship between air lead and blood lead. Two different relation ships were used. The first model was the "lead exposure'' model (7,8) which assumes an exponential relationship between blood lead and air lead. The second model was a linear relationship between blood lead and air lead. Both of these mathematical forms have been used widely in correla ting air lead and blood lead data. The "lead exposure" model used in this analysis was: Blood Pb = 12.1 (air Pb + b )-26^9 (1) This model was developed from the Azar data (7). It relates blood lead to total lead exposure to dividing lead exposure into two parts -- air lead exposure and background lead exposure (ie, food, water, etc). In Equation 1, background lead is represented by the B coefficient which was found to be 3.28 for the Azar data (7,8). Additional details on the development of this model are given in Reference 7. TEH 0470073 DUP050082893 -5- The second model used is a straight line blood lead - air lead relationship with a slope of 1 (ie, an increase of 1 yg Pb/m^ of air results in an increase of 1 yg Pb/dl of blood). Blood Pb - (Air Pb) + B0 (2) The blood lead - air lead slope of 1 was found in a combined analysis of eight epidemiological studies of the relationship between blood lead and air lead (8) and in the studies conducted by Chamberlain et al (9), The slope of 1 is also supported by the lead exposure model (Equation 1) for the Azar data and by the analysis of the Azar data conducted by Hammond et al (10); both of which indicate that the blood lead - air lead slope for the Azar data varies from approxi mately 1.2 to 0.6 for ambient air lead levels <10 yg/m^. Slopes larger than 1 have been reported (11,12); however, these appear to be out of line with respect to the other studies and are based on clinical rather than epidemiological studies. The methodology described here is general and can accommodate any assumed slope or blood lead - air lead model. 4. Blood lead Distribution To determine the blood lead distribution for the Azar data/ a blood lead value was calculated for each subject corresponding to an air lead level of zero. Equation 1 indicates that the ratio of the blood lead B.i at air lead Ai, to the blood lead B2 at a second air lead A2 is: TEH 0470074 DUP050082894 -6- Bl = Ai + 3.28*1 0.2669 b 2 A2 + 3.28J (3) Hence, the lead exposure model (Equation 1) predicts that the blood lead of a subject at an air lead of zero will be: Bp " f 3.28 1 2669 [a + 3.28J (4) where B0 is the calculated blood lead at an air lead of zero A is the air lead exposure of the subject, and BA is the blood lead of the subject. In the case of the linear model, the blood lead at zero air lead is given by B0 = BA - A (5) where B0, BA, and A are defined as in Equation 4 above. After the blood lead values were obtained for the zero air lead level, the next step was to determine the distribution of blood leads calculated from Equations 4 and 5. The blood leads corresponding to selected percentiles were obtained from the best-fitting distribution of the Pearson system (13, 14) because the frequently used lognormal distribution was found to give an inadequate fit in several instances. The Pearson system encompasses a wide variety of frequency distribution forms and does not require an assumption concerning the specific mathematical form of the distribution to which the data conform. Many of the distributions which are frequently used in the analysis of air TEH 0470075 DUP050082895 -7- quality data (ie normal, lognormal, gamma, beta, and Weibull) are special cases of the Pearson system. This family of models selects that distribution whose first four moments (ie, average, standard deviation, skewness, kurtosis) are the same as those of the observed distribution. The lognormal distribution will be fit when it is the appropriate distribu tion; hence, the fit of the Pearson system will be equal to or better than that of the lognormal distribution. It is shown in Section 8 that the Azar data and some of the data in the Seven Cities Survey are not lognormally distrib uted. It is well known that the lognormal distribution is adequate for estimating geometric mean relationships among air pollution variables such as that described by Equation (1). We will see later that* in the case of the 50 percentile, there is no practical difference between the air lead levels developed from the lognormal and Pearson distributions. In the case of the Azar Study and Seven Cities Survey, however, the lognormal distribution does not provide an adequate description of the upper percentiles of the blood lead distribution. It is very important to get accurate estimates of these values because the zielhuis distribution and the associated air quality standard are based on the upper percentiles. The Pearson system is able to better address this accuracy because of its rich family of models and its use of four moments to select the best fitting distribution. Results for the lognormal distribution have been included, however, for comparative purposes. TEH 0470076 DUP050082896 -8- An alternative procedure to the Pearson system is to transform . blood lead data to another scale such that the distribution of the transformed values is closely matched by a normal distribution. As noted earlier, the Azar blood lead data at zero air lead were not lognormally distributed; however, blood lead raised to the 0.3 power, (blood lead)0,3* was found to be approximately normally distributed. The blood lead values calculated from the Azar data using the Pearson system are summarized in Table 1, The corresponding values calculated from a normal distribution approximation to the transformed data (blood lead)0*3 are also included in Table 1. In each instance, the results obtained using the Pearson system are in close agreement with those obtained using the normal distribution, indicating the Pearson system gave a good description of the observed data. The 97.5, rather than the 98 percentile, is used in the Pearson system. This slight deviation from the Zielhuis distribution was necessary because published tabulations of the Pearson system contain the 97.5, rather than the 98 percentile. 0 After the blood lead values corresponding to zero air lead were calculated, it was then possible to compute the air lead at which the blood lead distribution was equivalent to that of the Zielhuis distribution at the higher percentiles. In the Case of the lead exposure model (Equation 1), this air lead is given by 1 Az - 3.28 [(Bz /B0)*2669 - i] (6) TEH 0470077 DUP050082897 -9- where B0 is the blood lead at zero air lead and Az is the air lead associated with the corresponding blood lead (Bz) of the Zielhuis distribution. In the case of the linear air lead-blood lead model/ the sir lead which equates the two distributions is given by Az -- Bz -- Bq (7) where Az, Bz, and B0 have the same definition as in Equa tion 6 above. 5. Air Quality Value Developed from Azar Data The air lead at which the Azar blood lead distribution was equivalent to the Zielhuis blood lead distribution was calculated using Equations 6 and 7 (Table 1). The availability of two different air lead-blood lead models (linear, lead exposure), two different blood lead distribution models (Pearson system, normal-power transformation), and three different percentile levels (50, 90, 97.5) made it possible to analyze the Azar data in a variety of different ways. This enables a determination of the sensitivity of the resulting air lead levels to the calculation procedure used. In Table 1 we see that in all cases the calculated air lead levels are greater than 4 yg/m3. In the case of the upper (90, 97.5) percentiles all the air lead levels are greater than 5 yg/m3 except for the lead exposure model, normalpower transformation case. TEH 0470078 DUP050082898 -10- 6. Air Quality Value Developed front Seven Cities Survey Data The calculational methods used in the analysis of the Azar data were applied to the data obtained in the Seven Cities Survey, This is important because the Seven Cities Survey included blood samples obtained from 2,015 subjects in 11 different locations. This large data base enables one to obtain an accurate estimate of the upper percentiles of the distribution of blood lead values. The air lead exposures were obtained from stationary samplers located in the areas where the subjects lived and is thus less specifically related to individual bipod lead than was the case in the Azar Study. In this analysis, the lead exposure and linear blood lead-air lead models were both used. In view of the close agreement of the results of the Pearson system and the normal-power transformation, only the Pearson system was used to describe the blood lead distribution. The air lead levels and the associated 50, 90 and 97.5 blood lead percentiles calculated from the Seven Cities Survey data are summarized in Table 2. The air lead values used were the annual average air lead results obtained at each site. The air lead levels needed to make the observed blood lead distributions equivalent to the upper end of the Zielhuis distribution were calculated using 1 Az = (Ay + 3.28)[(Bz/B7)*2669 _ 3,28] (8) TEH 0470079 DUP050082899 -11- where A7 is the annual average air lead associated with the observed blood lead, B7, obtained from the Pearson system and Az is the air lead associated with the blood lead, Bz, of the Zielhuis distribution. In the case of the linear model, excluding the Rittenhouse location, the calculated air lead levels are greater than 5 pg/m3 in 28 out of 33 instances and greater than 4 pg/m3 in 30 out of 33 instances. Each of the 5 instances where the air lead level was less than 5 pg/m3 was associated with the matching of the 50th percentile. The United States Environmental Protection Agency (15) has pointed out that Rittenhouse is an old section of Philadelphia in which many of the houses contain lead plumbing which probably contributed to the relatively high blood lead values. The lead exposure model calculations showed similar results. Excluding Rittenhouse, the air lead values were greater than 5 pg/m3 in 26 out of 33 instances and greater than 4 pg/m3 in 30 out of 33 instances. Three of the seven instances where the air lead level was less than 5 pg/m3 were associated with matching the 50th percentile. We also see in Table 2 that there is a wide variation in the air lead values calculated for the different locations. This reflects variations in exposures to lead other than that in the air and to variations arising from analytical uncertainties in the data. TEH 0470080 DUP050082900 -12 7. Air Quality Value Developed from the Analysis of the Combined Azar and Seven Cities1 Survey Studies The combination of the Azar study with its excellent estimate of the blood lead-air lead relationship and the Seven Cities Survey with the large number of subjects provided the best basis for establishing an air quality value for lead, in order to do this, the blood lead values for the 2,015 subjects in the Seven Cities Survey were used to establish a blood lead distri bution. This distribution was constructed by subtracting the average blood lead for each site from each of the blood leads collected at that site. Next, these deviations from the site average were combined into a single distribution. The standard deviation of this distribution was the pooled within^site standard deviation and was a measure of the blood lead varia tion in the normal population. Since the blood lead standard deviation typically increases with increasing blood lead level, it was necessary to transform the blood leads before the combined distribution was constructed. The objective was to make a symmetrical distribution. It was found that the power transformation, (blood lead)*!5, resulted in a symmetrical distribution; however, the tails of the distribution were longer than those of the normal distribution (kurtosis = 3.81; whereas for a normal distribution kurtosis = 3.0). For this reason, the percentiles were estimated both by the Pearson system and the normal distribution (Table 3). In the Azar data, the blood lead equivalent to the 50 percentile point at air lead . 0 (lead exposure model calculation) was 15.77. The TEH 0470081 DUP050082901 -13- blood lead values associated with the upper percentiles of the blood lead distribution were obtained by adding the corresponding values of the "deviation from site average" distribution to the blood lead 50 percentile of the Azar data at zero air lead. A sample calculation for the 90 percentile using the Pearson system is shown below. 1 Blood Pb = [(15.77*15 + dev. from site avg. ) ] -3-5 1 [(15.77)-15 + .0738)]"^ . 21.7 <9> The air leads which equate these blood lead values to those of the Zielhuis distribution are summarized in Table 3. The calculated air lead level for the 50th percentile is 4.2 yg/m3 for all cases. The ten air lead values associated with the 90 and 97.5 percentiles ranged from 6.0 to 8.9 ijg/m^. it is thus apparent that an air lead level of 4 pg/m^ is consistent with all parts of the Zielhuis guideline and that the upper percentiles (90 and 97.5) of the blood lead distribution of a population exposed to an air lead level of 5 ug/m^ would be within the Zielhuis guideline. 8. Log Blood Lead Distribution The lognormal distribution has been widely used in the analysis of blood lead data. For this reason it is appropriate to consider what air lead levels would be obtained if the lognormal TEH 0470082 DUP050082902 -14- distribution is used to describe the blood lead distribution rather than thS more general Pearson system. The resulting air lead levels.are summarized in Tables 4 and 5. It is important to understand that these results are representative only if the lognormal is the correct distribution to apply. We tested the adequacy of the lognormal distribution by computing the skewness and kurtosis statistics for the log blood lead data sets in the Azar and Seven Cities Survey and comparing these results with the corresponding parameters of the normal distribution. Using the statistical tests discussed by Pearson and Hartley (13) we found that at least 7 of the 13 observed distributions (Azar plus 12 sites in the Seven Cities Survey) were significantly different from the lognormal distribution (Table 6). It is important to note that the direction of the skewness of the log blood lead distribution is reflected in how the resulting AQS compares to that computed using the Pearson system. Negative skewness results in lower values than the Pearson system while positive skewness results in higher values (compare Table 1 with Table 4 and Table 2 with Table 5). On the log scale the lognormal distribution has no skewness; hence, when the skewness of the data is negative the blood lead levels predicted by the lognormal distribution will be higher than those of the observed data and will result in lower air lead levels. The opposite effect occurs when the skewness is positive. TEH 047003^ DUP050082903 -IS AS noted earlier, the Pearson system has the flexibility to describe a wide variety of distributions, including the lognormal. It is concluded that, in the case of the Azar and Seven Cites Survey, the Pearson system provides a more accurate' characterization of the blood lead distribution than the lognormal. 9, Discussion A methodology for determining an air quality standard for lead from epidemiological studies has been described and illustrated using the best available data on blood lead-air lead relationships and within population variation in blood lead values. The Azar study and the Seven Cities Survey include a wide variety of different adult population groups which provide a firm basis for the determination of an air quality standard for lead. The standards developed from these studies using a variety of models and assumptions are summarized below: Calculated Air Quality Standard (yq/m3) Study Average Range Azar 5.5 4.2-6.8 Seven Cities Survey 8.0 1.2-25.9 Combined Azar and Seven Cities Survey 6,5 4.2-8.9 With a few exceptions in the Seven Cities Survey (Rittenhouse and 50th percentiles for Ardmore, Los Alamos-Male, Washington, DC) all of these air lead levels are greater than 4 yg/m3. The air quality standard of 4 yg/m3 is considerably higher than the 1,5 yg/m3 promulgated by the OS Environmental TEH 0470084 DUP050082904 -16 Protection Agency (5) and the value of 2 yg/m^ proposed by Yankel et al (16). In the development of their standard, the EPA used a different and more stringent risk level than the Zielhuis guideline used in this work. They identified children as the high-risk population, assumed blood lead values were lognormally distributed with a geometric standard deviation of 1.3, and calculated the air lead level at which a blood lead 99.5 percentile of 30 yg/dl would be obtained. In making this calculation, the EPA used a blood lead - air lead slope of 2.0 which they estimated from the data reported by Yankel et al (16) who studied a single population of children which lived close to a lead smelter. The control population in this study had an average blood lead level of approximately 30 yg/lQO ml which is considerably higher than that of typical nonoccupationally-exposed populations. The authors of the Yankel study have concluded from more recent analyses that the appropriate blood lead - air lead slope for this study is approximately 1.0 (17), Our analyses (8) of the Yankel data and other children studies reported in the literature suggest that blood lead - air lead slope for children is approximately 1.0 and not signifi cantly different from that of adults. Since the EPA has identified young children as a high-risk population it is appropriate to perform the analysis described in this paper for child populations when the appropriate TEH 0470085 DUP050082905 -17data become available. It is also recommended that the proposed methodology be used in the development of an air quality standard for any pollutant for which the appropriate biological guideline is expressed in the form of a cumulative frequency distribution. 10. Acknowledgment The author wishes to express his appreciation to D, W. Marquardt for many helpful discussions during the course of this work and to the referees whose comments helped improve the presentation of this paper. R. D. Snee 6/16/81 TEH 0470086 DUP050082906 -18- REFERENCES (1) Zielhuis, R. L., Int. Arch. Arbeitsmed., 1974, 32, 103-127. -- (2) Azar, A., R. D. Snee, and K. Habibl, Proceedings of the International Symposium, Environmental Health Aspects of Lead, 1972, Amsterdam, 581-594. (3) Azar, A,, R. D. Snee, and K. Habibl, "Environmental Quality and Safety, Supplement Vol. II. bead", 1975, 254-290. (4) Tepper, L. B., and L. S. Levin, "Environmental Quality and Safety, Supplement Vol. II. Lead", 1975, 152-197. (5) United States Environmental Protection Agency, Federal Register, October 5, 1978, 43, No. 194. (6) Commission of European Communities, Council Directive of March 19, 1977 on Biological Screening of the Population for Lead, Official Journal of the European Communities, 1977, 20, No. LI05, 10-17, Brussels. (7) Snee, R. D., Report No. PLMR-10-78, Petroleum Laboratory, E. I. du Pont de Nemours and Co., Wilmington, Delaware, unpublished data, (8) Snee, R. D. International Archives of Occupational and Environmental Health, 1981 , 48, 219-242. (9) Chamberlain, A. C., M, J. Heard, A. B. N, Scott, W, S. Clough, D. Newton, and A. C. Wells, Postgraduate Med. Journal, 1975, 51_, 790-794. (10) Hammond, P. B., 0*Flaherty, E. J., and Gartside, P. S. Food and Cosmetics Technology, In Press, (11) Chamberlain, A. C., Heard, m. J., Little, P., Newton, D., Wells, A. C., Wiffen, R. D. U. K, Atomic Energy Authority Report AERE-9198, 1978. (12) Rabinowitz, M, B., Wetherill, G. W., and Kopple, J. D., The Journal of Clinical Investigation, 1976, 58, 260-270. TEH 0470087 DUP050082907 -19REFERENCES (13) Pearson, E. S. and H, 0. Hartley, "Biometrika Tables for Statisticians", 1972, Volume II, Cambridge University Press, London. (14) Hahn, G. J. and S. S. Shapiro, "Statistical Models in Engineering", 1976, John Wiley & Sons, NY. (15) United States Environmental Protection Agency, Office of Research and Development, Washington, DC, November 1976. (16) Yankel, A. J., I. H. von Lindern and S. D. Walter, Journal of the Air Pollution Control Associa tion, 1977, 27, 763-767. (17) Walter, S. D., A. J. Yankel, and I. H. von Lindern, Archives of Environmental Health, 1980, 35, 53-58. TEH 0470088 DUP050082908 TABLE 1 AIR LEAD LEVELS ASSOCIATED WITH ZIELHUIS BIOLOGICAL GUIDELINE FOR LEAD BASED ON THE ANALYSIS OF AZAR DATA Case 1 Percentile Lead Exposure Model Pearson System 50 90 97.5 Case i i Lead Exposure Model Normal Distribution* 50 90 97.5 98 Case III Linear Model Pearson System 50 90 97.5 Case IV Linear Model ~ Normal Distribution* 50 90 97.5 98 Blood Pb at Air Pb - 0 (ug/di) 15,8 22.4 26.9 15.7 22.6 27.1 27.8 15.7 23.2 28.5 15,6 23.5 28.6 29.4 Air Pb ug/rn3 4.2 6.5 5,5 4.8 6.2 5,3 45 4.3 6.8 6.5 4.4 6,5 6.4 5.6 *The normal distribution gave an adequate description of the variation in (Blood Pb)0*3, TEH 0470089 DUP050082909 TABLE 2 AIR LEAD LEVELS ASSOCIATED WITH THE ZIELHOIS BIOLOGICAL GUIDELINE FOR LEAD BASED ON ANALYSIS OF SEVEN CITIES SURVEY DATA ______ Air Pfc>(2) Blood Lead Exposure Linear Site Air Pb Percentile PbU) Model Model Okeana 0.32 50 90 97.5 15.9 23.0 27.6 5.2 4,4 6.5 7.3 5.5 7.7 Ardmore 1.15 50 90 97.5 18.8 26.1 29.8 2.3 2.4 4.2 5.1 4.8 6.4 Rittenhouse 1.67 50 90 97.5 20.4 29.5 35.6 1.3 1.3 2.0 2.2 1-4 1,2 Pasadena 3.39 50 90 97.5 17.5 25.0 29.9 7.7 5.9 9.9 8.4 8,8 8,5 Los Alamos Male 0.17 50 90 97.5 17.0 23.5 28.2 31 3.2 5.3 6.7 4.5 7.0 Los Alamos Female 0.17 50 90 97.5 15.2 20.3 23.8 6.4 11.6 il.4 5.0 9.9 11.4 Washington, DC 1.19 50 90 97.5 19.2 26.0 29,6 1.9 2.0 4.4 5.2 5.1 6.6 Port Washington 1.13 50 90 97.5 15.2 21.4 25.4 9.1 12.4 11,4 5.9 9.7 10.7 Greenwich Village 2.08 50 90 97,5 16.4 22.9 27.5 8.0 11.5 10.0 5.7 9.2 9.6 Lombard 1.18 (7 mo) 50 90 97.5 14.0 19.0 22.9 13,7 21.4 18.6 7.2 12.2 13,3 Bridgeport 1.76 50 90 97.5 17.2 24.2 29,8 5.6 4,6 8.0 7.6 5.9 7.0 Houston 0.85 50 90 97.5 12.7 17.8 20.8 19.4 25.9 25.7 8.1 13.0 15.0 (1) Blood Pb value (yg/dl) estimated by fitting the Pearson System to the observed frequency distribution. (2) Air Pb level (jig/m3) at which the upper portion of the observed blood Pb distribution would be equal to the Zielhuis guideline. TEH 0470090 DUP050082910 TABLE 3 AIR LEAD LEVELS ASSOCIATED WITH ZIELHUIS BIOLOGICAL GUIDELINE FOR LEAD BASED ON THE ANALYSIS OF THE COMBINED AZAR AND SEVEN CITIES STUDIES Case 1 Percentile Lead Exposure Model Pearson System 50 90 97.5 Case II Lead Exposure Model Normal Distribution 50 90 97.5 98 Case III Linear Model Pearson System 50 90 97.5 Case IV Linear Model Normal Distribution 50 90 97.5 98 Deviation from the Average* .0000 .0738 .1188 .0000 .0766 .1170 .1226 .0000 .0738 .1188 .0000 .0766 .1170 .1226 Blood Pb at Air Pb * 0 (yg/dl) 15.8 21.7(1) 26.1 15.8 21.9 25.9 26.5 15.8 21.7 26.1 15.8 21.9 25.9 26.5 Air Pb (ug/m3) 4.2 7.8 6,6 4.2 7.4 6.8 6.0 4.2 8.3 8.9 4.2 8.1 9.1 ' 8.4 * Distribution of (Blood Pb)*15 , average =: 0/ standard deviation = .0597/ skewness = -.02 , kurtosis * 3.81, The normal distribution hasi skewness = 0 and kurtosis -- 3.0, 1, 15 * (1) Blood Pb - ((15. 77)' + .0738) - 21. 7 TEH 0470091 DUP050082911 TABLE 4 AZAR STUDY ESTIMATION OF AN AIR QUALITY STANDARD FOR LEAD ASSUMING BLOOD LEAD LEVELS ARE LOGNORMALLY DISTRIBUTED Lognormal Percentile 50 90 97.5 98 Lead Exposure Model Blood Pb at Air Pb-o(V) AQS*2) 15.5 5.2 22.9 5.7 28.2 4.1 29.0 3.4 Linear Model Blood Pb at Air Pb0 (* ) AQS<2) 15-3 4.7 23.8 6.2 30.1 4.9 31.0 4.0 (1) Blood Pb (ug/dl) at air Pb = 0 (lognormal distribution). (2) Air Quality Standard - Air Pb levels (ug/m3) at which the upper portion of the observed blood lead distribution would be equal to the Zielhuis biological guideline for lead, TEH 0470092 DUP050082912 TABLE 5 SEVEN CITIES SURVEY ESTIMATION OF AN AIR QUALITY STANDARD FOR LEAD ASSUMING BLOOD LEAD VALUES ARE LOG NORMALLY DISTRIBUTED Site ,., Air Pb Percentile Blood Pb^v AQS12) Lead Exposure Linear Model Model Okeana 0.32 50 90 97.5 98 15.6 23.6 29.3 30.2 5.9 4.7 5.6 6.7 3.7 6.0 3,0 5.1 Ardmore 1.15 . SO 90 97.5 98 18.0 27.1 33.6 34.6 3.3 3.2 3.2 4.1 1.9 2.6 1.3 1.6 Rittenhouse 1.67 50 90 97.5 98 20.5 29.3 35.4 36.4 1.2 1.2 2.1 2.4 1.5 1.3 1.0 0.3 Pasadena 3.39 50 90 97.5 98 17.5 24.9 30.0 30,8 7.7 10.1 8.6 7,5 5.9 8,5 8.4 7,6 Los Alamos Male Los Alamos Female 0.17 0.17 50 90 97.5 98 50 90 97.5 98 17.2 23.2 27.2 27,8 15.0 20.6 24.3 24.9 2.8 5.8 5,6 4.9 " 6.9 10.8 10.3 9.1 3.0 7.0 8.0 7.4 5.2 9.6 10.9 10.3 Washington, DC 1.19 50 90 97.5 98 19.1 25.7 30.1 30.7 2.0 2.1 4.7 5.5 4,6 6.1 4.0 5.5 Port Washington 1.13 50 90 97.$ 98 15.4 21.1 25.5 25.5 8.5 13.2 12.5 11.2 4.6 10.0 11.2 10,6 Greenwich Village 2.08 50 90 97.5 98 16.6 22.7 26.8 27,5 7.5 12.0 11.3 10,0 5.5 9.4 10.3 9,6 Lombard 1.18 50 90 97.5 98 14.0 19.1 22.5 23.0 13.7 20.9 20.1 18.2 7.2 12.1 13.7 13.2 Bridgeport Houston 1.76 .as 50 90 97.5 98 50 90 97,5 98 17,6 23.9 28.0 28.7 12.6 17.8 21.5 22.1 4.9 11.8 8.3 7.3 20.0 25.9 22.4 19,8 4.2 7.9 8.8 8.1 8.2 13,0 14,3 13.7 (1) Blood Pb value (jig/dl) estimated from a lognormal distribution. (2) &ir Quality Standard - Air Pb levels (pg/m3) at which the upper portion of the observed blood Pb distribution would be equal to the Zielhuis biological guideline for Pb. TEH 0470093 DUP050082913 TABLE 6 SUMMARY STATISTICS FOR LOG BLOOD LEAD DISTRIBUTIONS FROM AZAR AND SEVEN CITIES STUDIES Data Set Log Blood Standard Skew Kur n Pb, Avq Deviation ness (1) tosis ( 3.) Azar Data <2) Linear Model 149 1.186 .149 -.35* 3.27 Lead Exposure Model 149 1.189 .133 -.31+ 2.90 Linear-Power Model(3) 149 2,281 .232 -.01 3.17 Lead Exposure Model^3^ 149 2.283 .208 -.05 3,00 Okeana 162 1.194 .139 -.81** 6.47** Ardmore 150 1.256 .138 -.76** 3.87* Rittenhouse 136 1.312 .121 .10 2,84 Pasadena 193 1.244 .119 -.06 3.42+ Los Alamos (M) 80 1,236 .101 .44* 3.05 Los Alamos (F) 191 1.176 .107 -.34* 3.95* Washington, DC 219 1.282 .100 .06 2.42 Port Washington 198 1.188 .106 .20 3.09 Greenwich Village 140 1.219 .107 .21 3.28 Lombard 208 1.147 .105 -.13 4.92** Bridgeport 147 1.246 .103 .55** 3.59+ Houston 191 1.099 .119 -.09 2.59 (1) For a normal distribution skewness = 0, kurtosis * 3.0 (skewness < 0 indicates the distribution is skewed to the left). (2) Blood Pb at air Pb = 0 (3) Results of power transformation - (blood Pb)*3 * Distribution not normal (p < .05) ** Distribution not normal (p < .01) + Deviation from normality significant (p < .10) TEH 0470094 DUP050082914 Figure 1 LIST OF FIGURES Title Schematic of calculation procedure for determining the air lead level at which a percentile of an observed distribution will be consistent with the Zielhuis Guideline. Linear blood lead-air lead model and 98th percentile are shown in the figure. TEH 0470095 DUP050082915 BLOOD LEAD AIR LEAD TEH 0470096 DUP050082916 TEH 0470097 DUP050082917 TEH 0470098 DUP050082918 TEH 0470099 DUP050082919 TEH 0470100 DUP050082920 TEH 0470101 DUP050082921 S'V'si ' P'60 - S kv*KA.ay. Stefans 3.20 A-+-3.Z8 ) / .73 Z ,f? 3 ,?H i .?/ f ,7f $ ,72- /0 ,<!? $ - 3; py, '^Vny 0" i* (/Uv''C&M* V< **V&*0 TEH 0470102 DUP050082922 TEH 0 4 7 0 1 0 3 DUP050082923 `Hoo^d? H e-Hod? W \j J\a Al L. Xi&Qu**ciU $v- & ef fcPt? 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I I ~ II II--.-- >--M--<-- | /? ^ 3. 8?U ~J LIC) Fm. , 2- I ,Z 9^30 ~Hh .\1.\ + ,1Ctq J2.( A f J.zg) 5 fCjo) - ,2624 (ll.li) 4- - 3. <9* S3 3.06 o ~Mv iz*J e Z&? /# ' TEH 0470106 DUP050082926 ftt-Z.ZS) & f(zo) - 3.6x4 (<}) ^ie) ~,^K./i/ Hie *" -3.Z-9 A 5 j. a^/ PA '& siatau = .4' . 2a - a.syg" t' TM > "J A {f(to) -. `ZtZfC?. &<t -3 - 5-25 TEH 0470107 DUP050082927