Document 6BwOjr8bLrD763V7ZKqmXByY9

FROIM: 366-3951 / TO: RONALD D. SNEE Engineering Department Louviers 5(185 ui) q u v JP^h j ^aXj UMf^k. d^v>, Ary'/ ^;V` N33755.01 TEH 0530002 Kv* ' * a vt-G*' ESTABLISHED W02 E. I. Z Po n t Z O NO u r s & CV n y & W t o n, DO V V O 19898 ENGINEERING DEPARTMENT LOUVIERS BUILDING February 14, 1984 Project Officer for Lead Environmental Criteria and Assessment Office U. S. EPA MD-52 Research Triangle Park, NC 27711 In accordance with 48FR43724 and 48FR56639, E. I. du Pont de Nemours and Company herewith submits comments on External Review Draft No. 1, Air Quality Criteria for Lead, Docket No. ECAO-CD-81-2. John M. Pierrard Environmental Manager Chemicals and Pigments Department Charles G. Pfeifer Consultant Statistician Engineering Department Ronald 0. Snee Consultant Supervisor Engineering Department TEH 0530003 DUP050030916 DOCUMENT REVIEW FORM Title/Draft Air Quality Criteria for Lead (External Review Draft #1) Return to: Project Officer for Lead Environmental Criteria and Assessment Office, D.S. SPA MD-52 Research Triangle Park, NC 27711 Coinmen ter /Organizat ion/Address * Chapter No./Title John M. Pierrard E. I. du Pont de Nemours and Co., Inc. Wilmington, DE 19898 Chapter 11. Assessment of Lead Exposures and Absorption in Human Populations RECOMMENDATIONS (1) Acceptable as is D (2) Acceptable alter minor revision B (3) Acceptable after major revision (4} Not acceptable If you have checked cither 3 or A, please specifically state reason(s) in the comments space below. fh. Raviewer's Signature Date Additional Contributors to Document Review (Name and Affiliation) Prof. Richard L. Anderson Statistical Consultant Lexington, KY 40502 Charles G. Pfeifer Ronald D. Snee E. I, du Pont de Nemours and Co., Inc. Wilmington, DE 19898 General Comments (use extra pages if needed, tut please be concise) These comments relate to the treatment of the NHANES II blood lead results and the associated report of the Time Trend Analysis Review Group, and the Billick analysis of blood lead screening data. We are convinced that major changes in the criteria document are required to accurately portray the meanings of these studies. Du Pont has conducted comprehensive separate analyses of the studies and is submitting, as part of this document review, the reports, "Analysis of Reported Blood Lead Level Declines During NHANES II and Their Relationship To The Survey Design and Gasoline Lead Exposure" and "Analysis of a Study by The Department of Housing and Urban Development on Blood Lead Levels of Children in New York City". We are further submitting the report "Comments on January, 1984 Draft of Du Font's Analysis of Blood Lead Level Declines", by Dr. R, L, Anderson, Professor of Statistics in the Statistics Department and Assistant to the Dean for Statistical Services, College of Agriculture, University of Kentucky, and former President of the American Statistical Association. *If comments being submitted on behalf of another organization, include that information. TEH 0530004 DUP050030917 General Comments (Continued) As noted in our report on the NHANES II blood lead study, we believe that the report of the Time Trend Analysis Review Group leaves the misleading impression that the reported 5-6 ug/dl blood lead decrease actually occurred, whereas our analysis, making use of statistical techniques and site location data beyond those in the analyses reviewed by the Group, shows that up to 70 percent of the reported decline in blood lead levels is explainable by survey demographics. Our analysis of the NHANES II data and our review of the CDC, NCHS and EPA analyses lead to the further conclusions that (1) the analyses reported by CDC, et al, which formed the basis for the Group review, are flawed by technical error and their conclusions are misleading, (2) national gasoline lead use is an inappropriate measure of gasoline lead exposure; site specific gasoline lead use is more appropriate, (3) when site specific gasoline lead is used as the exposure measure, gasoline lead use accounts for only 0.25 to 0.75 yg/dl of the reported blood lead decline, and (4) factors in addition to differential site demographics and gasoline lead exposure are responsible for some of the reported blood lead decline. As noted in his review. Prof. Anderson concurs with our findings on the technical errors in the analyses of CDC, et al, as well as the superiority of our analytic approach. The January, 1984 draft of our report, reviewed by Prof. Anderson, contained the identical technical substance as the edited version submitted as part of this review. For these reasons, we strongly recommend that the Review Group make appro priate amendments to their report after review of our analyses, and that the Criteria Document also be appropriately amended. Based on Du Pont Vs. analysis of the New York City blood lead study, we conclude that neither HUD's gasoline lead data nor the New York City blood lead data are adequate to determine a meaningful blood lead-gasoline lead relationship. As detailed in our report, we maintain that EPA's reliance on the HUD study is improper because (!) HUD used the wrong data to represent gasoline lead use in New York City, (2) the HUD blood lead data are seriously flawed by sampling irregularities, procedure changes and data handling inconsistencies, (3) HUD'S treatment of the blood lead data suffers from serious deficiencies which further contribute to the already formidable difficulties in proper inter pretation, (4) HUD's blood lead-gasoline lead relationship is unreliable. Accordingly, we recommend that the Criteria Document be appropriately amended to more accurately reflect the significant limitations of the Billick studies. TEH 0530005 DUP050030918 COMMENTS ON JANUARY 1984 DRAFT OF DUPONT'S ANALYSIS OF BLOOD LEAD LEVEL DECLINES R. L. Anderson* 1. Model (1) in Section IIIA is better than that presumably used by CDC/EPA, because it includes between site effects of the within site X-Variables. 2. The use of a two stage procedure is approved because the between-site X and Z values are orthogonal to the within-site X variables. If we have an X'% matrix As follows: Xw' Xw X"-Zw This two-stage procedure avoids the necessity of using a more complicated weight matrix. The latter would be needed in a single-stage analysis because a two-stage sampling plan involves both within and between site variance components. It is quite possible that the use of between site regression coefficients as well as within site regression coefficients will reduce the size of the trend decline in blood lead levels. Statistical Consultant, 33119 Braemer Dr., Lexington, Ky. 40502. February 10, 1984 TEH 0530006 DUP050030919 2/ 3. When we now append a vector, say T, for the linear trend to the W-part of the above matrix, we note that (X^ T) and (Z^ .T) will not be null. It appears from the discussion of the CSMB -procedure that T was not adjusted for Xw and Zw ; if .so, the CSMB - procedure probably will produce a biased estimate of the linear time trend of blood lead levels. On the other hand, the unbiased estimate of this linear time trend by adjusting for T and T (as I presume was done in the CDC/EPA procedure) may not provide an unbiased estimate of the change in blood lead level per unit time. In a multiple regression model with a number of X's and T, EY = ZB X + V = Vl iii btT' b^ represents the predicted change in Y when X. is increased by one unit, provided the other X's remain fixed. Unfortunately in the blood lead problem, if we change T by one unit,.many of the X's will change; hence, an unbiased effect of a unit change in time probably is not bfc. There is no known statistical technique to handle the last problem, but I would examine the X, Z and T vectors to see if it is possible to obtain sets for which the row elements of the (X(Z) vectors are nearly alike. Determine the population weight and the value of bfc for each set. Then weight the bfc's by the population weights. This weighted average b^. should have less bias than the over-all b^; however, its variance might be increased so much that its mean square error is not improved. This is a problem which should have been understood before the survey design was selected. I believe it would have been possible to select a survey design which would have minimized the bias in b as an estimator of the true time trend in blood lead level. TEH 0530007 DUP050030920 3/ h. An important aspect of this investigation should be an attempt to explain the decline in blood lead levels over time by one or more causitive variables. Time is an innocent surrogate for unidentified causitive variables. One such possible causitive variable is the amount of gas lead explosure. I would hope that something better could be used than site exposure based on National Gas Pb. Hie site specific variable suggested by the Dupont investigators appears to be more useful. I would like to see how much of the decline in blood lead level can be attributed to this site specific gas lead variable, when the proper adjustment mentioned above for T is used. One computational procedure is to determine the value of b. after adjustment for gas lead as well as the other site variables. 5. I would also suggest that we analyze gas lead in the same way as blood lead (i.e., gas lead as the dependent variable, y); then perhaps we should consider a canonical correlation between the two regressions. In other words one essentially has three regressions: E(blood lead) = 6^^ +B^T; E(gas lead) = SsiXi + 8 tT E(blood lead) - BE(gas lead). I am not an expert in multivariable analysis, but it appears we have here two random variables (amount of blood lead and amount of gas lead), with a large number of non-random causitive variables plus T, the surrogate for other un named causitive variables. Perhaps there is a better procedure to analyze such data than using multiple regression. I feel that the CDC/EPA report dodges the many important aspects of this problem. I sympathize with anyone who attempts TEH 0530008 DUP050030921 to analyze data based on a poor survey design. I cannot understand why there were not some revisits to the same sites and if possible to the same respondents. I thought that the use of overlapping samples was almost obligatory for detecting time trends (see the work of Kulldorff, among others). 6. In this respect, I was asked to comment on the need to consider the survey design in 'the analysis. I realize that many of my colleagues would advocate such, but I doubt that the improvement in estimates would even Compensate for the added variability induced by the use of estimated weights; for this reason, I applaud the two-step procedure by the Dupont statisticians. 7. Finally, it appears that even with the use of the amount of gas lead in the analysis, there may remain a large unexplained downward trend in blood lead levels, I suggest that the model include a(0,1) dummy variable for before and after the late 1979 regulation. I would also attempt to discover if there were some other variables which might explain some of the extremely high and low blood lead site values (Figure 1, 2. and 3 in Section III). TEH 0530009 DUP050030922 DOCUMENT REVIEW FORM Title/Draft Air Quality Criteria for Lead (External Review Draft #1) Commenter/Organization/Address * Ronald D. Snee Charles 6. Pfeifer E. I. du Pont de Nemours and Co., Inc. Wilmington, DE 19898 Return to: Project Officer for Lead Environmental Criteria and Assessment Office, U.S. EPA MD-52 Research Triangle Park, NC 27711 Chapter No./Title Chapter 11. Assessment of Lead Exposures and Absorption in Human Populations RECOMMENDATIONS D 0} Acceptable as is (2) Acceptable after minor revision 0 (3) Acceptable after major revision (4) Not acceptable II you have checked either 3 or 4, please specifically state reason(s) in the comments spece below. Additional Contributors to Document Review (Name end Affiliation) ^v^^sS^nature ' Date General Comments (use extra pages if needed, but please be concise) 1. Refer to end of Section 11.3.5, page 31, Reference to analytical variability and associated impact on misclassif lo cations is important. This discussion needs to be extended to other studies as well. In our comments of January 31, 1983 to David Weil on the December 15, 1982 draft of Chapter 11, we offered a table (Table B.l, page 31) comparing variance components for six studies. We regard such a table and improved discussion of analytical and person-to-person variance components as essential to the Criteria Document. Attached is a copy of this table. *I comments being submitted on behalf of another organization, include that information. N33755.03 TEH 0530010 DUP050030923 General Comments (Continued) 2. Refer to Table 11-62 Reference is made to Snee, R. D.; Pfeifer, C. (1983) regarding a statistical test that detected no differences among blood lead-air lead slopes over many studies for adult males, adult females and children. This reference is based on our comments of January 31, 1983 to David Weil on the December 15, 1982 draft of Chapter li. However, in spite of this conclusion. Table 11-62 presents a summary of blood lead-air lead slopes for several studies without putting these slopes in context according to our result. Further, the Roels, et al (1980), and Yankel, et al (1980), are inappropriate for inclusion here because of their inherent problems. 3. Omission Charles G. Pfeifer should be included as a member of the Scientific Peer Review Panel and contributor to Chapter 11. TEH 0530011 DUP050030924 - 31 - TABLE 61 VARIABILITY SUMMARIES OF BLOOD LEAD VALUES Study geometric Standard Deviation TTJ "" (2) PT Number of Overall Analytical Person-to-Person Subjects Populations NHANES II 1.365(4) Azar, et al (1975) 1.354(6) 1.301(?) Yankel, et al (1977) 1,293(7) Tepper and Levin (1975) 1,304(6) 1.313(7) McLaughlin, et al (1973) 1.531(6) Johnson, et al (1976) 1.549(6) 1.155(5) 1.227(6) 1.155(9) 1.268(6) 1.493(6) 1.476(6) 1.317 1.250(6) 1.180(8) 1,237 1.127(6) 1,143(8) 1.156(6) 1,222(6) 149 880 1935 217 241 5 7 11 23 6 22 (1) GSD overall * exp (aa + a*; )^2] (2) GSD analytical - exp (oa) (3) GSD person-to-person - exp (at) (4) Computed by Du Pont (see November 12, 1982 letter to Dr. Weil regarding comments on Chapter 11) (5) Computed from NHANES II blind QC data by Annest, et al (6) From Lucas (1981) (7) Pooled from GSD's presented In December 15, 1982 Criteria Document Draft of Chapter 11 (8) Estimated from (6) and (7) (9) Value obtained from NHANES II and used as a conservative approximation to evaluate the person-to-person component. TEH 0530012 DUP050030925 ANALYSIS OF REPORTED BLOOD LEAD LEVEL DECLINES DURING NHANES II AND THEIR RELATIONSHIP TO THE SURVEY DESIGN AND GASOLINE LEAD EXPOSURE by Charles G. Pfeifer Engineering Department John-M, Pierrard Chemicals and Pigments Department Ronald D, Snee Engineering Department February 14, 1984 E. 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KI'OCCoNlAf4tO'l<>MMfti-l-fi4M>(lKWnWflWNNOOOOObWANNNNNN^^rtNNllAA U|tfbHOO`04 00'NNOHKl 'Oow<fNN<OvOKico.o*O'iA0`<rfla3oaJw<Mow.j"tnftj^HH)NN'Tj(,0e>o f-<faOjHHUIWO'sruiHlOa)cONKIrtCO'4 e gcgcMcgcjcucjcgcMcMcgcgcjcgcgcgcgMc-jcgcjegcjcJcucjcgcMCucsjcgcjegMrN -r in rp'H-AH'Xw.'O co Z NmoiswoinioosrsffsoNNOoaCjOifIiAnNoOnNONNOI<ltACVlJno(sIAO'rOU)'<0 u CM eg OJ eg CJ eacMcacgcMcgcsjcjcgcacMcgcgcjcjcg < O COOO^IMfOriftONCOOiHOH<l^tJtONOl>OHCJI<ltUlION<00'0.iHC4lO^.UlONQi>OAlKI<rtnoNOO (ft ao N <0 C O H NlA<|,IA4M)OHO)KI>tlA>ON!O^Of4Ml14>lA>OM)0'Oi4ftJlh>tlA<AN<O9>O>J.MtA4tA4 TEH 0530199 DUP050031112 Mp- troO HH 0'' CD <a H< V> <n S S UhMJ- * go o3. > < 3 U-?J UJ Z* 3o tzs UJ Iu <t <o to o <r OHO O CJ ouo o e e o c> O 03 KI H I"4 <T O (0 ^6 U if) O' O Cf* ooooo tA tO <0 \f <U k sr 0* r** O W h> M >5 O 0s 0 (0 HOOO0 odooo eppo<o <r ino >r ** iA IflH O ^ <inr m<oeof *oo p n o oo o o ** * 1 O t O N O' Kl ^ tr*o* <nS-I <r-Q O<o *0 U XU sJ <U <!M #"4 flO *4 H O' <0 P H ^ H CD N (M sj CJ CSJ CU M o> rs p* <o to Kl O H rt H Pp* mO' (U Pr* tMo in so m m ir* oo o o o ooo nXS*J mO' 0csi -X<SrJ <Irat* sr <r m m p J N N <J M to <f f*l Utt 0O' CO0O' mM fs. o to < <f ^ <0 K 3 W N N O rt UlKMAiAO <U C4 0J X4 W * Ow3in in UoJ; _<j a 3amm u3aj UacJ Cin7 SBmcoo hm m ^m O-o H in in TEH 0530200 DUP050031113 0 Between Site Model Survey Demographics Only Ordinary Least Squares Dep. Var.: Adj. Set 2W H0e Y100 '< a tft oS S3 3E s <UJ fS a ito eg s* to m QV) a % 5 < SC M Si 5> 3 Ia tn) UJ 1 J 3 DC s< uh-i u. oZ UJ Si s UJ J a o o 00 I H Kl 5 N IA s; ui to "<<UI sc tft N HU1 S3 ui 9 Ig?a li 11. (ft OfN 5|C> Ui 1ft sf ft* in > 000 Kl 1ft 0 in n o gHh H09 z (ft a MH 00NH *o"i egeg (ft ** 0 3 s*.UJ z S3 UJ M g? 8 a. > z h* afUiJU WOO l DC H > OS : ui o N^09>i HH O H i i N |H O O < eg m sr 0 0 0 m eg 0 ' eg o <o 0 0 o n * 0 <f touiOh U)>0nOHH<0O(0c0inM0MJ)O0'ON'fO^ o <0'T t> n in n owqge-p'Ori^.oNsONgg O O A H 9 O 6 0| 4} 10 O Id Q O .U) O H O g <t In H O $ A 0 00 00000000 0 0*00000000000 8 IA Kl 0 # HK) h^HO-tfhHIOOUi^g,<M^KK1HWKlNN<0K1'<r Kl^9<^dNQONOHU)iHHlA(OgNeh7inc*q iOn HeHHNMei Oi HNi OeOi Oi NHi Hi ODOi HHOi -I II is I OUlHHCMHO'lO'Oinf30(O^H'OOhm>00HO4 lOOejOMANOO0MAHOU)^NOO>7itnH h(Mngoino><MOH0o^hH>eenoKiH.g 9 9HonlfliOnHmlOg Weg HOeiP'lNrteH<OWUhiHh'iNAOOhH'Oe'OopOeJMoortog ooooo 9 ' m' mj l<J|SOOOOl SH tj sc 32 CL 0 *-< 0 0 eg 0 tfteo 1ft 9N 0 n in tf Id UI KI CJ Kl O *f M N 0 0 0 h (ft 0 Ift <0N Kl 1ft *4 Ift N0 9 0.9KI0N to o 0 r* n ><0 ri N 0* 0 Kl 0 N N N dngQHNOh 0 0ui 0 00 eg H Kl 0 iH to 0 JO o <r Ift 0 h* <-e to 0 Q VI N .M h Kl l> 0 O 0 Ki eg 0 eg eg 0 N .0 in m 9 ST fH m 0 Kl n eg gWHHQepO JOOOHOI ION d d eg o e e d o e o O to H III I to I a1L HHHHHHHHHHrtHHHHHHHHHHHHH eg * s * At e1Ig X * si gg to UasJ faie<-I IU 3 e (A UJ fit (A zUJ NH 0 MVI o ss | 1ft u OH ss O 00000O 0O9H NOM00 9HO0H h 9 O Kl HI t0omo oti*not o9o* oh0n oion* poo 0 N l/l if Kl 4 NNO W O0COKIN r* N 0* /S O N<ro*f o 00000 1 10 9 0 e ri o o n n <r o 0 0 HH0O9 W Kl N IO W (J0000 O00H1N0* U9 l 00 eg n eg eg <a Sts oUJ M P UJ is *H 3H 25 9n 9 ' N 00.gnn 9rt K0l9H4OMeg OO00 o HHOOO dddd o 0 in k eg 0 M CvJ 9 1ft to o in ft* o eg eg eg eg eg m o k 00 9 t> O 9 H hh g NN eg eg eg eg eg H Kl 9 l/l ifi HNKI9W TEH 0530201 DUP05Q031114 M 0 00 H-4 0 5 oS ss WH UJ 0 * a pUJ 0O 0O 1*1 0O O 0CJ 0 .0 O O 0 O t IAJ 0 0 0 f* 0 0 IUJ <0vO 00PN1* W t0 OUJ 0 P0 0000 0 Waa 0-Sj 000000 b0 <r*0 NO r0t 01A 0>p g'S0 00 O<M 00 O OO 00 SSI'K 0 0 H0Ifk 0 0 UJ 0 0 UJ IX .OM0 0 o o oo 0 o r* 0 0 0 > NOM O- N^ CNJNbN0O0 I ^(0 <t O N 0UJ I a. I N000 lUMOe asUJ fir & N*tM<tNiA Mfl -y > O N 0>NNN(0N N AJ <a M N M J < 0J N00 hOM* HO^IAQM 0 H ^ 0 fs p4 f AJ H N N. (*J SS OJNNNAIN 8 C gg0 0 0 Z UUJf ah* ap (0 ^ it 0 ^ s000<Or 0o0 0N00o0>0m0 S30UJ 0UJ p UJ E.E 0 0o oP* 0 0o I* I0 00 ft. U3 o h*O4* 0h0 0M0 0M0 000 000 * ' (yJNAJNCJAf 00.UJ 0COJ 00 o. 0 io 0 0 rv 0 I *0o 0w 0r> 0N000H ftiNNAJNM 3 O 0Oi-4000 0000 00 0a SS 85 0 0 0 0 0 00 h> 0 0 O p4 TEH 0530203 DUP050031115 APPENDIX 4 Corrected Site Blood Lead Means Versus Mean Examination Date Based on Between Site Analyses With Survey Demographic Terms Only Adjustment Sets 1, 1W, and 2 TEH 0530204 DUP050031116 TIME PLOTS OF CORRECTED <BJ SITE MEAN BLOOD LEADS (CORRECTED VALUES FROM MODEL " 1 " ) Kl Kl 9* <P0 s uUi Oui * 5 8 g j 5 Corrected Site Mean Blood Lead (CSMB) Survey Demographics Only Based on Adj. Set 1 N Uu O0 U U u * < * r> a U (ft CD * +Kl + sM s + ?> s tu 5 N *O NCsJ. I Ui . rrx** i $O + <0 TEH 0530205 DUP050031117 NOTE: 1 OBS HIDDEN Corrected Site Mean Blood Lead (CSMB) Survey Demographics Only Based on Adj. Set 1W TIME PLOTS OP CORRECTED ( B l SITE MEAN BLOOD LEADS (CORRECTED VALUES FROM HOOEL " I N " ) MEAN EXAM DATE Ou K \a P i j Pf Ui 8 o u I$# I rS1*0 PP 9IIS NN s uu I i !> oh** 8 Pu ;ss uu ! ? uu P uo pp up p p p p p p p p p o p p p 4Q IN *II No4 II IlII uNt i IS I IV Io IN 1IItI MM II Nf* II oH ! ft p p p p p p p a p y p p p p pP p p III iNNv X10 I iH 3t)II * i rv<v0 oO *- X (ft :+ -Ik------ + -Fw - m4> O H fv HH + -------- + in & HH p o t ac as -- + -- -- --- + Om HH + IN 40 I r-i HUI TEH 0530206 DUP050031118 Corrected Site Mean Blood Lead (CSMB) Survey Demographics Only Based on Adj. Set 2 TIME PLOTS OF CORRECTED (B> SITE MEAN BLOOD LEADS (CORRECTED VALUES FROM MODEL " 2 " ) lft <0 O' aa s? 5 2 S *01 1W t * Om & 3 CL U u u uu ou uo u po u u o o u u u *a IN 8 8 itt s . Of>' i 5a 'H Pes 3 rUJ $ NhNH NCM 2 i* N u u + 5' -% t3 A 8 O' eo I*To) 'O iA V IA 9 cr IA ro CJ 61 6J CM CM u w r 0 lU i TEH 0530207 DUP050031119 APPENDIX 5 I Between Site Regression Summaries for Models A, E, F and G 1 Weighted Least Squares Based on Adjustment Set 2W .. \ ? TEH 0530208 DUP050031120 Between Site Model A Untransformed Gas. Lead Exp. Dep. Var.: Adj. Set 2W 1 3 !3 1 SATUROAY, NOVEMBER 1 9 , 1 9 8 3t GCUR75 COMPLETE RECORDS FOR BLOQD_PB, VARIABLES 1 - 6 , 2 2 - 3 0 , 0A Y S _P B , LEAD_MT, # 3 1 A : 6 ---------- A L L COMPLETE RECORDS EXCLUDING THE TWO NEW YORK S IT E S 1 9 6 N^.O N NWOO H O OO 8 ** oeoo CM $ ou'ke9>Moo*0eHi/i'tM)(OeomKtoK)s0rt<O9'Hin O ^ N H H H O tfl >Q 4 Is N h It) <0 ^ 9 M O H 1) HX O'TOHWWfdd'WfgOMAOlrtHWCslCHO'WN^WH OHlAHW^dCF 0fNW<rN0rtH0 O^JMH O in Ifl N Od1 W MiO (OvOHON<r<fNO)in.l>HHCO' h~ -I Z< u j z> ON* o0** 0* cm Sr>f o rlH H N W N Lfl N CJ rt ^ sf W o3 o*-< H Q O O H* 10 tft.iu ma oM.HOUU0>n^Of'tt'OON* O(A H^I^NMNl >N0 ^^^IAV(UA HAIO0C AS<<lIKA IOhNe 0<OHO<f.^NOU).M<U<)<l'9<0<OIANHOHrOK1 lfm0O(0<fftJ0'SNrtc0e0NXl4SK1l<YWlfNLnK>H a -J a uj D* o Ow h- m 0 fro N O o O CM in O m >0 in Ort KI N i0n .0m 0co0p* MiAca*tNiA^^*r!iniA tn.m HN.ni<iinH(w-<rNio OOOOOOOOOOOOOO O Oi 0000000 0000.9) UJ x o <* *- m < F-4<6eO<O0'HOt9k'0Mt'Ms-COCMlA,Mlf|lft<riAO9>McQm o<roinwo'ri.MomcO'OHKiff*.NP'vfiniA^irid,MN < [<o <p p- m in OOOM s? 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O s O iH CM P* H *n eo O in CM 10 C* in O CM U) O' <t0g^c<TjHH C'jM'i^AcaKl^(QQrlHQeifte9oIpMo/I in *6 d* CM oo o o I HNHtf)KUON<rOOOOOOOO mm* UJ w _ OM1 OCM t>*0 H oomo HHOO OOOO P Q N <6 O-IoN oin <|N0 0u. <ft UJ QC 53 in cr in <t HP KON Id 'Q H 0 0OdriA CM ^ <p in H CM 00 0 o> *r n in m H CO <f K> <0 - *c m in m 'O >f N rt m > sa ss UJ M Of a5 UJ o a. oz ;UoJ uj 2 s 0K mJ a. > UJ < O ui * 00u mk h a 0&5 IU O OQilr 0 OX 0in e u j X UJ UJ K H< uj Z ZM * h* oc in < UJ {L rNm0mNT Ooi0c<rnHmrr*Km<-mUm~0Y*1l0:M^r^tHOH<(iiOHnPHWO'c(oNOMN<pA0in.OO<o5PNMf>NH-KNuKHai1f/3fIH',.-AOpIAN^HI^fOitn-K'JwU>Ii/HNMIH^A-0ejOHoO O O' M) m m p* ^) N Kl k m (PoHnP* CM CNM OPOO OHdSeOHftlNbOl m co in o M'NOCP N N Ml N IU a _j UJ 2(0 u 0 10 <, X ^ Uu Jj _ Xz < X Z Z X Z Z Z Z Z QC CD 0? uj Z uj X in in UJ H u u i u mZoOri)hHUJ-MH.H< hHthhl-QK < > > < J H ly 0Z -J < X UJ M z >* (*J z IH jej|jajI.c<Q.1 <}Q<cI oI sZIzcsI UuIQtH-SaoZ,zB5mgoi2niutmfo)zKuz<^iu3o in h mi o p Q o TEH 0530209 DUP050031121 *3 i -J >- o <i-UtULrt"-)tOf-WOMOCftilOf|eI'fJl <nOrOHrN-lC-O,iOOO.trfl-4OHWNr-(<>-HlH^rOtOHOV'HWOW,W0ON>H-4Oi-4N9<*tN*i-O4>TOH*-4WONOOaH<'tgNH-<OWinW-<O\ilrf-l<f*OHfl * OOOOOOOOCirHOOOOOOOOOOOOCiOOO i<V OOOOOOOOOOOOOOQOOOOOOO < o o oodododoooodoooooooooooooooooooooooooddodododododo v u * ift r i p Ui fc; 4 to * * 8 S a *.s I s* *** * * ** *** *** ** * ** * >* <u m3 iU J in z oPE V) >* z* Ui ^ j^c*oJaili<r^tNvOin^f^iifrt)M)tnH)&'4Win)ft^^n'<OtnrO00<l'6As'UOJ,^lrN-*r-HO4KHKl?ilN>i(>h^-o4}0vK^4tst,*r9iN0`0<<`\&MjouO^,r>HciAuWONKi''>O14NUf*)mfO*>vrdr+4FNo<^*r^>^N'o-4rt'iOd>NtWAir}*CCi'MO><4<utOft>c>sirj<N,ov<j<0&OH<SoOw')<VOQoOkkeaOvO)^j'o`^v^-*0tir^*<tonOKr4tifr;*tt ss OrH0OO<H0 0Kl<-l00'`-4000 0 4->*r-l00''1i-44 00r-IOCMOOr-*0'>40O000OO a* vi te2x i a-J 2g Ui 3 UJ a) UJ 4 9 W H tO <0 UJ a 2 dddddddddddoddddodddddddooddd ddddddddddddddddddddd IO'Wlf)iJ')rtO'Off`0*0*'JOMO'0`<ONH\rWH>OOSrtH<Ols<hfl3<Ort&>0'0'?O^N>f6MO ) ^ Wl i CIS > M >A IlS N Al I'T A n 4# At Ifl .n IA (M ./I ai .A M ^ ^ ^ ^ (J ^ |>f |j^ ^ |y ^ Ka> M0 <p0 MM \^f ]) UO AU MCM *A-4 Ain M<0 I* W^ $ Ut KO' CIr*t I>Ar <^M <>uJ f('A*' ^\J fA# <o O n w o r> mQO'inKi V4 O O O O 1 .V V- U4 sy z--aJ ss aa. aa; p' -j <c o NlA U - 0* PO4tAN0PlOUlrtN<MKINtfNiiMeQ^MH^4>VMAO9>^(OOddN0IAlAU1MNMMQ><td<fO>^4Kl n04lfllNMltO0ONliOnNM<fHtJOlrINNCH0MN4W,<l0<llfsi<r(04WNi'nfO.NNIO5^HI<rilnNpMlHrtKO)K'34,<Ntan`<MrMf<l`trrt4a>-<4l>flrNtKWMCA3.KNtH<HMIWO>^H(0in(0NOn4`0rNOKHI g gitut tt.Q ss o a. rjCdftittCsttjWttfUMf-tftJCiftJeJ Cviw <SJMMAiUNMCUCSt<ijCUJMM<M<SjUiMCS|iUMaCsJW(UUU<lid<vd tf) a iniorseiNt^iAtfiMmtfimoJsriA oi o HHO(M4NnAOi>no^itia9ifl>otAoui<aiHiA<t*oiAui9|N9tnH0>in g MH*0N<t<fU\O<043O4l/1(9l0(M(l4,Oin(0(0NU)N9>N0>4Kia}<0HNOHHt(1N(0(0OAIl/|},N0'^lA.<{uo UttI aHv) mfaUna*.: wcvmf>.or^co47*or>ri-Hor,^-iH*o'or-.-orc,-c>irw^oowv,*owcuC`minwsr^>oinr^if>w^<7,o^-'r'jw nH<},.e(ONOH<d.eN^MiNN^H(0^rtNO>UHANNKn<l>6N<rdn<gH09><OiOIAOO>NNN(jN<M sO 'O -^ O '0 rs m ^ in o o sf <fl >o >6 <o '4 ui 'O O ^ n ^ u> w >j n m m , ' o> w <1 r> r so f> 'O >r O' o* o ifl >io o* OOOOO0O;OOOOOpppOOOOOOOOOOOr4O0OOOOOp-<OOOOOOQOQQQr4OO0 00000000000000000000000000000000090000000000000000 Ui H Ui up fK-4IpN!AHfS.KUI,IC>Pi^fHrtp<P<<lKfr>lUHH4NlWIA9^Nf-Nng9iA,.nlApPVIo^W<0W<OOW^HJN9k?POp^0H'rN^rf*4tPiOU,p>Oi<OOP<p3^,r4in<-t4OrHNt\i<HK4IO,tWflNOHP)lA6MN Q_ c <8 Ma -<J .'O'au)'O4''OiA^'twPsr*tv9Q<o.N^v)in^'6U)'C4rM^4'NSN^>9<0Q)ui0N^`!fifiH<rN<o4N^<6 o Ui > c\j<xj<\i<vc>i^^J<iM^isi<^Muciweiiricai<siwcucuei^j<si<siuesiM<^<j<uNruru<sjdci^jevievi<^eiti<s<csj<Si u eax * <HdNH4OKMI^<9r)N0N4<lAOM<O4.'I'(MMOA9NlKOU'UAld9<>s6r)aO3a(,O>.0O><qD}(gK^l.Mrt(r4t<Mr(eAe('Ol4HlA0N).NN<Krei'3M<<JlO,<>OeilHAH^OUHUOft^(K^UO\'eHOrOOl>90(O>NNftmM.IH) p NN'fN^riA<r!>H<0H'jUl>0(p4>M*)<ClNU,l<inmifl4rrN'J).N^.CMnN.O><0N.N>0HlinNin<Ni(l'6't>0 *j<vjcj<u<uejt<gajej*ji<uftJAjcsiCNJCU<UMC4u*ieitJ<JC4&iNdj6i<sJftj<ittMCi<vj<\Joj.*i*j*J*j4<\j*JC\iutJ WNOeHNn lA>Oh4)9>OHUl I 1A l /> ^ M fS n FI eoO HHHHHHrtHriHNWNNWNN^WfaMiniOfniflrtM tfj -4 <\J W tAONtO^OHNM^1 TEH 0530210 DUP050031122 M ,1 (0 <o r4 O' O' ri 0C >*C 0 1 < . K I in fH i a* Af w in ' o fj ^ O OOOOOM OOOO 88 o o o o o o o 0 ** r-l 1 N f H Ifl W O W x < (M> >6 tfl N sD 4 41 0 Kt io-on o r> to *3 a" aa M 5w o *4 a o <a . tn to UI oc J 0 tx -j N CMn Kl O *0 N m os .< Nrt N M W H U* 1 Uig 4- m 0 4 o' ca OH O' O f"4 0 .O' IS '- OHHOO in ui . K o o o o <0 5 .-J M C4 < rv M 4* O' O o 0 n O' O' 4* rt a: a *H m to 0 M m 4* fs U 10 0 O 0 O UJ Ui a in a 10 9 1 Ui OKtOh <u O H u*i u S r* O' M H <p O* o 4 O' r<NM a. 0 O Ui Ui (gNNNNNAl Is o S"u .* in u rtC0K>NWO <-J in is *' in o j O m m in O' M Ci <r H K1 N i Ui a a a UJ UI 0J<UCU<VJ<VC4C<J 3*p 2 a Ui in t* a OS K <g i/i <r <0 Fi o N I au Ui n _ .a o i in <o i N H(MO0KI KVH O O 0 40 CO O' 0 UI O' 'a lO Q. e o o 4* #" > 4 44 4 r* xCOr 4iS* S r 8 = cj ea O j O j <g cj oi 2|M 0 -J >4 in 4 4 N (0 o 4BC 4 w Ms 4 H p in sf I (J M N M N (M N M UI a s2<3 3a) o> e ' n mo ae fe ju 8 r* o d .' OO TEH 0530211 DUP050031123 Between Site Model A Transformed Gas. Lead Exp. h l Dep. Var.: Adj, Set 2W j o <a Csl O* Ui 1 g 5 r* f> to r- mo (AHU) UJ h U> z os a: Ui U2J: a 8E V) > Ui S a 3 H IU UI I H V0) w Z UI 9 -4 U 03 Z 5 ia. 8 3 (O a a y Z Ui >" UJ -j a. iCOnM O-4 #COM &COM CM H ut Z ss 25 a -j < u. >Z O H Kl <r O H N1A M <A M 4 ^ ^ N N N 4 H N O<0(0 9`H0>N<4^(00)<JHIA<0MM(0^<0HOHH O'0NM0'C00-0'HO(}qW^NHNr0>a3NlA'0UUf) O(OIA(OH>OH^HO<0^9,CilAiA(O.<Ortrt.(O<OONN ON^MIJ'ONOMOONflN.HO'P.W.Otf.rtHNNO om<od`Hin<o<roH'fiC'0>oNOinoHOKi<oM'5fin Oldpiliei)nr>iN<tl(UHHHNNOlAiAfOKI<C 'JN Sfr Is* UJ KI|flHNNNMMHVl'tHrt.WOqi(IN<(Mn)0 1 W7`9WHHH*>HWlA^rlNIMnHlAW-OCf'WM JdHKi^W>J''0W`0Wf0H'J,(00'^OW0t0NOK1M .co<rmintoiM.Q*f>csimois*oOkNmcgc4.tfiomcjK CM U1 CM Nf CM tflf W.OH^rtlflrtNSf Wi-4 _J P 000000000000000000000000 * CO o tu 3 i1n0 M <0 N<0 N N U) OO X< UJ at ui r .9< oM o M3 0 o rv o <0 O 0* 05 f-* r* UJ 9 8wi 5 IO Of <4 U. 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H<^OO^OlOH(JNN'A9><ONHIArtlOOONfA4H(l)Uin>0NM^N4Ut^HM>nS^nK)^9>'fU)N r<H9>H<9li9,in<!rHI<)O*fO8)O0'OO9>\OtA.9,O9>O>0NO>eN^^eMAClAKH.H^H^N^^)] 0!AO>00^0-Or,*fS>09,>in>OPU)P.^9>'00d>0 009tP^*AIAKI0.%0(,^OiAU\*0.vH9ktAr^N>p43N'>0.^.0 0 HrlOHOPOOPOOOOOQOOOO<9OOOOOOOOOOHOOOOOaaH0OOOOOOOOHO OOOOCOOOOOOOOOOOOOOOOOOOOOOOOOOOOO' ooooooooooooeo MNHW N!-$ Htt*><P`IAsTr-!!AV)*4'*4`ej'?*>'>'O*HcO'6*lAtAl*l)<0*'6egf'v(A0P'*tn*fMAIiNIAT>,eb 03HK)OH>yO'TrtNMKlCOHOHK\HNflJ<Mrt^31fl'OKlOf-<<OinHH^<0(0 COW COlftsOlAOsOCOW'OLAo O' -- 0 K U1O^Cl'OtA'O4,-<OUl9>SflAO^tA^P>ONi!r.tA*AU)<4*43U'OsriAs0 h>N<rsON}^N''<r<AH<tlS<d MMNMIAlig<NN<UM<VNN<aN(MNMNN(<JNNNNM(vJMNNNMMii<UN<vtMMMMNMMMMNMN m HKlSflfl^rvcp^OHM4'iA'^NeOOHPJrt-ifU1'eN<00`OrtWlO'sf^'ONCOff1OMNrrtNflftONc5ff`OWW V) INK>4'lfl'dN{O^OHNM^tfl<NrtO`OrtWrt<tW4)S)OOi g HrtHHHHHHHHNWWWWWWNNNlOinlflKnOKn J lfl vfl S ) O' O i sr 'T * * 3* m iI V,J TEH 0530222 DUP050031134 9icna <o (vj * .8 ui X 5 o V> Q H W 9 *0 Vft W vt ^ O H M <g H O O O O (9 Kl O O fi >w< o O O OO O OOHOOO o OOOOOOOOOOO u rty 'u 9 ?s 2 Z O I H O *0 HI O VI <9 0 St O N O oor9`Cr*<j>o9'N<ru,nfl n o* ' xt >t m ui o <m a o o o o o o o <-< o o o Q}<0O(0(>KtiAc0>0N<t 8 Ui 8 Hi .* a a cl Uhu*ii mJ Uo>.<J-i CL U 00*<0-400*-4UIeHH* i-IOOrXOi-XrHOOOO O O O * O O O OO 40N9i-<4f(sMir*>CQO(QfrX^SCfMOT owrM^o<oHP >to<ncf yoOixn*roO9^*Koiro,o*<0<oov<TojsoMefovVOfiooHrt I I IOIo I I(Ngr<-9CNviO^f->i6OslAl KOl KrHOCO9>HOt OO'NOfll^NNflJNN HI CM *4 HI <V CM <sl CM Cvl (VI <V| (9 ? Ml (<--H -9 <9 H*I CM <V.l..(H...(.0..<-0 X"t gutoi O m vi O m cvi vi (si cvi i evi (vi M ui DC <aCM'*N0v*6SfHt'6OSr N ^ N^P-itvCvitflOMO QOO'Ort4IAOtt9> <Z Hi UJ03 O UI *0 O' P* <i O T** 10 O O OOOOOOOOOOO OOOOOOOOOOO f-COOH-OCvlt^COHIHlK sOc Hr* x<0r r> in O n <IA* sOr N vNi N p p q qO O O ..O O m cvi O m (vi O m O m (si HI U*3*I rOH* fU*I VOI CONoM K>Ootl oo oo (MgcgcOi-m^^No^ .OUlCMMMHMIrtCUOI^^UOICXMl NiANUt1ffsXt * ** CM CM CM CM Cvl CM CM CM CM Cvl CM 3 <3aM Wj (UoAsi U<IrUUIIU<IOUINUII0A'-eOH' ONOKO1'<Ot <o S 53 Ui ss os y> B 5tft ru<tiuCMiuHIiuOiuVtIcSn3 uiu<0ciinOoiol Cl V) TEH 0530223 DUP050031135 Between Site Model F Transformed Gas. Lead Exp. Dep. Var.: Adj. Set 2W # 3 1 * : 6 ----------- A L L COMPLETE RECORDS E X C L U 0 IN 6 THE TWO NEW YORK S IT E S 2 4 1 13:31 S A T U R D A Y , NOVEMBER 1 9 , 1 9 8 3 COMPLETE RECORDS FOR BLOOO_PB. V A R IA B LE S 1 - 6 . 2 2 - 3 0 , D A Y S _P 8, LEAO _HT, A GCUR7S <Sl * * 1 s z K3 >2 NiR9><rort^N(09l . OOtA O^NrtO^(0Htf Ntf|------------ . . - ,...................... OON<0O4`9Nk^K(0U(On9HlhAOONH9h<((0O<Q0H'0I(OKC)(O0OcgHN<O6>l0JlAI|i)lUA,)UOUNIN^ OI*IHAMIAHMNNHH p ' O mw o u k 4V,nOu ><n t C'C` H (HO I** is (SI (SI 'C(vjcoc40in<0'T'psio>3,cs/iHmur>nr,`^^FH)HsS'^>o O(gQWH'OC0'f<l^0lN/lWNNOtfl^NOhO4^KHWOn>N0^9W>OrKtHtKH1NOOWH^HMOMO Uai NN MIA lCA|M<7NO<^tA<OlON^<>6rtNf|I9A>UMimAQnO"HrItA9,HHNlHAHOK^INNOOOO -4 O OOOOOO ooooooooooaooooooo m o 3 NNHO<OHO>QOm<<r9e<rcO<90>NO^^UlNUilA H'KriAOOHUt^HNlAQMON^OMMANIANOO A oodoodooooooooooodoooooooo 8 CM <> <0 O' fi P* *pH NO * o a11. m(0^0'7<<t<r<tN0<KplON'H0H<9tN><ODONC(SOiMO(MMNN9`ONIQflN<HtONrlltn4<4'(A0N^ (rNMANMP>U)m't(MI^HANAN|HI^O(4<(gHO *S2 `irioHHOOMM eo I! tt k w 23 <0Z ui O* U> z UI w oCO Cr*M ui iH O' ? U> UI <f UI OB p Qa MhMM^tAMO^OHKMMd^itAMMCNO*OQ6^UNONM9IPAM'mPtpMi94HIAO>tNNfA|OCMOPiO>aH4PCO)^OHOCCOlHAPlOApOM(KiOQlNAOIlNOANOn<UN'i7Ad0H^UOOHMMtlHOOAAPO>NINCONO<nNAfUMO<CMI4'<OKQH'OOM^lOAOMOAHM^A<M0CN^0>,eHON4iOA,OOO0^^> Si M. 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UI HI O O Nll<6 UI .1 K 0 Urvi rUi 3 2=.3 3o _ UrI < x z z x z z z z z aui U2 twt * rH 3 > lUIJZOSUHHUPHHHC ZH - <t:iiOc-<cj muh: puu..J.i.j.H.uZ..Z...xf..<Ji..i.Q*..jj..i.j.*.o-.`.\.j.<.oj...ci..c.O..<i..sc....ii.c.<2...ig:g__hi__i_i_aO_c__og__H__a_:_iv_ib..n52o3V) vi UJ 2 a ~ <"3.^ TEH 0530224 DUP050031136 CM HI <4* <0 CM O' 3 U>l > -< a < w 8rHItU h4 g 2s 2 Ul .--i z o a OOxaO^Os*flH>OfWN.HOOOOOHHIM^4NH'^IHNsOtN^OOMrHMO^^K>I-Nia^<NrrHtHONOPhNNKHIONONOM0'f<lOrMHHWH<lfAtO<rMQM<0HOM9OO(OCCMOOOt>fttK`0)-Otrnt OOOOOOOOOOOO9 CM <H O OOQOOO O O O O H o o ooo a p o o o o o o o o o o o ooo o o o lOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOQOOO Uasl 'a< o HI I CM CM v> o HI * id 5 - I ?!a Pui tu H* Ui -J a JOw?v!U?Oo)>oOwN>i^s9OfH<`H.OO(<iOhiOHi^>vt HOOO^.irC<Hr0tbOONe'9iO1/>5i)O^ON0ukO(OoONOiN>oP<OcM0I rCQ<MioatjPnaOO}J<O50loOPUli^nJO^0Ho<OMH^OI ^.t<OOPtSNN*Hw *oHOH*I^eWHH^*eiC-CO-fMOM--i-H-U.-M->O---PCo--OO-p--wCpP-O*M----MC-i-OOn-M----HgHt-lOA*OII ffHHMQ*-r<p--HHef` 4O((i"<o*,><O.^.'fOMlHOHmOU.O'idN)0OowM`Oi0fr}i'ifNOplSCOOi^n(SONOmcH^OcOMotMO'WQU'<KOi)nuOl)O0WriN*WNg''Of(lOHONnMH'NWOmfuHHO.f0ti P 0 e oo ooooooooooooooooooooooooooooooooooooooooooooo Ul fM (0O>HNt.lNM0lP Ul O' in 0.0 O^COK)(9<OOM(SMU|(Olfl9>0 N lAON vf 000MU||H00H)HIP0 0 UC1MJ HI uPHiI o OMM'PtuM-Ai'U<^Mu<OHjr'rt-(POsCw<U'rJ-rM.UPuH^CHi)-MQl(w^f4laCU'SHO^HfJl)'UOt^0uOHf)i)NOHr9H--i>t0HH>HH-rQ'rK-HHnO'lC<0POa^M<O,M(VJUfMH\HIl inA.AU0|O(N3MW0aIOMOHo<.NAO0NNM MW*AOOM0ew^O0)HH4O<K>POMoM.ffOCn^N0^MOlNlNifplA-A-HMliN(0A-H0IMON^^HtAIHHHOpO_)fi'(Ol9)0f8W(*)`lO.y.NP0KO|lrNPH990At>NOTA0pM*(lOayO<M^eiOO9AcA*l*AkJO9NH0M<ktIFlOMr^.A-*(CIgPO<HAC>IOOOO0ATHOOKHC^MUIC(iH-HI[A)IilIt(OONHA00 CO lf 0 0 <r O' W CO HI 0 *0 HI p0tiO.0tnuicMinui0H>p HCMNHWCMN0OA4tHf^I0OK^ICMMUOHlr0t OOOOOOOOQriOM HI roedro rr ro r o a o roodio oiii1000ro 00 I i i i eo i i o Nin Ke tN0^O'HtM0ipP.!MIrW>fc0fON'cMb0pM0pHrotOo.p.WmrNMuHOipIPCovo3rMHsiNOONONOMrOti^nhOo*M0H0Ho0oWOpl0AHO*M0,>nWOo<0OfONo Mfo>u`?0H'O^' ONo MCrO-4lJr0N40Wp0^rO0O-wd0O^O0H^0lH-A^i>>O.fl!He^^MO-pfc,,OH^NwOO0` 0 H) 0 0 0 0 0 0 0 J* 0 0 0 0 0 H H> 0 HI 0 0 0 0 H) 0 0 0 0 0 H> 0 0 HI HI 0 CM .Ht HV0 0 00 0 0 0 0 H* HI g c-PJa tuMfili 33 U. 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Lead Exp. Dep. Var.: Adj. Set 2W CCMM 003* I o < 3 CM 3 O 3 N x s >- HX J >o UJ a s 3a KUJ I <Mtwo mio ~UaJJ I 3to tu O UaJ: u (A I1O2 2 tmo UJJ a. COAD CM CM 5 r*iCnM4 rUtmO*R <P W *C II Qi^^nmemiANHiN com :<m m o * M lfl H O00>ON>(0nMjNO'OO.QMNNmHHi<trVUfl )OU' O)MIAfi<fiONHM'OIASN' .IWdtNf)HM o Os tn o r* O lf| N VO w N N 0 Sf W N d1 VI CM CO CM CO 't fH f> OONM(,OHC'JO<HO<I<lOOlO(O^^NHnMo<9O>HN(>OOMNU)dlh3dKH)aMU'lcOgdiM>>HfCs0t tO CM <0 CM CM CM M CM CM M H CM CM N* . h* CM m r* <* 4* .<tO>MMK)roNiInA*H-CM <0.^ to .C<J -t `b* IhS. 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H* eg <g eg eg <m eg eg eg (g eg eg <tUlsONB)9<OHNM^ UtUUAIAUSIAOOOOO HNIA^IAONOOOH Ul Ul IA JA Ul IA IA US US 'O *0 TEH 0530232 DUP050031144 APPENDIX 6 Regression Summaries of Corrected Site Blood Lead Means on Time From Between Site Models A, E, F, and G Based on Adjustment Set 2W TEH 0530233 DUP050031145 Corrected Site Mean Blood Lead Between Site Model A Untransformed Gas. Lead Exp. Based on Adj. Set 2W m 40 <0 * Ui X >o s ,15 S !8 H W XX g9 I a(0 V) >z w V) UI at Q U uaj u o 3 s Ui a 0 UJ 8 <4 i a. g o Vin) UJ Su>t a o u UI 3 H <o& a Ui o .a 5 M Oo fn< HO Z Uai rUJo< c<or Kl O' *0 co a} in a cO' U. t/i m CNJ to O UI in O' O' o* --z <Ot d* 4* in CM CJ CJ CM 03 c> JO 0* 3N O' in tj v> O flr <r c> o o 10 H o Ou m H CifN) O :S3 =g a: S a > > oa aUJ O a UJ a n4Q*"4f-i0ooof-4CJo<-4OOoOcjegMO9o<<r 0 9 o 9 O O o J9 O 9 O e N 0 e o P o o o o o p o e O .9 H oooooooooooooooooooooooooooo B 5P a ,-j > :z oo ooo .o oo .* * * * UJ s < g - + Oo Oo' A 8 s C* rM >0 si -i oa gssg n in co eg cu rs. <r CJ O 0 ft; u j UJ h>- < UJ Z Zw < H o: m < uj si. O i K1 CJ a. . UJ (Q u a. 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U3 M _| 85 10 jo to -4 <r O' o m Kl is. m N eg M o en in in CJ in in <n eg 0* o eg <0 pH0 Q O' O' 0* <0* 'J- O' in o m o in in o *T P P 'J* * m sr m CJ eg CJ g O j eg CJ eg eg eg eg CJ eg CJ eg eg CJ CJ CJ eg eg eg eg eg eg CJ Cj CJ CJ 10 o o- O' * CJ o o r-l <0 n4 P CJ tfl 01 r'l o o o 'T m H <0 o H CO H O CJ H IN o H rH rt <r H O' Nf 1-4 H OfN*. H 10 . H N O* 1-4 CJ eg o rt r-4 w in rH H 1-4 r-4 <INo. ro CJ o rj pH O" 1-4 o O o O O O o O O O o O o o O O . o O o . O o o o O o o o o O p a in in in to CO in o tn CJ CCJ O' 0* CJ CJ CJ CJ in eg to r*4 sjm rl m o N m eg CJ N in 4 0 o CJ CJ <M CJ O j eg eg eg CJ eg eg eg CJ CJ eg eg CJ CJ CJ CJ eg eg eg CJ ej eg eg .CJ 0N0HnMtftN09>i0HNI/i0N.tA9'0H0H09>NNO rt'OO'ONOKUftMNMIWMN^-fO'COrt.UIONsr^^HH-O oojnp*.srN.tn O <UMAMUN(ynUN4U00MMMMMNMJNN(J(JM0M(siN < IT) a i-iejYn>rtftr'<>cooi-icgtnsr0rN<QOp4egfn<^r,'>o HHHHHrtrtHrtHfJN<gJWWNWftl o TEH 0530234 DUP050031146 11 1? liiiiiiSisiiiSiiiiiiiisiiisiiiiii . I __ v* * 55 55 O O O O M O O O O O O O o' O O O O r-< W ^ Y ** 7 ' *f 7 O O I O O I I O O O O l' o o r r O I* o t I o i' 1'b i`o r O I O O I SsHlS5m?11?1sS1fiKRE*gss11"1Ssls t '>***** JgSSI3l?3S?S33S5SI5mssSsS3#S5SS1S "*ssi5sl!III!"l!l!i 3sa 3S33SSs S.SSSSSSSS!SO S$-3S2S21 M N M N<M1 N M J l N (4 N M N< l.3issllHl3a5ssssll?^II05isIssS *` ,1 SSSSSSSSP;SSS!5?S5??gggSSSa$!5SSS3^! ss 55 (0 <n TEH 0530235 DUP050031147 Corrected Site Mean Blood Lead Between Site Model A Transformed Gas. Lead Exp. Based on Adj. 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Ocr Qw a KIt grMtNOHO^ahDHOlftSOWfnWoMNONHNOOWOpOolOooWt^Ow'OrifSnHHl^folOc'?tHoWoo^NMOoOo'o^ ooooaooooopoooooooooooooooo9o0o0o.0o0o0o0o0o0o0o0o0o0-^0-0^0-- ooooooooooo > e o o o o o3000000000000000 * *.* ** ** UJ Va? 'ifi-<rinift:ors*o,*oa'r*>`irtvrKix3*cocsjr^N.osi,K'j,rs>i'or'<Mi<>csiO'<Ni'0 .<9kTrH-*(cMs/Hv.*isdrNnC9>MioIAcpHf^KM)M<oAcOo<^rOxcssr9fCkMU^|9<o'nuN)r^<-o0f^iOM.<Io/|sNr.^fkOn9K>'O)Nao(mDr^><0d',>Oi u OCOH.cOOOOCHOOOHcOOtiOHCOOHP.OOOH.cOOHOHOPHOPOfSH'OHOHOcHOrctoOOpH.cHacHOH.cOHOHp.dOfpl ooooooooooooooooooooooooooooooooo ooooooooooooooooooooooooooooooooo Ofr<('.i00W<9O'dN*lO/41MKHiOOOMCH.JNm't>fii>0^iOOAiMNnN<<0c<\MjmOi4KC.Ni0pN<^sf<'ofgHc0a^Mr>N>tKri<nt9W'.^iM-Hn>HrotPoao>4p<^pOrKK<iTp0fmMncKh4>r0<K<*lcf-lfu)l a. H M HO 4,lN^4UW4N^MOlOHnHMiA^(OOe'fKI<tNHtftl<> or OOOOKlOOOOOOaOQOOOOHH^HOHOOOOOOOOO u o a i toi i o pooi I O I o I IP! I i a f ot o o i yJCNWOHCMOlfttftNniftHin-tft. O_ I I N H <0 -0 O N N -fi KI rt 10 *0 fi <n. WWHOCOOlAO''t O'flJ O' <f ^ f <0 Ml<00tH-NM^*04NI0<0__I_A___iA_M^i(gOH MNCyJMMN^eyl^MNMCiJMMM CUAI fti M N N N (U N N N N (J M M N N N to pQ'^(Mr,h*'K0<)(pr'OJvw0t9ft>r^NirSirH)U>,)0-^*u^,j9o^'9-o<*in*yUfl^K^IKNi.UOtK^i<nHp(oWM^NcaO<(sOjie>>o9p>a(g''0s^rH CgNN^MMMNNAiMNMNNNMNNMNWUCtlNNNMNNNAKylNN tMfr^tN^<OO.NU()0l>(!i^H0.(000`,>O<rtUfitnlO<COyJOUW){!ONKOt<WAKff1-M0i>flt'Mfr't9>)U<kONr>ttl<A0(!O0(Wnp45'W4KO)HOff<fii3d HHHHrlHHHHrtHHHH r* t~i H H N WHHrtHHHHWWrtHcirtHN ooooooooooooooooooooooooooooooooooo ooooo* O OO O OO O < ooooooooooooooooo* a oo SOlSrtnH^XOOC'stcON'O'OKIWWO.tfJ^O'OOlrtO'N'O^NOjfW N(0<g.M<UNMN(ttMNNNMMMNNNNNMJNNMMM<vlN4NNNM S vi>0>Pta0cOgOp-Ti<H-K4.>dl*<otN(0-idnr^pK^,v<i0fO.iirHvf<%Upv(3><'rf^^v4fiP3<>a0'<^04'0'-^4'^9K*>uif<^^MCc0vliNnrCi/i9JO*Oi-*Hc'^i )A IA *0 O lOlfl h *0 in *C <0 tff.tn U)M^<rS:IA4,lAtf|<0U)'0'flA*0Vl <gc^ca<MNCJcacg<v<>icjcsiCMcgcj<\i<s{c^acsj<Njwc\j<jra<vr4u<NJtje'jcsJtJ WUQPl OS P !v>'oOnHwMpliO\r<vrntfs)O)rNiQOOO>'aOrHtt*NlFI l Ifl ^ N <0 O pH W W P U) O N 0 O1 O H M M oCO SUM OF SQUARED RESIDUALS D .4026709 TEH 0530239 DUP050031151 Corrected Site Mean Blood Lead Between Site Model E Transformed Gas. 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Kl O o ED Z to to TEH 0530243 DUP050031155 Corrected Site Mean 81ood Lead Between Site Mode! F Transformed Gas. Lead Exp. Based on Adj. Set 2W Hi HI 9JH CcOh aiH* a 9MPoo<sJ.ooo*or>i-(tA'Tro<eoo^ooK)i-odr-<oo ' 09000000 ' OOOOOOOOOOO0OOO' > o o o o oo o < Ui 2 <gK* sH<- a ml >< zu. eo O9 O9 3** ^* zs U UJ UJ 06 UJ 3 UJ UJ UJ CQ p. o o ' CQ eg So UJ ui 3 pH 3 ui 1-4 (A * <0 CO 0 O9 Z UJ < o: UJ < C3 O' 0 O O' St O' to to eg ui *1 9 oo >0 oo o o UJ Of Qt V) <1 3 06 or \n -> 1o OC < 0 0u. w O' to t* ^ HI 0 to O uaj x< St 0 M 0 t- eg js o 0 eg ?0" O0' 0 9 9g .w3 03or HI UI C* O HI HI 99 0O O0 HI eg UmJi u. HO* uj X Q 09 0< s z* M oc ml o a. > < > UgJ <c -i a ' - O uj as o u 'CL U4 o o q a' - UJ o o as o 0 X uj O 1 2o o o fH g- H e' o eg oo A II e oc x UJ II -I ' rs. O' eg 9' N eg MI a.06 3S O tt X UJ < HCO a uj u j >H< uj r ZM < ha to < UJ p. CO N r- tn O JA O' H fH IA o rt eg oo o o -4 9 H> f-* co ui 9 eg eg d* 90 o eg . u. rH pH .a UJ B. , mi UJ 0 9 O CL H SW Z h- >< z< > '' a *H0<g*?<g9U1HI>HO'rHOUICgUtO'HILn.HlcgQHI'?rHCQ.<O.vH9' U)0t4'.H9 9<MCSlN<0HONN<ro9<0HN O H ^ -f M 9 N 9 H H g N 9 9 9* H H H N Ifl N O <0 .N 9 Ui CVl N O r> (MA N <6 M N 0'OH93<OHWOK>N(ON-},OeJMO'>ON03lAH>d'tNO UiQ.<MO><NHNfO>O99'7'0<0M9N99 H H O N 91 N N H ^ in uirviAf'9rN 90999 ui009i>'0h'-f*'f,'9rs9r'9.f'iA r>.r>.|s.r>f>r>.H*r>.r%r^ i>* s is r*> is r> fs n r^is o S i> is t (s (s oooooooooooooooooooooaoooooo OOOOOOOOOOOOOOO o o ooooooooooo 99klHA<I0Ag'10*^* lWf|Otfl dU),Og- CM9Wr4(M0Jl1<lC(sll3n(a9H(OWl<A0Ho^O't9<>lJA<Or 9<>tTOl*>> H9 Hw 0 ^ ' ' >* 0 o p ' o* 0 t-1- O' 9 sr <t 01H r- i k <o V ,o n n 9 <OKl(IH<OM9(09g>'t<OOH9MgiAMAUI4H>OOU|gH MNrtH'jNHHH^CONNrtOONvC.cOlANcOHMMNHlfl OOOOOOOOO.-HOO'HpHrHOOOOO O 1-4 OO O Or-t eg * 1 1 to o o 1 1 9 t 1 o i o o t o t o o 1 10001 1 1 9tAf>tH99H9>t<tMAlA09M9Q99'tNiMiMlAN9lA .<9g,(OMN^KWNrtNHNb9'tf'rtlAintAHlrtlAONnH * .. t * 1 cgcyj<M<g<g<g<g<g.cgcg.cgcgcgcgcgcgcgcgegegcgcg<ucgcgcj<gcg O' >H aa UJ UJ 3 tt O Ou mi 06 to: U uj w ao ui H k:uj p3 w -j 85 E 9 N W vf O N 0 N NfldOsAKIrtNN\t>^ <f H 9 (0 0 9 H 0^9 >1>_TO_T'-_Oy_A9_t9_<rN9MU!i-e---t--n---0----'IA0I '"PlA ^ (T0'W9>SrAf>^Hi O<>|r'gfXO,lXA'T<I nM^OnH'fOMKi^fHgv('iMl9ri eg <g eg eg eg cgcgcg<gegcgcgcggegcgcgcgeg*jcg f-4 o N O' 9 <t 0 9 9 O U| O eg O' <g 9 HI HI eg pH O' 0 eg 9 0 9 0N O in UI O' eg r- r- CO M 0 HI N eg r 9 HI UI 0 UI HI t* eg r* co m St <g rH ui o O' 0 JH 9 to eg fH O HI eg 0 9 r- fH 9- O HI <ONO rs fH o 0 O UI H.H H H 0 rH 9 pH 9 pH <0 pH pH o eg eg . ri rH eg fH rH H O rH 9 pH 09 pH pH p H O' rH . HI H ooo O o lOOOOOOOOOOOp O O O O OO < 0.9 0 0 00000000.0 000 <gN9N<OHCOH9HKIHAH<,OOtN.OO'9tfl9>N<09COUI 99Ut9tn9lA9kA9tfl9U)9U|<OUnA9^.tfnAlAlAiAV|UMQ cgcgcgcocgcgegcgcjcgcgcgcgcjcgcgcgcgegcgcjcgcgegcucaegcg NHN^OeJ^^NOIOHMKKOcO^^tOlAfOHI/IOfOmA^ :9U,llAKIKi0>90'(0NN^(Q^IA999c0.lA0'N9HH0t9O m ui m 0 0 0 m m in *? <? 0 i-o t* 0 ui 0 ui 0 0 0 9 t* 0 0 *0 0 -ct egcjegcjcgcgcgcgegegegegegegcgegegegcgegegegegegegcgcgeg in HNrA^lA9N(090HNKIvMA9N<O^OHNlA<fU)9NcQ <oo HHHHrtHrtilHHWWCVJNNWWNCg TEH 0530244 DUP050031156 ^ K1 -4 flO . 1 fillsI111s11111211sis11 s s si 11 if li tu Ui p ooooooooooooooooooooooooooooooooo 51 it1 os * s' |a ? 1-4 4 --I-.----1. ____ 1__ I__*______ * ** ** * * * !3slgaSSsBSSsS3i*SffSg|fSSSiSSlSS5 mw * < 111 6i m: iSOWO'OHNHCOWrtlOthflJKl iSs :S! !BlllgEllgggsIsS ii * 3 t(J XI >^51I : i g s s g V -a1 ws IplIIlslIslIIIlIlilllllSSlsiSsll'' ^SSSSSSSSSSSS^aSSSSSSaSSSSSSSSSSS i 0e i P.P.IiP.siPP,ISIISi*lls.Ss3.5ls?l*ls Mac>iCMNCwiWNMMMMcucacawNMjesi<sie<icaMa<\iM<jcsi<v<<44Cyie<jM I UJ IS 5I i-i I ISI|S2ilSfiS33;f^.3^ISaSMM^isi * * U MNNMNMUN NN *j ti i CJWM i ftlcJ UNNUNij Al.Cvj N M fJ J g SSP!S{S!SBS!SSS;?S3!5SS^5$Sg3S{13SaS5SSS5S2 *s TEH 0530245 DUP050031157 Corrected Site Mean Blood Lead Between Site Model G Untransformed Gas, Lead Exp. Based on Adj. Set 2W o*3* 9<0 a uCOj I <a p '5 hft to tt(fuftt s I 3UJ Z OUfUtJ G g a z 8 UJ to sUfouiJt 06 to Si 3 .aour. -J < uoa. (Uaa9J a(ft HH zou U06J (ft zUU3JJ ano. uA. 8ao a iHrOfit a 5m > 9Iff4tt u. 9IHft pCCOOnO o 5JjJS< (0 99e Iaoopcna)-n UJ or 5?Z t i3 Ur (ft 9 9 ca Ift ftto O W z s< ift ca ca 9 Ift ft ca o o r DP 9 09 9 9 z 9 P 9 9 O ft O o o o ca ift U. o Ht(hft p 9ft 5 > -.2 OO Ou jL > zau s 2a UyJ zo ZH<. f*<2t I* oooo oaoa i UJ H ft A QCL HOOO HHIft o a11 Z UJ u.ss, .HOfOI0ftt' A1riftJt -I 9 ssii SCoeoeSTgI f3C9sSI .fttt UJ UJ ft < uj ftr ' < a < UJ a p ft Ift 9 O ca o aUJ <^fi u a. UzJ (jft 3> (ft o u3iHfrHOHHOH<Oe.lfelWeWoisflOoWooHN-OinNo<H0<otO.oOoOe^iHOlif')iNNHerot^oiniAO O O OOO O O O O O O Ca O O O O O O O O O O OOO Oft oooooooooooooooooooooooooo * ** 4*C * ** 4*c * ** *4c * 4c * PIQ IOft ft pNnNH!oNN..<U^AllrNOt3NiAwUlfblllM0^,UwN|MHw*O0uH'0i3>K0iif<(lvi0fn3lt-lJofltHf.|oH<o7Of<O>Ng(SH^r3h<iiNfl<ltHhicnrg'<iUo3) ^HinrONtHp3t V? OftOOOOftOOCJftftOftOOOOOftftOOOCa 06(ft UJ aUJ af(ftt m(u<3aafti .rHCOO*' o Hc9a o cc<fooaat ca 'ooOf irPftt 9 PrrOtt o 9Hf9Pt O 90OINJ eIcHOna o Htoo iHIOfNt *r9rO9tt 9cooa o HrO>If-tt .f9I99nta P irftt O io99ft o rPr-t O Ior9<o N0t* iacafat o .rOtft o Oc9Oa e rc9fat o 'o o 9Ho99 o M9reft e N fet 0 -j 3awUa(fJt izUa9fJ.t UouMasJ OiHeofst'j Noit9fftl IcNcnaa P riiIffftttt o IIiNfftt 9K1 O 9(c(2ffatt .cN9mcaa 9cc<aar 99 n f' t c9coaa 9IIcHffatt o9ircfatt H99O 9OIft I99ft I99P9S .9ctoofat o09o .r99ft 9i9eOft i9c9fat rr*t HIIonft c9999oa af9ot) 9f9NOt 1 .<or ca 1 fOt AJ O fP(ft*t 1 cNa N5 ca (N9A ca j HIfftt ca o cI9Na ca ! fIfNftt ca 1 O9ft ca t ccNaa ca fN ca 1 fHNt ca O N N o cMIna ca IrINNN M O ft ca 1 f9iftt ca o 9IcNa ca 9r- ca o 9 ca i cc|Naa ca e cINa ca O 9IINft ca e u|n .i ca ir n 9N ca Ift u 9M za is ftU)ft.(AftlA9lAmrN9IS9CJO?ncOCJOCa9ft ST "t <r 3 <f 3 3 rt 3 M -y 3 rt 3 3 3 Sf 3 fl 3 Sp 3 ft SPM cacacacacacacaeacjcacacacacacaeucacacaeacacacacaeaeacaca 0zU6J Hfoat 9e o e 9IN fOt f*4t Oft o fot cI9roNat Qfftt II9fONftt O9?99f*tPWft I9IfeNNt cfeat 9fOAt 9oIfnt Ifc9oNat 9 9ca o .No o ca 9|N o N9 oOfftt |Ifo9NNt Nfe9Ot 9ca o o o 9 o N O OOO0OOOOQQPOOOOO0OOOOOOOO s> a rKiionw<ifolw<.inow>iAo<MinifiNin3Hi<nrHiOft,i`Ar>ooi<np.tinnoin`iNncinOin'OinOiwn tsiNtJWNMNNNMMNCgcgNOJMNCjMMNMNAMjNAI UN)0NU)3OgN>NU>l<OM0 3l<ftUiM3i N4^UN)Ce3>UfiJm)'34ml<OtNN^<HnOMA<O(U03>'fUl3Hi<N^ObH'0.O<'3O'Uft3eiiOs>3(<OOO3W33ljWi3Mir3nt NcilNN<ViNN((JJNC!JMM^<U<4NMNN.NN.(jNNMJJ co(fat HNI<l3IA'6NOi-HtHNHOH3HIHAH'dHhHH^ONNHCNsIJ<Ni3NlAN<N0CNJt9J TEH 0530246 DUP050031158 O <0 S os UJ oas p aK> UOJT >H Vt(u4) -*iQ/4tO O oHHdoWo? oOo9fo^lKo?WonKo>oSWooWH oSoOWeOWoOOoOrtoeOoOrto>Nfonf'NeIONoHHoH^eOOOortroot<oOgo'QoNHOoOOoH'oJo' OOPOOOPOOOOOOOOpOOOOOOOP o. ce w g z o UJ iE a oz .*# X x *X X** *X .*# M fK-cJ o UQCJ M I &s o u OouS- ^N<OHr4 9>iO <r9><A^OONttl nTH.WO'SNrtO1 Ut >t O O <f M M 1-4 H O HOO O O 0`4'^fl)0'<r^^<0M<0HNNM>dO^WdWWW<rNNOH N P* P* P* N P* N NNSfsNNNNNr*NNNN N N K h N <0 N NNMNMMNeiJNNN(VlMMM(JN<JNNJ(4NNNMiN <0 CM h* 10 Ml >0 O CM H H <f tf> tO H I* N 10 p ** O CM CM O CQ <0 H ^ O uz (O9t|><OJl3>N<OHtAIAUHMe<r^<rN<tK)OnK1<OONNJ^O<O0k<ON cr p p sr rfr *> p m o * m < K UKJ UJ h> UCQJ OS >* N^OtfNW fl5<rHMiA<0NN^iro Hl<MtPP*fHnU-irACOiHtAiH<0'M fH OS u CSJ M CM CUHCPOsTlftKIKllflCO O<f0HNOUlia3(Ac0a3'0H(yjK1H9N * zou OJ- VQU OV tfl 9p *1 p9** p* ^o O lA K 0* UVK CP Q H MA 4 H <0 H <T it IflWOO^Mrt-OHNin'ONCMftNO'T (OHlOHNHHajMOOO.-JrtOtfl^H i-4. i-* --4 H H rt H rt rlHHrHHHHWH HNrlrtrtHMH H H H rH H H H rt H N o o o e o e ooooooooooo oaoooooooooooooooo f> O * ' W CL ooooopooooooooooooooooooooooooooooo N O N ^KIHK<1M iAlflU)*0>0 c}S9tf <0rtNK1i I N N H (M r> A1 N H <0 I 00>00`Ntfl'ONO'tH inr-.cpeocoPHtn**1i iniAiAininiAifiiatnoui suit OF SQUARED RESIDUALS 0 .4 0 2 6 3 8 6 OHNW ^ O <9 'O o>fl N <0 9 bHN K> <f tfl >O N <0 9 O rt W h -t ifl >0 N C 9 OHNrt P P 'CrsrSP'*rtAlAlAUltlAlAlAinU>> TEH 0530247 DUP050031159 Corrected Site Mean Blood Lead Between Site Model G Transformed Gas. Lead Exp. Based on Adj. Set 2W ut m r-t 03 <r p P ri I 0 .U Z 075395 -2 .0 6 1 I ****1 a< <v> ^ .m** ra> (MA * as o U3J 9U-JJ z H- 2< OS auo: I I zI n UJ 2 uUaJ <CO M U(9J W OS > -aour. g o HCmUocuOaDsJif 8VQ) UhCHDJ* U aHUJ a. u 5HHOrtHO<dHrtOr>NOi^O'CO`'}NOHO`rtrtMM ONOOONOOOfiCiH^IANOOOHOOKiHOOHO e p e ,o o p o o p 0 o p ' e e e o o e o o e e 9 e e e o o pp p o oooo p o o o o po o po o oopppo uo 89 S3 Sz oo oo oo * ** .* .* ** 9 ** Uyi e A Ooe CM u>3m<ii iNpn (A Ui 9mo 9npe eP Z ui < as S3 g u_ in a ui os z< 5X tn O' v> W K %tCAM0 pO>9 Kl p oo p 90 O o m p O p n <r mn m O n o |D u> p mm o ui Or 9? CD "-> iO as *c NPH NOP 60 P N N (0 O N <0 O w p CM ,, pX a HoaUiti uj 5 -1 pPP tNfo-i HiNn CiM gg f<iOScaPa"S CD UI M r> ' 3PPO *IMDA o . o a ui 3Ui H- rm < H* a: to < UJ CL pp <0 o 1ft CM pa CM P <wT - CM O U. c- P u j Z *s* .Q in p in < 3 ftOS 5 a. > 5 Ui O UJ U 4Q!.h oo 3as UJOO CL Q OS 1- Ui o a: Q CD Cup u. H H Q .mUIl <o a uui c0 a. < c: t M UJ CD 1 h- >z c MO S3 SI- SCD (9 UJ OS OS J DC < UJ 3 Q *O- Mto CD UJ --I < aHI iuni as * Pu PM as o u j ui aO - Sa* Ntf -6 ^ W P d' H f'i P N S 9* O O H N -O P .d P N W O rtNO-fPlAO,NJlAP>tN>fOONHNMNmvOP<OM^ 0PI<i.OMPHNNOe0>NN<JO(OH0OH<r<riOQ>6i 0OOOOPeoe<MHpJHHPOPHPQHHOPOO III I II I I II ti ff'0'tpNNI>0PlflH0P`Mn'fl*10WfllANM0^H U|pNUlNpNppppPIA)0lfl'4N'dNNN<dN9NpN Is* n n sNPfrrsf,f>hr*r>f'r^Nf,f,[>NNf'isr>ffs ooooooooooooooooooooooooooo oooooooooooooooooooooooooooo IO e H .e H 9 9 N N p Kt (MgIOp <fPp WN NSfpl3( d'NOSpKIVl`0 P'O^'fHO'HlflWHNinN'O'tn/'tTvTOO`' O rMtOA`1(p O O M 9 ^ ID O ) <o ui <r (9 in o <j .nl-O.'wOO'O.N,i'nW'PntnPOOoiiNlNMflrNtflnnHoiorcWUQnMHNOCWMNMON'CONMPKPpWiOKMIOU.OUPltO^P<N'NOOvNcPpMwPPPP^J.Pp,<l. ifIOOAl^>QprpHtHmNMNMOOINN`kNHNNPO(\llPi^fnl 00000000~>I`OHOo*p-.4*r-** '--4----0----0------0------0----0-------0------0--<------------O-----O----O- O- r-l i i i eoe i o e OMHrU'OrtW'tMNrtrt^O'rtPOP'OMN^ollftMMn pp^pKJN^f*csjN,Hf^-p.op-^ninininiHinK>^rpinH N.NNNN Is* In ht|>N|NJsSN.NNlNNI>NNlsNN,NNNh CMCMCMeMCgCMCMCMCMCMCMCMCMCJCJCMCMCMCMCMCMCMCMNCUiNJCMfM Nm Hu PaUJ: UMoJ se O9NPNlA<M9PinPPP.Ull0tmr9^^PlOHKiHNP 'pin -p,fosrrD^Ta*^sr<r-i9,M'T9,^9*-^fn NJilCIMNMMMMNNMNOJNNMNCIMMNCjNNPMM et ' os o UJ M a O UJ >- as <0 CL N ui U3 M mJ a< UJ > sto P <t UI 9 N In .N.N OMlArOiNMNpiD't'OUtK'INcgPlD pMpcMMinopoNpcocMc-iomcM.cO'j'NrMppmpN? NOPOlfl-f'T^'ffflMONOWHOO'nPHff-MON H HHrlHHMrtnHHrtwHHHHHH H.H M P H H H o ooooooooooooooooooooo ppppppooooopoooopoppopppeoopp p CM CMC0r<<0HP*-lin V-4..U3 H-3'P0'NO0'0'Ul>N<0>0Plfl P P U> P m p JAP APlS|PiA>ClAlfkplAVlinAlAU)UUA9 COMmO mO mO mO mO mO mO mO mO mO mO mO mO mO mO u O mO mO mO mO mO mO mO u O u O j O u O u 3 NNm'?cMCMmpu>NPPPinsf,cMP<omo<-4Ni-icoNf-4P aW'DWH^N.PaJlftNO(0>?Ul|HUiHP>Off`NOHHO'^C> H U :< CD HNKI<tlftPSp9OHCiW<Mft'JlN<0POHNrt'tlAPNP CO o TEH 0530248 DUP050031160  SI ssi*- r<a*o* S| ,2] iiiilsisIsiriissssiiSlilisiiiiiSI ** 4 * * .* .* > * S. I ; i3 i ?' 3 * _*__ I _si* _________ I___1 _t____ 1 * *"* |* *t~* * $*??$ ooooo*? it!'! Hi t til s S llsllll5slsl3S3slsS!?IS3Slsss?.IIISS S3 8ipiHSs333|SS3lsiiislsssp.slp.HI S> SINtiliNNNNMUNNNNNNIliNN NCJ NNNNMNMMNNNttNN I sssKBSsaKssssssssssssga'aassssssssss ** TEH 0530249 DUP050031161 B'SSi!;; ..43S "1 Table IV-2 Site Specific Gasoline Lead Exposure Data I ,w< |^f2hWPNNHMrtW*Oj5WrtH^WW^3`HWKI^<gr!.0: I OU|(00`HOWNWOlfltfC*9'rt*OM )M firtN ri HHHH l,(4l^<h4NehO< #H H HH 653 702139 392 60454 11206393 5309197 Hi f 0.000008262 0.000315505 S :<s t5oS't fVI:iiiitisM9sol riH csi e O 1 go ss in iih r% w o f* H P* r> o W M o <si m g o* t> o <W *0 W Pd *0 Si* *0o lor *0 nr o* p o o O P tf> fH oo HO I 1 e p o <ooooo O o o o o o o O o 0 <-4 I o o e o o o O -O ! . e o o o t OI 0- SOO*OONNK 2SCO CO CM in <o 0 co CM CM co O m m co o* 2 ST 0*o o O r*> |n M C 0 O 0 W e P 9CM H h> 9 e Mo CM CM r-t K 1A H CM CM CM C0 CM O > P O m m fH HOKtOtllOO OP ' OO o p e o oo oe oooO oO oOoP P9 >000000004 o o o p e o _ i ^<MiN^oo0t>fl0NH00 mo* in ut n m m m oin co O m co m Z K*Htf5<OnMNWOION-yiflHHCyJ00)<iWOlftNrtONK1rtlft t ' ' ' ' ' ' w ' ' ' ' ' ' w n' ' ' ' ' ''' '' ' ''n H 164 144 12.2337 14.5417 0 4 /2 9 /7 9 0 6 /1 4 /7 9 HATTOON, I L INDIANAPOLIS IN NsN\sN OHI CMM N \\ H *0 0 OOP V iisesis^ag: ' J*2gO< s"te* a5><a;-5i gi<iu"_*iSS. n=*-G. 2?2'-s S * o v> *S>ugZ_v)H r 2<uI p Z_O_ h .> 5_H h i_i S I- Irt O W > mj OW_C,zKwH<ttt*tJ>-*Oo'>5-.Jrz5ZztfofofaWw;wnlnoftwC>fJuljOOe oaaz<wuJ' z5MH u z H H O < w Z H W < > K U fi o H U J < H O U. ^:UQIiOOB2U.IhXClD(flO<S2KZH>*H(J>M*UJ(kHS:HM 3ZuH >2H5*__j__i_i_:__5_ 03UZ V> SV)3Z2O4Q<lLOUV)<ZI0UZPaZh2:S-i.ZpC IHHHHHHHHHHHHHHHHHHHHHHflH HNH'ClftN<O0OH<4Hi^lA<CM3 0OHNM<Ctfl9N90eHN OOOOPOOOOHHHHHHHHHHN(yNN<M(\JNNNNrOIOH Si 1 Q 1 HCMM<tU)MN(O0.eHNn*tlA>ON<O0 9HeuM<tlA>(>N.9 9eHN HH i HHHHHHHHHHNNNCMMMMCM CM CM H> H> H> 9) I TEH 0530080 DUP050030993 Table IV-2 (Pg. 2 of 2) Site Specific Gasoline Lead Exposure Data iI 1 I On.eeHNNHOo^(9NWio?iAn<^o0itnhN(NOeNNhNme* H H tfl H H N C*J H HH .K>NOM**^KHOIOCOMM^9m<<NM0'?^rtOtAK- w * sr m Nm iI* 3s&sHmu MOo*Mt*r Dtfl Nft icno ' 1-4 0 0 O & *4 M <oOP **0 MIft CJ o IN o o O tn M O m 40 c* o O P o o o oo O O 9 O 9 0-0 o o 9 in0N9^0n0o(iynneAiAlAH^ no <0 0 0H N in *T .O 9 N N <NtK9HNAOOO<tHNN0<A0I MOOOOOOO OO OOO OOOOOOO m Mrt CO CM o CnJ IN Irs-t oo No Mm R9s<Mo Oo Oo IA9 <r in M O OOO CQ H oo N N OiOn oo CO 9 <m<mNJ oo O 9 c<oOr oo rtM9 sor osr oO' OOM ooO Oooo<eM oO OOOOOOOO O o O o o o o o o o o o o oooooooo o o ooooooooooeooooeoeooo 5 ! I) WerO>NM<MfHnMH.(99S9>On>NHhi>NitMWON*(Og9'in.(o0(9MltMN0H9H9iKn!I9H(0<tff^MNHNNKNI>^79(*9f I H HNHrlrtH HHHWHWHHHrt MM rlHHN.HHH -j&i u 8 i xS i oS 2 SSuv s .38 ** < ' S w w - - -S:; 5 I 5 - JU 2 2h >*a.J Jaw j W O UJ * u i hujk. * D b z yj o** -j Pm -j ^HuuD INNUNNNMNMNNNnMlt^MniMMMMMMN^fgtgNNNNCJ H< 1! HNM-!Mh9Nffle,Oi tt 1 OOOOOOOO- M<0-MOl1IMIAtfKtfI|K9)SIO<0r00lO'OKp>iN^^M<f9t^U^il99<N^4O>?9i'nOiAHlAWtArtin^ilAAU9>N>A9lA0lHA'We<W09s9y9 TEH 0530081 DUP050030994 - IV--9 - assumed that the association between gasoline sales and population holds at the county level as well. Accordingly, county gasoline lead use was estimated (refer to Eq. 1} as the product of state gasoline lead use and the ratio of 1975 county populations to 1975 state population. To account for differences in the areas of the sites, and the consequent different exposures even if tne same mass of gasoline lead were used, the county lead use value was divided by the land area of each site. Inspection of Table IV--2 reveals that the two largest gasoline lead exposure values were associated with New York City sampling sites (Sites ID's 19 and 51). This is not unexpected because New York State represents an exception to the strong relationship between gasoline sales and population. Because of the influence of the New York'City area. New York State has much lower gasoline consumption than its population would imply. The nine county New York Standard Metropolitan Statistical Area (NYSMSA) had 1970 population of 11,571,883 persons and gasoline consumption of 1,964,179 thousand gallons [19]. For the same year, New York State population was 18,236,951, and gasoline consumption was 5,506,910 thousand gallons. Thus, 1970 per capita gasoline consumption in the NYSMSA (170 gallons/year) was only 32 percent of that in the non-SMSA portion of the state (532 gallons/year). This pattern is ascribed to congestion and the availability of common carrier commuter facilities in the NYSMSA. As a result of this exception, these two New York City sites were excluded from all analyses reported in Section V. Further, no gasoline lead data were available from Hawaii and, consequently, Honolulu (Site ID 2) was also excluded from these analyses. In order to achieve fair comparisons between results given in Section III which did not consider exposure to gasoline lead, and those in Section V which did, these three sites were excluded from analyses in Section III as well. TEH 0530082 DUP050030995 - IV-10 - IV.8 Comparing National and Site-Specific Measures of Gasoline Lead Exposure Figure IV-1 is a time plot of quarterly national gasoline lead exposure during the survey period. Here quarterly national lead use (billions of grams) has been divided by U.S. square miles (3,540,023) to express exposure in the same units as the site-specific measure. The plot shows a dramatic, nearly linear, decline in gasoline lead use during the NHANES II survey period. The cor relation coefficient, based on 17 quarterly values starting with 1Q76, is -.79. Quarterly values of site gasoline lead exposure using (1) were computed for each site throughout the survey period. This was done to determine if the relationship between site gasoline lead exposure and time conformed to the pattern exhibited by the national lead use. These data are provided for each site and quarter in Table IV-3, along with the national values. Correlation coefficients and plots, similar to Figure IV-1, were developed for each site (although the plots are not shown here). Figure IV-2 summarizes these relationships in a histogram of the 51 correlation coefficients corresponding to all sites except New York City and Honolulu. These coefficients are large and negative, and range between -.97 and -.47. Uniformly, the individual site time trends conform to that observed nationally (r-.79). Each NHANES II site was sampled once during a short time frame within the "1 survey period, roughly about six weeks. A time plot of the site specific measure is shown in Figure IV-3 where site average GCUR75 is plotted against site average examination date (Days__Pb). The plot reveals only a slight downward trend (r-,10). By taking logarithms, the highly skewed nature of the GCUR75 values is symmetrized. Figure IV--4 is a plot of these logarithms (base 10) versus time. Again, a slight downward trend is present (r=-,17). These figures and correlation coefficients suggest that exposure to gasoline ] lead, as encountered by the survey site itinerary, is not nearly as strongly declining as the four year lead exposure trends based on either national or individual site lead use. : J4 TEH 0530083 DUP050030996 0.000014 + N0V75 FEB76 HAT76 AUS76 NOV76 FEB77 HAT77 AUG77 N0V77 FEB78 MAT78 AUG78 N0V78 FEB79 HAT79 AU679 N0V79 FEBSD HAT80 Figure IV-1 Quarterly National Gasoline Lead Use 4II 4 J I I <4 < < < 4 4 4 4 4 i| .j 4 4 4 4 4 4 tHesj O* rv o z <' mo z <-j o c -ui<o uxaoiAPBiu TEH 0530084 DUP050030997 Table IV-3 Quarterly Site and National Gasoline Lead Use I NCf'^tONNOlftO'KlHOSrlSSWH I ^0*O.OOCJOW<f^N.IAOH(OOkN J HlONNiN^OkOUiO'Mfl(Od3in<OHH i rHisrHsrMcQcMincMininH) M 1 NH WWWrtWC'iHHHfHHHHHHp <Mtf,<MrHHicoinisinoin.rs.cM O m tn to rs eg ' >r is rs o < in <r ' V O N N N W lift H OH O O >0 U1 M O' fr*nsriAin'inn4-:!fcrinH0\mrH oOoooooooooooooooo 1 ^HHOOKItAHff-UiWHrtOOOOO I iflOd'O'O'NKXrNOOWN.OstW.lflN II M<3 0eg N00N 0J 0N0N N0 0N 0H 0M061 0(a <00 0N0M H0 H0 i HusooeominooafSfHco** i N(on com in <r w ' in <o o I 3tf<fH!|}-fa'NtfNO'CMflMOIOO' I H O' m to o N N H (O O O O O1 O O (O j .f 1 rt O H H rl H H H H O H H O H H O Q <O<0r''mcO<McOHliAH'<O<M- rl?O'Plf|KiNrt(OHO0,N^HO^ o 111 o o o o o o o o o o o o o o o o o rH w ooo O o o o o o eo o o o oo oo Xo W 111 -> rs JS CO o o HI N HI o rH Hi o IS n co N <0 CO in fs HD CM rs rs in IS O m CM in O rH IS a) in in m CL in o o o o o O o o o o O o o O o o o o X M oo o oooooo ooo o o o oo V> o < UJ f-J CM HI <n Hi in CM ftj in vt <0 <0 CM cn < o UJ 1 <0 Hi <0 <0 in CD o o in o o rH Hi HD <0 ' fv <r Om <0 CM HI r- <n in o HI CO IS fs is CM <0 is tn in in in ' UJ M 1 o o H o o O o O o o -o o W1 M 10 i ' co o . *' uv o N ' > O O m o i wrtNWowiNSMHNe'rtoNitfow I n^NSSKiNUi<d<0(0ONNa9'f^H in-Hi<Mrs<M,s>rsrH<fr#HrsfsorH I <** I HlHl'd'>3''a'H>tf,<f4'HlHI-$*'3pH>H>HVH><M t m n in in co r*- w in w ' ' * rH to Om tI lNAHlANWfsOH0<NM<ff0sHD>UiMf0HH1MlA>0HHlCaM'0'Oin I NC<JKisri^HHHO>09aO`fl)NN *0 10 I t I .HrHrHrHrHfHrHrH I HrH<tf-tnNtnfsHIN.in,COHIH>tf` OKlMN.-d'COO.OUitsiNONNtOeHH I 0'tfwaiO%00`1C`0N<J,WH0`MA<0U,| I lAUlm0*minminininU,i>'Na`-srHI.<M I * r I Ooo o o o o o o o oo oo o ooo l NlAOfirt>6(Vl.f>iO>ONO<6nO`N'(OOl> i o '^ O' Ui n w -a k in in >6 ' k p j ^ o .(n o> Ii Winin.OmNrm<<WrH^Ir>inO3<`r'NT^WHMiH>i.y'0KPiH'<ir0HH.cNo I **>*' I HHHHHHrlHHHHHHHHHHO t l/IC'O^Oh'NSN.cOAOlCltf'O'O'^O tv j fs rs n n rs r> n n rs s r* n S n n n n O o h- I acrcroarorao'crcrcrcrcycrcrooof CT I <,HNIO>},HWKl^,HNIO>HNHl'fl,rt fSi tO I N ftl e Ul e O 9> N N M 1A K1 H ^ ^ 0 N <0 CM I HON<OHO'-OW<rNHUiHd'tfjONK1 tu i id in <o q to <oo ^ >0(0 <7 in ^ n mu)ojl9' hI H I HHrtrirJrlHrt rH HrtHrtrtrlrtHO (A I ri |i Kisfts9<.MH>UH|N>-O0*OHiMrMHOkrit''O7O'OcMNNinWNHHKlON3<r'ctfMMMArj IIi <o 0<H`rtOwOoC1 lOinors' oorN.AtnIwAtA|Ain:* MpS-Af'4>-Ao'AqttCImOA I I HHHNrlHrlHHHHHHrtrtHHO iJ rH I NUKJNpMOMOKt^^MA'OM^'d'^ CM I MM|AHr0O0K>OO.0>.(0<f S9>Uil/lltf I IftcOH^MWNNonHO'iOOOlftO'^ Ul | Hl<0tnCO<MfsHrHCMMfN|sfsfs M 1 W\f lftOlA<jriAlf|lftiAiaiftHfHVM V> I O I Q)UN<fOC0O(C)O<t<tNlD^HOUiNi N I M*i >0 ` o o lO O' Mn rt o cvj a 0* *0 0 I <0 rH *J *> <0 CM H O O CM O .'T O CM Ul I 9`H^H<0HHH0`0*0'ff'OSNsrO I UieiAlANMN>0<dH<0UlHO0>N3M rH tI 0<3DOKOilfH|KIU^)O.'fKi>OH'TCOJOV3 UNl<N0I<A0ON0NNN 111 I 0<J'^0.0C^<ON'0'OW^'00'HWN -- I *. w t rHr**m<o<MHco<orscoMtn r* 1 WHOrtOWO'lftHMHH'tO'fCOlftM fH IvOO^N'ON^eONHlAO U1 s |s . I OCHMOCOOO'OO'OT'O^CMflH UJ I NHMtJMHCJNHrHHNHHHHHH ' i oooooooooooooOOoo Vi l I N H O O' Nl/I N H (O <t O IA O O N H IA rH I lOH^N^HONOW^HN^NO'^^ mNU)Ntfi.K)^MA(g.<r uv* ' v ' ' rs IU ( irl fH rH rH rH rH rH rH rH rH rH rH rH rH rH rH` rH O M I OOOOOOOOOOOOOOOOOO If! MQlAHlftHHHrtlftlOHlA -t CM Hi <t iH I H^N>0UiWMflO'0>6.3in0`'0(0in>> IU I HrlHHHHHHHHHHHHHHOO h i v ........... H I OOOOOOOOOOOOOOOOOO I rsfsH>.K)'?OrMrsC0C0C0f'H iI sinOK'i0o'0c0o^iA>cvf-J3tn,'<PfH'sr<HOiNKCiS<HfcNMS,tf)`-Ou"|HcevOf'' l . . .............................................. I OOOOOOOOOOOOOOOOOO to I CMOO.<M<frHHirsH>ininC0 rH I K'd,^OH0WKI^CMrt.*0OO<0'fiH in Ii wu:riHoirnoN(Hoa,'jfrsH>.<j<fQi'nCfHsmUriHuiW'TKin'0 +- .1 M I (00<O^M0^H>40N<O<0U1l<l 10 1 rH I Ui'0'd'0'6NNNN40C9(0<09`9k9>Oke D I SNNNSSNNSNMsNShNNCO fc i crcrorcroaoaocrccrcraoffcya OF I rH <>J H) <4* rH <H ' 'S' rH <VJ HI <r .rH (vl to 0* rH TEH 0530005 DUP050030998 Table IV-3 (Pq. 2 of 3) Quarterly Site and National Gasoline Lead Use Ifli n wtl SITE GAS LEAD EXPOSURE (X 1 0 ,0 0 0 ) W II 1O0 U)4`0M)OHIAOH'4U)<O9'OlO,<^<OA<tOO<ONH .9A} S<6Asf UJ I IA!AN(O)OlAlA<irN0riHeOk^ON- HI * . . * * cnMI1 HHHHHHHHHHHHHOOOOO K I 6WWHOtJ)vtONtfl<fWN^K1(hrt^ HI | N O t> (h ,CJ U1H >l Q <Q H (0 1A N O VI HiUJ I TNOOd,>;f'tfU1tfNONWWNNHO M * WONNNOHHOaJ0'(0(>0'Q'<0Ntfl (fl JrtrlrtHHHHHH 04 1 HOOCO'NOfOCONSOfOCJHO-UUA HI lI^9W9NHfOtAW.NO9`OH^HWOH(0l(f0tK(0IO'Wt0(N0(O0<N0O't U) 1*H04HfSOvHHHOpppOOeOp H1000000000000000000 II O>tO>WeNlOH^O<<OO^KUM)flpW4>llOO><)QtN^r0^THHWNO I HNO'irh^HQKlKItnNiNH^NtOO I 0 O H N N rt Kl N (0 (Vi H p p 9 O ! eQ'OH9>0(OHIiNKI^OOIO<tH HI 1 NONO'NO^uiKi.NojH-i'ON-fHCJ uj I 1 Msr wW-trflM^flnNsNMrtfOl'JvwOwWwowf^fONK^iW<f NNH<0 w 10009000 0 0000 0 0 0000 Vi 1 P I ^^rl'O^ ONH KI81 Ol 1 HSWv0O4 0`ri>0Oin>0C0^N(0N-f I K).evjmKIKC4<MMCMCSJ.<gcj<\i<gesjiM<N|H IUJ OOOOOOOOOOOOOOOOOO M t OOOOOOOOOOOOOOOOOO ,W I CO 1 MlliM4,<0N'flrt.'3,O>MKl'rtHO*rt 04 IU)NI^MO'HO(&HtOHd>(ONMO> I NNfiOHcgNJOfl3NHHO<rOW<r Ul I HliH0LAH<O'-<OHsri-<sr0'tf>O0<UCO HI ............................................................................................................... WV) f1 KlKMOKtKlWKIPlNWririWKltOfgNH n 1 ifio^Ne^^o^Nco^rfN^Kie^ O m * O m <o to *r p o <r 0 .' r> o O m ' ' m 9 p p I (OU)inNfl9Ul(OON>ONKiMOeOIAM u j 1 .0* <h rt ' o o H p o O m O m 9 O ' 0 '<p <g Hi ****.***.*.* M 1 NNrt 0 I P HJ CQ tU HI P O HI HI P K s* H CM I >0 -o I'i N .<r O O 0 Off H N Kt H N ^ Kl I Hr>fONKiOcJWOKi^:kAoull<rvf^rt UJ 1 KicgrOiomcjnnNNMcgcgcjNMHH lftMN^lA.aNHO`KlO>0&*N^OMlf| H<fHNUMi-O0UNirWtN>.7O>f0'l'(J0HOni>Oj,MMWWN<rN<JO'-f.r'NO 'I w 1 o o <0 o o O O O O 1 O O O 0 O 0 O 1 I lA 0 0 0 0 H H is H 0 0 .0 CO P P P P tt I H H H N H H -H H H H l* h. f* N N -N ' 1 crtja(jtjaaaaoo&&crcrcreref or .1 -ffHNM^rtNMjffHWiO^HWKIsrH V I 05 CO.i^NNMsMJhOtf j ^NNrf-a UJ 1I HOk<tu).N(OQ>!rif)p`H.<oe,<o>i)o9> N o H e 4 N ID CO Km M Q b <0 m <0 MID II 0 0 0 H 0 lA 0 0 0 IA IA 0 0 <T sf lA 0 CM I 1 CUr>-4p'HntC'0,o*-tHcolCwOoO1inAPco<pf>r0iN'.0 o-pCMin H0H0) 1 rtWl Ift O* ^ H O O' W N M f M fl 1 4S) ^(Mil e VI H) ^ N N 10 p m <0 O 1 eg' O v .' rt I rM0sr0HlKMPP.P0lAH90O0OO .1I HN^W^HPfOff'SfvrUiVtaO'OvJrt Ul 1iO-l WON0OO* 0MHHI0rt0WONOMHfNi OH- CNO Mr>KHl ql)Aij>sOf 0CM I COtAlA.<OO0PPr*>00<OHl0lAHI0>p lI OinO-PUPImCO0IAO'PHinIHH^0r'H0IHPlHAOOH0l0H.I0^ieHjCICMM UJ IOOOOOOOOOOOOOOOOOO 0 ' 'M I OOOOOOOOOOOOOOOOOO I. I 1 1 Ho31o?IA roJ0'cU0ri<iA0fCdHM>.H001OoUK0)V<>V(H\OJNhO-uiMOiKfHHi<0^rr-oNOHNO)t700<sJtoA' I ** . 1 HrtrlHHHHHHHHHrtHHHOO II *M-f ClAh0O0N0^9O'9<9PN0O(COM iHH (CMM 0MC^O<HOI NHi-nOO.0' I CSJ H eg HI CM H CW vj vj rH C4 CM H H H H rH O I 000000000090000000 I 0 0 0 0 0 0 0 0 0 0 9 O 00*00 1I sHf oOOH etgOolf'tN0^MMw^AKl<O0 'aoedw'm^M> I lA0intniA0UVlAin00HrHlHI00HICM I OOOOOOOOOOOOOOOOOO I OOOOOOOOOOOOOOOOOO <0 ( H>1 eg Hift tOMfl wNrtalo^Wrtxoort HI I P1** O 0 ' p sr in Om .p cr ,r*k -P O <\J eo p ,H (O W W N ^ N H N W <f o (0 H in in N -V HI SIMA 0 H| 0 Ul 0 HI HI HI HI CM HI HI CM H OOOOOOOOOO00009000 fv 1 00tAi-4i-0Hltft0r>'>0H0 00HtHt HI IHU|0HPCO0in0M00>-lPH I iniAP0 0NlAP0PCM-IHI0r<-<O*M0 UJ I O0CUXrOlAOO0lACQ0rsM?<OCpH:CM M l -^HI^^rMTHISf^HIIAlOrAHIHIHIHIIOCg HI 1 P00f-4HtAPfH^O.0 0Cdi-tlAHIHIHl I cg.CM0inHIC\1OJCMPP.P<O<OHHOtn UJ I r^.f-IrHv-trHfHH.p^MOOOOeOOOO HM IIO O OOOOOOO*O OOOO O OO O Ul lN0O<OK)OPCMCMCMHIH!lA0tAi-t0Hl HI 1I09P<0(0.UHINOO00NPaO9(O0MH0}vH1I-UiriIMIAAP<Cl>M^00 UJ .j sf ^ l/IJAUl ^ ^ ^ ^ 9 sf ST SfM W V) IH I 0 0 90000 0 0000000000 1 tA0000NNHr*>00coeoOopp I S N N N N N N NHH.NNNNNNNtO 1 a er or fir Ct.O Offa.CrOOaO'Off oc TEH 0530086 DUP050030999 Table IV-3 (Pg. 3 of 3) Quarterly Site and National Gasoline Lead Use SITE CAS LEAD EXPOSURE (X 10,0001 II0ORK0H1 N0K)N0<Nt K0NH>*<41Om0PxIO1 m.iOx(0i<MwOO0pJ09N>x(COi g0NN0NNNnNiH0n OOOOOOOOOOOOOOOOOO I o 00 o o OOO o o OOOOO .0 II (tfOl<Nr(SO>tNiONO(M^A^NtOHM<MH^NiAO^e(i0ANHNIA(QIAN I (O<fNN04lAOl(M4 0 4lflOO<dH I HOKlUiONinSNNOOO'tOO'rt'OlO I N H N N N N ej <g N H INI M H H H N H H UI I vO^MOKIWNNMKIO'flJ^COHOHMN 1hU II H*< 0 M IA N 1 9 1 H^ O Ulf*NNN* 1 lO Wtn I* NHNNNHCJNMHHHHHHHrte eg 1 mood,ooHo(MOMin>d<o^ort^ 10 1i cOto<>oo<ifrlN(MN<iio4Uoim>o4u0H>Mt9nrio/i>oo<HrinooLn>do,(gK) LU j rt (fl ^ N M 91 4 <0 3 O' H M H N M(0 ]1 N.4N<ON<O>QN'O<O4N>Ov04lAKi H 1 Vm r* p* <u Kt ^ r ' 0 r r* 1-4 0 e ' m 0 ift I N N H O 5 <f N N N Ift t' 'O O >J f) N W O ui I 1 Nco<1oWMMajninNw(^0rOcjKiA iPoT.flj-NoNO'OO'mO' dij'oif-cin W i N fl^ H b M rt <0 s& .rt .0 .t<ViftjiO Hi N N t)J O' (O 1 0 ui rs x* ,c 0 r> 0 ui in 0 ui in u* ui 0 eg I1 rHs0PMnOMegN<OofNsUeOIUiH'Ofs-pNe.oSx^iHegNHKCifOseMg I W H N *-l P fH M P H CQ 0 * rtHrlHrlOrlHHOr(HH H H HO O 1 0OO0O0OO4 000000000 0 I NfrO'tOrtd'HOl'lN 0 0 |s P P P 0 1I M0 tnA 50,0rt<Onj0n't<00o9'04dr*<0flr4s>lfr>|>cof'cOo <INsVrMHtlH0fl .ui i cgcgcgxicgegcgcgcgegcvicvcgcgegegcgH W' 1I 000eo000eoo0000 1 <00 o-O'^PMnHHPW'd't'or'iNin I H4 <() W > N >0 H P* H .0 H O' >0 O H 0) t 0O XI P r- CO O' 0 0 i-l IS 0 rH 0 0 O rH I PP O 0 0 N P 0 P .0 p 0 CO 0 |s fv 0 0 1 ' x o p o . 0 0 A- I VlWKicO^^Kil/iH'twMNCUimON 0 i <o O o p s j o m w o ffl ' o in o m w ^ U4 II dO'CO0AOHH^fHf`OSO.^OHW0`O(0O0O`OWaO5NO(o0CO0Q^<Of W lOOOOOOOOOOOOOOOOOO 1 1 0 O eg rs to eg P N xi N pH p H N XI P P 0 0 is p eg XI O 0 X* 0 p 0 0 eo Is 0 0 1 0 H 0 0 0 H 0 0 XI rH XI 0 XI eg XI 0 p XI i eg eg eg eg eg eg eg eg eg eg eg eg eg eg eg eg ' pH 1 1 0 O 0 0 00 O0 00 0 O0 0 0 0 0 O 1 1 0 is 0 IS 0is 0fs 0 IS |s is N fs Is IS K <0 N is f0s3 <fs0 <IS0 pfs .P Is PP |S Is O eo 1 1 P 0 cr H cr or eg xi a 0 o' r-eag O XI cr 0 a H O' eg p XI p 0 <y pH P eg p XI p 0 p pH i<ou oo i<n ' (9 X Is sH sO lx X>eOejUlfSP|sOOJrHPrsp0 <D0fs.0Xl0O0PXI-0 0CgK>0pt-4 O O' H N H ^rt H P (0 ^ O' O' O CO N *HOrHHfHO-IHOOOOOOOOOO 0 0 0 O 0 0 .0 O O > O O O OO O 1!II 0PWNKH<^iOiWA>Ur)fssiJO0N0K'>W0iOtf0iHWpl-A0W4N00cMo.J0NtHAO0NiAePH>0c0tPgiJ<<HgOg0CHrM^tH>p>jH0iA-.H400 4'0 0000000.0 POOP 1 4QN(0<0HI(0l<linO(0<fNHNH0 t 1 .D0 j<n0 <N0HHMNOM' ion<Q<rNH eNSOHHuiU| )>H0 (K0 )<i9n<<o o7* 1 0 P 0 i-< rs ' 0 m xi eg 0 co <0 0 eo co eg 0 l x>egxi0xiKixi0K><gcgeg<gegcgcgcgpH eg i Ncoo`0Moinomn0.N^ininMOin 0 I 'OwmO^NWMOHONHinMHHO' I <OOcgrHPj-tr4PP<OCOlscOprs0 U I P-*OrH#HpMpH*-trHOOOOQOOO O OO0* IIIIi HH tn 1 OO OOOOOOOOO OOOOO 00 r4 X I I M4 0 j1 riAt<xgi0ocrgsx-i<Fx4icNg0.eoO00Xf>+0iret0Oc0Oe0gtto)xPiiPs 1 WKiMKlKlWWWNWin.M.WinWK\Np4 UI I 0000 OOP OOOOOOOOO 00 000000000000000000 i a. S o 1 P <0 xi 0 eg cb eg 0 0 p 0 x> xi co p eo o xi s 0 t1 l0A0OtgtNAeNoicngnc-4oomcgo0^PH00HOo.iusi>iA0<^-g4^0 in iUJI u j j 00r-JN0000tA00000xx>xicg M1ooooooooooooooooo t<n 0 tf)UHwJ i .m 0.0 eg 0 0 0 o 0 eg 0 0 rH r- 0 xi 0 0 1 1 <?gg.i<inoicsog0>0(oO0i0nfoceo*oeso^cNgxMiKMtun,i0oOui'NP I CM7>fO<JH(OCON<fOWNOCONOsTfJ 1 cgcgXixixicgegcgcgcocgcgegH.HWj-tr-* 0I <0 1r tI UHwI lt 1 M0Oh0H1K0CI0H00N00H0CIgf00lO0rHN0Mr0t0i0nf^o0.|>g.00M00j0H0XrIltACO04 I 000000000000000000 1 tn JN t -U| 1 txi 1 1 I t 09r-cHg0NuiHeeom00.0^iNNiA.puP*i00^0i0s0NrNNiA.r*Pt*.Fo0*cing0N0r0-W.00iNiA-i Pso.ocgo00pHP0r>Oco}r--0Kio 1 H 1 * 1 1 * . 1 >H 1 HHWNNHrtWHHrtrtHrlHrtHO . go.cyeoaocyffaaacyaoocyatt 11 WN 'K0,eN ',f0s vr0sNfvNNfN-fsMJ\0|i<f0s(,0|\fe0frfs^fs^0N'OCD 1 P j 0 * < <gxi0HcgKi0r-icgx> .0 rH eg x> 0 rH TEH 0530087 DUP050031000 ffiSSSSS zeeon ' 8S33SS i*ii Figure IV-2 Summary of Correlation Coefficients of Four Year Quarterly Gasoline Lead Exposure at the NHANES 11 Survey Sites ' SA. ^ Kr* <KS A(s*. UUIMIAIAIA 2 Lft u> m in ut NtfXf^NN I10fI1C0 N .N0* Nlf>Nlf| ROQNiAtfl (ONift ' O'p N N N X N NT -- P* 10 O O lft H .* PvO*P*iH wo (0 Ul N O ^ H <0 IA09<0 V) i N< N<0 HN SN 0<6 ;2 . 20^503 S5C3 tNNNN U/I.OMO > V - in O >l oK" e NoO~n^6$^*ve^$<0 HM c> eo c> tf| ' *o Kl N Q ft** O vO H * o <> A AIM MMH NM<kANAieAlU)ti) H H H tOo ><HOo CM O 2---tu (A li * --O AA A i> S>Sx:BuPio S I! 8: 8 I UJ *H0 <jp ON N*-N-0A0* <0 C0O Ifll I' I . r* *0 tfu Krl*CTM rl* CO fO H UJ sUJ J 5 ii 2 z " 5 2* r 8 : < p Ut <0 ut4P0n(:0<90 >0 5 >- 40 55 2O t5 is SUcJ H [ At iH t .N H 00 0 ^ >0 O M At CM CM 9> o e o o n >o o o co is i a. I H- iMI i*tlA| UI IM| IinIiAI^^MMI 'OI .I NI NI N NI NI OI O O fIlpIOI'frJ ^If TEH 0530088 DUP050031001 Figure IV-3 Site Specific Gasoline Lead Exposure Trend ( < +>8 'eoT < < < 3 ul 4 V.vJ N lift p* O oo oooo OO o o . o oo o DAYS_PB IP It O O II <0 Ii I o4e IIII 4 . !II * O I It te TEH 0530099 DUP050031002 Figure IV-4 Trend of Logarithm of Site Specific Gasoline Exposure 4C < < * < < flO < < < < << < < < << < < 5 4I OO I 1A I tI 4Iii ,4*O-* M. 4O II *W-< tII o 4- O IO 4o I O' o <0 4I O i rs to !" II O I ^4- O < DAYS_PB o lAA* oo* lAsj o IA Ntft e V o <v j K1 *4 sr Vf IA tA ii TEH 0530090 DUP050031003 - IV--18 - This observation on the influence of site itinerary is conceptually illustrated in Figure IV--5. The solid lines indicate the strong downward trend in gasoline lead use at the sites during the survey period. The points on these lines show the exposure at the time the site was sampled. The collection of such points, summarized by the dotted line, portrays the exposure encountered by the site itinerary. The slight trend in Site specific gasoline lead exposure raises suspicion that this variable is not well correlated with blood lead, since blood lead levels dramatically declined during the survey period (see Figure IW). However, a plot of site mean blood lead versus log site gasoline lead exposure (Figure IV--6) demonstrates a fairly strong relationship (r=.49). Thus, the site specific exposure appears to be sensitive enough to detect an expected relationship between blood lead and gasoline lead. In fact, in the analyses reported in Section V, this variable was flagged as significant (p^.05) when adjusting for demographic effects. Values of GCUR75 vary by a factor of 400. tittle reliabledata is available on the range of exposures to be expected. In the study by Azar, et al [20] where individuals studied for olood lead wore personal air monitors, air lead concentrations varied by a factor of 46. Thus, it may be expected that variation in exposures in a sample as diverse as NHANES II would be even greater. It is common to represent a density measure in regression models by its logarithm due to the typical skewed nature of such data. As the analyses in Section V confirm, there is little difference in the estimated contributions of gasoline lead exposure to the reported blood lead decline when using GCUR75 or log^0GCUR75. TEH 0530091 DUP050031004 Figure IV-5 Conceptual Illustration of Exposure at Individual Sites Versus Exposure Encountered by Survey Itinerary TEH 0530092 DUP050031005 Figure IV-6 Site Mean Blood Lead Vs. Site Specific Gasoline Lead Exposure BLOOD_PB | NAT. GAS PB < < ffi < << << * co < < < < < < (O < I ii mon io 41 sj* iiiiI I?s* i4 in iii ^ i io 4 O' IllI cn io 4i Nm +:Iil oi'n 4* < < 4ii mr4 io .4tII MO' 4!- r> I CM 4I Oin 1IIII CM . 4III oO' II1 r4 r-4 CM <SI C1* rHH - 4 --- -- * -- I *4 O1 N TEH 0530093 DUP050031006 - IV-21 - An aspect of the site-specific measure that could result in a time-related bias is the between-site variation in site area (square miles)* Counties or groups of counties are defined by political boundaries rather than natural boundaries. Consequently, if these areas tended to decrease in size according to site itinerary,, there would be a tendency to dampen the true site-specific exposure time trend. Figure IV--7 is a plot of site areas versus site average examination date. No strong trend is apparent. The correlation coefficient is -.20 and this is exaggerated negatively by the influential site near the beginning of the survey. Another way to investigate a potential time bias in the site-specific exposure is to relate county lead use versus site average examination date. County lead use is state lead use proportioned by the fraction of the state's population living in counties representing a survey site (see Eq. 1). County lead use divided by county size gives the site specific measure. The time correlation coefficient for county lead use is -.13. Consequently, variation in county size appears to have little Impact on the exposure-time trend relationship. Inherent in the site specific measure of gasoline lead exposure is Specification error due to a nonuniform distribution of gasoline lead within a sampling site. A measure of gasoline lead exposure that accounts for variation within sites would help to alleviate this limitation. Unfortunately, on the basis of available data, it is impossible to derive an exposure measure to account variation between individuals within sites. At best, one might investigate an exposure measure accounting for variation between subsites within sites. It is expected, though, that the specification error associated with the site specific exposure measure is of much less severity than that resulting from use of national gasoline lead exposure, where all individuals in the U.S., regardless of location, are assumed to have the same exposure to gasoline lead in a calendar quarter. TEH 0530094 DUP050031007 Figure IV-7 Site County Areas Versus Examination Date i. om << 8 < *_< 1 1 1 ,o*H3- 1 1 2 0 0 1300 AA A A B AREA I pm :1 f1 s s 1i 1 1 A i 1 A A A AA Q0 U < < 1 < << < !l i Htoa AA A A 700 900 0AYS_PB ffi << 1 1 1 1 <0 1 1 < < iii* 10 i e !* it A AA ----+ -- 500 -- +--- 300 << < to < 1 1 1 9*3 1 < 1 1 <! AAA < < < i i < i zoo A 100 TEH 0530095 DUP050031008 f V. Effect of Exposure to Gasoline Lead on Reported Blood Lead Decline In this section the results of analyses accounting for exposure to gasoline lead are presented, the modelling approach is that described in Section III..A where a between-site analysis is performed on the set of adjusted site blood lead means obtained from the within-site analysis. The only difference is that the between-site models incorporate, In addition to survey demo graphics, one or more terms (2-type covariates) for gasoline lead exposure. Based on the regression results three methods are investigated for estimating the amount of the blood lead decline ascribable to exposure to gasoline lead. The first compares the residual blood lead trend before and after removing the effects of gasoline lead exposure. The second uses the estimated blood lead/ gasoline lead coefficients to estimate the decline for the survey sites over the four year period, and the third uses the blood lead-time coefficient. The collective results of these analyses suggest that site specific exposure to gasoline lead accounts for less than 1.0 ug/dl of the blood lead decline. The key results are presented in Tables 5, 6, 12, 13, 15 and 19, V.A Results of the Between-Slte Analyses i The four sets of adjusted site mean blood leads, based on results of within-site analyses on models 1, 1W, 2 and 2W (see Appendix 1), are used as the dependent variables in the between-site analyses that follow. The only change from the between-site models shown in Table II1--6 is the inclusion of one or more Z-type covariates reflecting current or lagged exposure to gasoline lead at each survey site. The key feature of the measure of gasoline lead exposure used is that it attempts to reflect the exposure of the sampled individuals at each site at the time the site was visited during NHANES II. This is essential since it was shown in Section IV that the gasoline lead exposure time trend, reflecting site itinerary during NHANES II, corresponds neither to the national gasoline lead use trend nor the lead use trend at any single site over the entire survey period. u TEH 0530096 DUP050031009 - V-2 The four gasoline lead exposure variables considered were current site exposure (GCUR75), thirty day lagged exposure (GLAG75), forty-five day lagged exposure (GLAG275), and sixty day lagged exposure (GLAG375). The lagged measures were constructed analogous to that described in Section IV for GCUR75. The values for each record correspond to the date preceding the examination date according to the lag interval (ie, 30, 45 or 60 days). The individual measures were averaged within sites and the site averages used in the between-site analyses. Table V-l presents a listing of these site averages. A variety of between-site models were investigated for Adjustments Sets 1, 1W, 2 and 2W. These between-site models, involving gasoline lead exposure terms, will be referred to by letters A-K. Table V-2 indicates the gasoline lead exposure terms included in each model. Two variations of each between-site model were investigated - one where the gasoline lead exposure measures are considered in untransformed form and one where each was transformed to log^g units. TEH 0530097 DUP050031010 Table V-1 Site Averages of Current and Lagged Site Specific Gasoline Lead Exposure li OOpa'OOOHOOHOOOOOOHIHIAHHOI'IONmOOHO s l.mif3fi5S3`SEI23Eamii33 H eo^peoHeeHeeoevenHMHHenaMneane S SS?SfSSSS22SSS3EfSESSZgSSS3S I .1 k * t * . I t . * . " OOPOpOHOOHOOOOOOgHPHHO^PPK.PPHO a ,** **. * ' e o * 0 o o ' p p ' > p p p o p uj ' p ' H 0 m p N m 0 P 0 li! li KSsssssss^ssssssascaRKsassassas SSSSRSKSSSSaS'S'SSRSSRSsaBSSSSas! S3IS2335SSSSSS3SSJSSSS.SS3SS5JSSS a i ?s .6 *is3 s r-s 1 a O g if2S 1 s15 S f| *.=1 i s i i || ^ s 11 *: iillisll |l| li lirfife !Si IHHHrtHrtHHHHHHi < 1 HMK)^tf|N0M0OOHNKl'J-|fls0N0'OHNrt^lA>0N<09`OHN ^ I OOOOOOOOOHHHHHHHHHHNNNNtJNNNCgNKIKMO i * tfl * ,'**ss8B.aa.s!5sa88ss*a8tt8*;*P( TEH 0530098 DUP050031011 Table V-1 (Pg. 2 of 2) Site Averages of Current and Lagged Site Specific Gasoline Lead Exposure lA NW l IIII *njO4IKUA)lA^OOHO4O; NHOH 4Oip$0<n0rn41K0 NN0)NNiO.OH.HNHK-HOOOhN_h_i_/(_OeO__OA0_NIONOO,NHOO. *P4lIAA..*..N0N.*..t..O.thI.f.f.l.l.*O4O4O.<40|OsJ.CiMvOj ifK)sC|rfMt<lOf*ttM0ON(OO0HHO*1 J ! NH0040 0,0 ^OOMIAOOOOO N'N *4 0100*4001000 010 tf I O # OONONOCO'd^ O 40 4(O4^NeNNNONNOON0OOOO rui ,I nNn\\nNn\s\Nn nNnNSnSn\Sn nSn\\nSK\oNn\SSnNn\nSn WVSs n n s n\\nNn\sNn K< I| HN.KHI NOHOOONNHNOM^OmOcNgOHNOOHH.OOKnHHHNIHA(N0NMAOJ*NOHN(WO*OtMHHO.<MtNH^OH IO II \HINO\H\^\ft\llASNN\OSN\N\O\N(O^\M\M\\HNn^O\O\\NNOO\H\O\\M\nSMO\O\\U\) IjHOOOi-IOOOi-IOOOOi-IOOOOOOr-IOOi-lr^rHOOOOOO iIONNfiNH4NHWNH(9-f^lNCW^NHN<d0,Ni0r9tNN9kWOO^Nd0^0N<HM!4Ar<tH60^<^NfNNHrNt^N464^ i H HNHHHH HHHWHNHHrtH Hrt HHHMHHH Z > hJ 2 l KWOJ<OOfiOK UH fi I INNNNCMNNNNMNNNNNNNOOMMMMMNNNNMNNN ) <I < tjMHWCJ F^lf|OMO^OHK>tlft'OS<00*OHNKl^WNfl^6rtN {OOOeeOQOOHHHHHHHHHHNNNNNNNNNNlOKm NO S K ^ 10 *0 N (0 O* O M M 10 <tUiON(O^OHNKI^lAON<OOOHNKl^ (0 PH H I to to K> to IO to to sr ,o o o TEH 0530099 DUP050031012 - v-s - Table V-2 Gasoline lead Exposure Terras Included in Between-Site Models Between Site Model A B C 0 E F G H I J K No Lag GCUR75 X X X X X X term 30 Day lag 45 Day Lag GLAG75 GLAG275 X X X X XX X XX XX 60 Day Lag GLAG375 X X X X Table V-3 presents highlights of the weighted least squares regression summaries on between- site models A-K, where the weights were the reciprocals of the adjusted blood lead site mean variances. For reference , the results of between-site analyses based only on personal, residence, and itinerary survey demographics are included. Inclusion of one or more terms for gasoline lead exposure increased the adjusted R -value from .01 to .07, Although in most analysis categories it is difficult to justify a best model p based on adjusted R-values, model A was marginally the best in all cases when gasoline lead exposure was untransformed and model G was marginally the best in all cases when gasoline lead exposure was transformed. The overall 2 best predictive models on the basis of the maximum R -adjusted criterion were models G, F, E based on Adjustment Sets 2 and 2W. These models include GCUR75 with each of the other lagged gasoline lead terms. Appendix 5 provides TEH 0530100 DUP050031013 -Q in o) id iCD thCl--D ' o iSZ O 1--H NfOOH CM CO ^ CO LO co m NNOOM 10 VO rs Ci m co VO o CM vo co co oo fs VO CO 00 in is co n a> (OOHIO CO VO CO o in OO H r-1 CM CM VO in ompri VO * VO * CO 00 <dH rH o vo cn vo OUOHH in * co <ors O r*< CM VO VO VO Pinun c^otH CO vo rs oo co ci rH 00 CM CM in * co vo *d- CM O vo in fs oo co m O co co o CSJ m oo co o vo VO CO 00 in oo * co in on O in co is rs* vo <d* c in sr CO H o rs oo vo aunroH m .* oo co rs in rH rH Cl CM CM IS NlPISrt m CO CM rH rH rH rH CO m CinO VO 0c0n H co vo ov<a/>>> :c CSJ O O O 0in0 vo o oo m ' O cm is. m rros t-H in *' oo co oin iniosOoo oo in co O m IS VO CSJ rH in O * CO CM MO- o> a. c>oI > VO Hsa>-- 4<-u> 4S)- 04<%c<0Jsiu',7uvoXQa3>j>_oCVasrod>>-)r oJa> 0-(O)) CO ;.c a -a; t O H-> c-- <u C.D o s: 404) r* U00I C a> 4) 45-> iJLl CO o i icinno cin ovo oo * .00 H Uco) CinTtJoVOdN in co co oVvOnDCiOn *Om--i odt.** 00 C\J VO <T> OO rH co in ci o intco in rt IoS. tOnin.nVO vo rs Co rH CM CM CO rs o m o *' lO Cs * CO CM O co 0> is. VO vo * * CO 53* CM Ci r*. CO VinO vo * CO * H * * co c Sf rs vo risH* CoOn in <r CO 5t is o Ps VO 00 <71 in * co*co * in co o rs rms vo m O oo * 00 CM rins vo oo os vo ci m in in rs oinun rms n CO rH rH fS O 00 Cm IP CM rs rH . CO CM co .CinO oino * ion is. ci rH oo O 't H 00 imn * rs oo oo o ' ffe.J rd ro Cl CD 'i" 3 4) oe; :7? . is com rs o I cino m et o> oo in ^ CO 00 mlO lO t rH . eo a* VO 00 H rH rins vo o o co rs riHns00cVoO H00 uo CO Cl .3 1d0 22L 0o)> a: ! GO 1 .00 00 rH 00 compel m ** co vo m oo co co mVO VO M* * co o> rs co vo rs iisn vo co o rs co oCM CO 00 m O ' m CO Cl OISO^N < aint uoo co | '*00 10 c vo co oo miomH ir> co On C CM <3* CM NinlOHC O ro rs IS, rH rH Cl omin rs. o *' * CO rH vn cn O V) to -Q U _J CD Q- <U I-- +-> C c 41 o +eJ 44-1 73 VO OO <v if) 13-3 to 73 CO < o o Q) vo +J </) 111 3 (/) U. o '7OJ S>*-1 o CJ i CM ox o 3 X rd oc c. s: S H o 73 a> to -- to UJ .3 vn u. o 7r3>2S *H > O <d -m CM1 o X <0 X ro CC QL z z X r--1 O 73 0) VO -M * V0 UJ d oo oz 73 uH-.< > o o rd 4-1 1 OXX CM O rd <d DC 0 zz t *H o 73 +aj; to vo UJ -X 25 V0 U. O *nzn o 73 > CJ 03 44 1 OXX eg re <o oc oc ^ S X 3C rH TEH 0530101 DUP050031014 -O a. VO vi S 3 S<fl <D H O z o *H CM fs* Ot CM VO 00 00 CM LT> * VO w ai sf vo co rs. rs,, vn st St VO o CM V VO Ot Ot rv. <n j co tn vn r>* at st rH r-1 Sf oo O rr> r*** VO st * st r-i vo VO CM rH O O CM vo vo st co H t-H st vo at O HOHiVj vo 00 sf r>0 rH VO rH VO 00 O vo rH * OCOl CM st VO O CO 00 H St St CM CM vo * ,* * St vo O OO 0 0 VO 00 00 OS* VO * CM st CO O CM , 00 <M 00 VO v 00 cn vo to *00 *t vn os CM CO CO O N CM t Ts* VO it * StrH st CM OO CM O 1-1 m vo CO st fs. CM VO rH *-H CO CM CM CM OHN CM VO O * st CM rH rH CO to CO CM a> rH CO CM to at st vo "st CM O CO N O n ro CM COO ST 00 vo st OO ac 00 CM *-H VO in .vo O rH 00 CM VO rH is. CM O VO vo *r>% * at rH CM vo CM CM. a> St VO St O 00 *t m * st O 00 vo ?? CO r" C 5-- < <u o 73 o OsJ ac.n a> CSD- vCQQ/>iJJ 5^ =<a3 XoQ. uj CaO> sn33ccor S3* ,(. -.j; <oo O 2 a> 44 Lu V11) cAwt CD 44 LU a> ' CO <uiJ WHOO 00 CM vo 0*^ to * st 4 st vo o rs vo 00 CM VO VO VO 00 * st NOOM CO CM vo VO VO rH st CM VO O St CM CM O VO CM vo . ts St rH St O CX) CM CM O O CM vo n-. * St CM t H |3t CSI CM O St CM VO v ^ St rM> -ON H> Ov vo st * St tNNCM is* CM co vo VO 00 st VO vo O rH hs. CM VO VO VO CM * t CM VO vo vn CM rH O vn CM VO IS* * st rH St VO O CM rH O CM CM VO is* CM ro is* vn -H rH vo 00 rs. CM . st st .r,7 ro---- p<?D. -rQO f6 5nS2 -O&t CD - 5gS II Q1 00 OO rH oo rH cr> r>^ CM CSjNtn CO CM 00 CM co r< vo O at at vo vo CM CO rH 00 is* CM 00 CM O vo vn to * * *? vo st at 5t vo vn t at O 00 vo 00 st <M st 00 at t rH CO St is* vo OO o o>--i a vo vo CO CM St CM VO -> * * f-s. CM O VO LO * rs* vo CM 00 ' CM <3- tp st at st st at v<v>u>Ty^i O) Q<Zv rH 00 *H VO VO fH CO 00 O st VO 0 vo VO 0 CM CQ at -' vo vo * CO CM St CM VO * CO CM O VO to fN. O at CM vn St VO st cr> ^ l*> st at <C 1 CVJISOIH <71 rH O VO VO * * St VO co b) co 00 CO fH VO CM VO . st at rH CO st VO 00 CM rH to to st is* at St rH CM IS* vo CM O CM to <A cn vo e jOa(Oail kdi e ca*: O 4EH: "<Oa0) vi c<a0 X<;I oCoU O 73 CD vo 4-> VO LU -X =3 V/> U. O r-5^ "H O 73 5> C-) A3 4-3 1 OXX CM O t q c pc s: s: CM 0 73 QJ to 4-3 (O UJ ^ 3r^ Vjr) >L--V1. OO 73 > O ft} 44 O I OXX 0 ns a: oc 2: s: X 13 0 4<4D -vo V0 u j 4^ 3 OO U_ O 7n3 S >m O O ns 4-3 CMl OO xIQ fXO oc a: s Z 3: CM O 73 <D 44 --VO VO UJ *3r-3 O50: Ut---1 O O 73 rd > 4-3 ^-3 CM1 OO X05 nXs Ct C S 2 X S CM TEH 0530102 DUP050031015 II - V-8 the detailed regression summaries for models A, E, F and G based on all adjustment sets and transformed and untransformed gasoline lead exposure terms. For Models A-D where a single gasoline lead exposure term (centered about overall mean) is included, the maximum variance inflation factor (VIF) is 10 or less and usually associated with the urban term. For the other models with more than orte gasoline lead exposure term, the VIF's are considerably higher and, as expected, always associated with the exposure Iw terms. The VIF's among the gasoline lead exposure terms in Models H, I, J and K are exceedingly large and generally have marginally poorer predictive ability than models E, F and G. The VIF's associated with survey demographic terms remain relatively small (ie, less than 11) for all models. For models using untransformed gasoline lead exposure, one site data record (Washington, D.C.) suggested marginal influence (according to Cook's 0 criterion) on the estimated model coefficients at the fifth-percentile F-distribution value of .60. However, in the case of the models using the transformed gasoline lead exposure, no influential site records were noted. Table V-4 presents a summary of the regression coefficients for models A and G based on Adjustment Set 2W. The corresponding coefficients from the analysis without gasoline lead exposure terms (see Table VII--6) are included in order to assess the impact of gasoline lead exposure on survey demographic effects. From Table V-4 it; is seen that the terms reflecting exposure to gasoline lead were flagged as significant (p<.05) in the presence of between-site survey demographic factors. In general, for models A-K the gasoline lead exposure terms were significant at or near the .05 level in all models where one exposure term (log transformed or not) was present or where log^Q GCUR75 and one other log transformed lag term were present. It should be noted, however, that when two or more highly correlated gasoline lead exposure terms are present (refer to maximum VIF's in Table V--3) the coefficients will be driven away from zero in opposite directions. For example,for model G the lagged coefficient is -1.70 suggesting, by itself, thatthe higher the lagged gasoline leadexposure, the lower the expected blood lead level. This I TEH 0530103 DUP050031016 - V-9 - Table V-4 Coefficients Compared in Analyses of Adjustment Set With and Without Gasoline Lead Exposure Model Terms Without Gas Pb Exposure Coeff. t-value With Gas Pb Exposure Model A Mode l G Coeff. t--value Coeff. t-value Black ,34* 2.00 ,20 1.16 .12 .73 Male 41 ,78 .52 1.04 .35 .73 Child .54 1.65 ,24 .71 ,14 ,41 Teen 1.09 1,78 1.34* 2,24 1,06 1.80 Income ,53* 2.43 .52* 2.47 .45 2.21* Bl_MA 8.59* 2.08 7.39 1.85 4,97 1.25 BL_CH -.30 -.23 >16 .12 .85 .67 BL_TN -1-26 -.41 -.62 -.21 -1.73 -.60 BL_IN 1.74* 1,34 1,73 1.39 1.78 1.50 MA_CH -11.49 -2.16 -9.86 -1.91 -6.39 -1.23 MAJ'N 2,28 .16 4.77 ,35 7.91 .61 MA_IN Si CHJN -.43 .50 -.12 ,21 -.46 -.46 -.14 -.20 -.30 -.69 -.09 -.31 TN_IN -2.35 -.49 -.91 -.19 1.34 .29 Urban .22* 2.61 .08 .76 .03 .32 CC -.17 -1,59 -.14 -1.25 -.08 -.78 Winter -.12 -1.83 -.14* -2.19 -.13 -2.14* Spring .04 .61 .01 .15 -.09 -1.21 Summer .06 1.05 .06 1.02 -.03 -.43 South -.09 -1.05 -.07 -.93 -.07 -.90 West .09 1,27 .15 2.02 ,09 1.27 Northeast .10 1.71 .07 1.29 ,03 .61 Lead Wt 9.7(xl0"-7) .14 27.5(xl0"7) -.41 24.2(xlO-7) -.38 1og10 GCUR75 log1Q GLAG375 .12* 2.11 1.82 2.25* -1.70 -2.11* | flagged as significant at P. 05 TEH 0530104 DUP050031017 - V-10 - interpretation is: clearly implausible. It is well known that the individual coefficients among highly correlated terns provide little useful information. At best, the impact of the fitted exposure coefficients may be evaluated as a set. The other aspect of the results in Table V-4 to be noted is the comparison of survey demographic coefficients. Following the analysis presented in Section III, inclusion of the single gasoline lead exposure term changed the t-value by more than one unit only for Urban; inclusion of two exposure terms resulted in a one unit t-value change for Black, Child, Urban, Spring and Northeast. Comparing coefficients between Models A and 6, t-values for Spring and Summer changed by more than one unit. The VIF for logjQGCUR75 is 7.50 in Model A which implies 86.7 percent of the variation in log10GCUR75 can be explained by variation in survey demographics. For Model G, the VIF for log2gGLAG375 is 1734 which implies over 99.9 percent of its variation can be explained by survey demographics and log^0GCUR75. From this perspective it is doubtful that additional information can be gained by including, in general, more than one term for gasoline lead exposure. V.B Estimation of Blood Lead Decline Attributable to Site Specific Gasoline Lead Exposure, . ________________ . In this section,, three approaches to estimating the contribution of exposure to gasoline lead are examined, The first compares residual trends from between-site models with and without gasoline lead exposure terms. The second employs the regression coefficient of gasoline lead. Tne third uses a time coefficient adjusted for survey demographics and gasoline lead exposure. TEH 0530105 DUP050031018 V.B.l Comparison of Residual Blood Lead Time Trends Following the same basic approach as described in Section III.D, residuals from between-site Models A-K (based on adjusted site blood lead means from within-site analyses and transformed and untransformed terms for gasoline lead exposure) were regressed on site mean examination date. This residual blood lead time trend is the trend that remains after the effects of survey demographics (P, R, and I terms) and gasoline lead exposure have been removed. Comparing this time trend to the one obtained when only effects of survey demographics were removed provides a way to isolate the contribution of gasoline lead exposure to the reported blood lead decline. Table V-5 provides a summary of these results for all models and situations evaluated. The residual decline Ug/dl) is estimated by computing the difference between the predicted residual blood lead at the mean examination date of all venous blood lead examinees at the first site sampled (Day 16.46 after survey began) and the last site sampled (Day 1452.93) in NHANES II. The contribution of exposure to gasoline lead is then estimated by comparing residual blood lead declines from Models A-K with that associated with a model only accounting for survey demographics. Df the 88 analyses performed, estimates of the contribution of gasoline lead exposure ranged from .11 to .67 vg/dl. Models 6, F and E, based on Adjustment Sets 2 and 2W, were identified in the previous section as giving the highest adjusted R -values. The contribution estimates from these analyses were all .52 ug/dl, which reflects approximately 10 percent of the reported blood lead decline. TEH 0530106 DUP050031019 <s Si XI 33 J3 03 03fflO3'<tNCSHH'fl'O N NN IA *A K> l<A IA fA HU> HN NH (SI N N 9S >0 N K\ IA IA Ift ^ IA ^ CO -rt si T5 8 C wSO a x o UJ *H Lj J o XJ CPD 3 XI 0) *g a O to <3 ~8 3 58 co -H s 3 X3 *2 0> OS '< X 8 #X->H UJ 2 TJ CD . 3OHH .<0 ao 0) C 4J BQ B 5 , CO *H XJ <v -p o 8- a; *-< t4o) 5JO. os 3* OXt1 w. | 2w oc *a a 2o < 8 c CoJ 58 H s XJ o 0:* 4J 0 . p H 1/3 COCDfflfflN<T^UUnOO n n nn n nn n nn n (eSg Qeg 0e0g hN J^A NIA NIA OIn wH ^ O OwH N O OS h rH <r ' ' g w n eg oo tA eg eg HHHH,lftlAIAIA(AlA'0 W eighted le a s t squares - w eighted by r e c ip r o c a l o f th e v a ria n c e s o f th e a d ju s te d s it e means. a n eg <9 eg er eg V eg V a eg eg q eg < -e 4 ^ o a p h p os IA V ^ V V V A V 3o orAs on V ^fA inrA g fV 31 to r*4 N N H W IA IA ON O I'H #-( rH *H in >V p V ^ to NO NNOMOCs SONsNNnNrANiANlANOAN 00 too On to O On IA-5T<IAHONOS AAAg' sJ eg --i -s eg V to ox o n rA >o U> (A JA A A lA AO #'OHAOOAMAWP # .A >A A H p CD eg eg a o> <auouitUiHni,! s 3 8a H "8 *8 1 ^ s03 4J < CD c.) o W U. C3 x ** to SX TEH 0530107 DUP050031020 - V--13 - The analyses of Models A-K are not conditional analyses where terms for gasoline lead exposure were fit after the survey demographic terms. Rather, residual blood lead time trends were evaluated from two separate least squares analyses where all terms were simultaneously fitted each time. Because of this, it is felt that this is a viable and fair approach to isolating the contribution of gasoline lead exposure to the reported blood lead decline. All of the residual blood lead declines (.93-1.51 ug/dl) from Models A-K were significantly (p<:.05) greater than zero. Therefore, the individual coef ficients of model terms will be biased to the extent that they are correlated with unaccounted for causes of the remaining trend. However, it is felt that the approach here, which computes the gasoline lead contribution by differencing, diminishes the impact of biasing in the individual regression coefficients. A single term for time (Days_Pb) was included in the residual regressions from Models A-K. Although this may not be the best model to estimate the blood lead decline in all analyses performed, for purposes here and in view of the data limitations!, this seems to be more than adequate. Figures V-l and V-2 j are plots of the corrected (residuals plus overall mean) site means versus site mean examination date for Model G based on Adjustment Sets 1W and 2W, respectively. These plots typify the general linear behavior present in all analyses. The details of the regressions of corrected site mean blood leads on time are presented in Appendix 6 from Models A, E, F and G based on Adjustment Set 2W. According to Cook's D criterion, no sites were identified as influential in these analyses. ' -H y TEH 0530108 DUP050031021 Figure V-l Corrected Site Blood Lead Means from Between Site Model A Based on Adjustment Set 1W 1% Uu P P Ii M lI N ft sn i ft f!1 UP U P _P I*tJ \% ! ! I8 uu To pp u 4 !I 8Ul III life 35 +O II SK I1 P tI P P !II I \KfeH* IP* NJNO Pu OP s $o t j * + * - o r* * in . +. p m i#I i N\iCnO 'ft P OT (0 TEH 0530109 DUP050031022 Figure V-2 Corrected Site Blood Lead Means from Between Site Model A Based on Adjustment Set 2W 3 I . 5 02/26/76 07/25/76 12/22/76 05/21/77 10/10/77 03/17/70 00/16/70 01/11/79 06/10/79 11/07/79 04/05/00 DUP050031023 - V--16 - One last set of between-site analyses were performed to evaluate the contribution to the blood lead decline of gasoline lead exposure by comparing the trend present in the adjusted site mean blood leads with the residual trend based on a model accounting for effects of current exposure to gasoline lead (and lead weight) but not in the presence of survey demographics. These, analyses are summarized in Table V-6 and follow the format and interpretation of the entries in Table V-5. The estimated contributions range between .27 and .75. ug/dl. Interestingly, even when ignoring effects of survey demographics, the single term for exposure to gasoline lead is estimated to contribute only slightly more to the blood lead decline than when survey demographics are accounted for. V.B.2 Use of Blood Lead/Gasoline Lead Regression Coefficients In each of the analyses with Models A-K, regression coefficients associated with gasoline lead exposure terms were estimated. In this section these coefficients are used to estimate the blood lead decline during NHANES II attributable to gasoline lead exposure. In order to do this a reliable measure of gasoline lead exposure at the beginning and end of NHANES II is needed. Since the blood lead-gasoline lead coefficients were based on 61 of the 64 survey sites, the contribution of gasoline lead exposure should be evaluated based on the change in gasoline lead exposure during the survey that collectively occurred for these 61 survey sites. V.B.2.a. Description of Computations Three computational methods were investigated to evaluate the collective change in exposure to gasoline lead at the survey sites. Basic to the computations was either a state or national gasoline lead use value associated with the beginning and ending quarters of NHANES II. These lead use values were then converted to gasoline lead exposure measures analogous to GCUR75, GLAG75, GLAG275 and GLAG375, TEH 0530111 DUP050031024 dn fN CM to C o n trib u tio n (u g /d l) to Reported Blood Lead D ecline QCJ d *r-- S32i. rC--J QQJ x: A93* d So-> QQJ d a. R++CJj.'' dC(o0D Ol a? CM CO CD &. 00 O L4QOJJ C2Ll Mr+OQC--->J- X) CJ QJ tO CD qO j d ci a. T- TJ Cn < vi :i C5 K'.o s- 4-> o 5 QJ c <u d *r-- St. r-- i3. XI o QJ CO CD o CL X ~*o3 QJ JV r--1 LO to *3* to O<T> CO C<yM r**% CM |-n H to to AO to r*. AtoO to CO O' co eQJ: o QJ to3 CD C to r*> [4Qex5.* *ro--r- to to to CO os II O Q to +qJj e(O `f QJ 00 3E tj d QJ Q_ to t3 3O **o>*--O < co to r*. G os o i. CD 4- SZ to 4-> r-- *r<Q .SB Srr- QJ <S) TD QJ O e* s: EO s- 4- to I--CrO d 4r---> QC 3 3U d3 10 *"QOJ o ioH O' QJ O etc ae o TEH 0530112 DUP050031025 - V--18 - Gasoline lead use values were linearly interpolated from quarterly values (associated with midpoint of the quarter) to arrive at a lead use figure associated with no lag, 30-day lag, 45-day lag and 60-day lag. The quarterly values are given by site in Table IV--3. Table V-7 provides a summary of these times in terms of NHANES II study day and date. As before the blood lead decline attributable to gasoline lead exposure will be evaluated between the mean examination dates of the first (Day 16) and last (Day 1453) sites sampled in the survey. Table V-7 Summary of Reference Dates for Evaluating Changes in Gasoline Lead Exposure for the Survey Sites Start of NHANES II Day Date End of NHANES II Day Date No lag 30-Day Lag 45-Day Lag 60-Day Lag 16 3/7/76 1453 2/11/80 -14 2/6/76 1423 1/12/80 -29 1/22/76 1408 12/28/79 -44 1/7/76 1393 12/13/79 A gasoline lead use value was computed for each of the 61 survey sites associated with each of the eight dates above. These values are given in Table V-8 using the notation GS, GF, GSL30, GFL30, GSL45, GFL45, GSL60, GFL60, where "S" refers to start and "F" to final, with the lag time appended. Additional information by site on county population, state population, and county area that is used in the gasoline lead exposure calculations is contained in Table IV-2. TEH 0530113 DUP050031026 Table V-8 Current and Lagged Gasoline Lead Use At Each Survey Site At Beginning and End of Survey IN <0 I l* ut I W w I1 eO<O^OK)tflN^0NHl2|<ONHU)VllAIA^PSlfteNO<NN s b<to0<^<OdM<U0 tHHoflHeO NciogOm^|AO<NO9VI>?slr*!rOtnH(oMO<M9Ht'JIUA^lHCtoJNC9H>H9>H^KICrN*JnK*o1No>O^OHeO lV>V^r oMoeH^erteHHOHPHOHeeeoHHHMMrtHOH )m ,VtfJ* tII CPJ V) I f* (0 II H rinoeNHe^^4neM<h0fl4iAHNioeM4 ioh/*iH4oMo0oco<0Mo9*i1f.Kt^el ^*Uoe) i<cnro^Kt>flfonl0p ^^pim.O>ooLHonn<0 oN0iA9r**<r*oo*ooM^^,Aoo* ^pInii>nto^0no0 |inn o<*^M^tffl>w<0ecnoo a * >* ertoepep^OHi-iOH o ' o ' o o p o ' ' ' w k o ' o ' 1 O 1I tmo tI u. t HP^4^WMWPPlftH.NPDOPP5PO..HtfJ5N^AO PPH-PTIJMfNtMO^PbO9HOi<Oa^OMimH^(OHM<pAOpNNi(t0PinfllMA(ANNMNP9N<P?HpHPUNl)MPWO^0'lPf>tNfPi <pSHlNpOPH9>iCnMOPm IID 1 OHOOOOOMOOOOOOOOOOOOOOOOHNOOeo T>j |l| !*, t CSI 0 K> i $ mtol 10 t* (0 1 rt NrtO^O0O'M'NJNOOtO^eO^NI^PmN<OMOOKMNWOlfNlNNMHO*Ot OW<0MOlfOl-JOONK<|0NONU^> P'OHNnNH^PeHH P.H *0 to to HH pNprtin^noinH oiooeeopiooMHeoeHeHppepHH^io^oHeH 1 HHHHHrtHHHHrlHHHrlHHrtHHHi I H H H rl H H H H i ) 'I 5 r4inin<tN6.HUI04<NabHNMlit>eNOM OOOOOOOOOHHHHHHHHHK(\lCJCJMNrJ(\iNMNI I So ! m 01 ' * 4- n > is <o o- o *>i w * f* o- o * >i to. m m <o o- o m W IMM I rtHHHrtrtHHHHNWNWNMNNKrtW TEH 0530114 DUP050031027 Table V-8 (Pg. 2 of 2) Current and Lagged Gasoline Lead Use at Each Survey Site at Beginning and End of Survey f ------ *<0 OlflO 3ju?. !!j CqbSwS&ibffsS5n:22ia2;2oSiSf*2O!2Stlf5?in!22asBS2Sn^JtlSf;?iMti,H5'HjHWiHiir|str'w*tr^rttH*'"*>S^N*r*tp,M'i*H OfniooMin<*' IOf-l>-(HOOOOOOOOOOOOOO(-IOfbOOl-lrti-(r4rtJOrtO O II ON o0 S0 I p ? nHnSa6NGN"NNO2e&aiN941 <Ow >U"b*r<b*N*iiH">b*UoMo onlfbie<illii V> j 0 4 b MW H M b e IH HIA NOabrtl04?H ID I OnHK)HOHeHOOOHHeOOerieHOeHHHAl<inHH f:1 P II HNtef N*0<87N)O.ed,N94bMH(fOt.MOON(OKKlINKNiMNi0IiOd.lAba>)IWA0MMA^PMM'^40,0r-OflNO-Nfl>t KV I <>eO'OinHJ/lN<OiOCH!M'lfOCnrtMNOKi(0.-(?A7HOW 'J S : ) ^NOVOHOJnj-OrttflMfthN9'Ni6Hr ^ ~ ^^ OMHKIHOHOHO lertHeeoertOHOOHHHlO^WHO 1 MlNNttlNi10IMMNNNN NCM NMNNN(4NNMNNN<y(SI ^?< j!I HeONOKle^O|fle^Nep(feleH'OriHHHNiW^HtfHWHHOHNCJ^ONMHWMNrt^tgl/N|lflNNNON>MerrttWM <0 I ili-io il^<f |n^NO^eHNIOd,iA<0M9POHMK)^IA4NOOrfNrt^ 10 * TEH 0530115 DUP050031028 - V--21 - The first computational method, referred to as Method 1, evaluates gasoline lead exposure analogous to the method of evaluating GCUR75 for an individual except the individual components are replaced by averages based on the 61 survey sites. The simplified formula, where the summations extend over the 61 sites used, follows: S(Stat.e Gas Pb Use at time t)^ 2(County Pop, 75}^ 2($tate Pop. 75).. s(County Areas) . i1 This formula was evaluated using a state gasoline lead use at each time t shown in Table V-7. See Table V-9 for a summary of these evaluations. The second computational method, referred to as Method 2, evaluates a gasoline lead exposure by averaging the exposure densities of the individual sites. The formula is ^ (State; Gas Pb Use at time t). (County Pop. 75), S --------------------------------------- --------2---------- -------,-----------J- 161 i=l (State Pop. 75)^ (County Areas). This formula was also evaluated for each of the eight times and these values are given in Table V-9, The third computational method, referred to as Method 3, evaluates NHANES 11 survey site exposure to gasoline lead by proportioning national gasoline lead use at time t on the basis of the fraction of the U.S. population represented by the population of the sampled'counties. The formula is (Nat, Gas Pb Use at time t) ^(County Pop. 75)^ (U.S. Pop. 75) X (County Areas)i TEH 0530116 DUP050031029 - V--22 - National gasoline lead use was evaluated by linear interpolation between quarterly values that included each of the eight dates (Table V--7)* The relevant national quarterly values and associated dates are listed below. Date Nat. Gas. Pb Use (gr) 11/15/75 2/15/75 5/15/76 11/15/76 2/15/76 38,332,862,660 34,270,161,240 41,421,017,370 25,147,533,040 17,842,296,150 The other values used in Method 3 are 213,030,000 for 1975 U.5. population, 46,714,564 for 1975 total county population of 61 sites, and 72394 mi2 for total county area of 61 sites. The evaluations for the eight dates are shown in Table V-9. Table V-9 Total Gasoline Lead Exposure Values for 61 Survey Sites For Three Computational Methods Start No Lag 30-Day Lag 45-Day Lag 60-Day Lag Method 1 .000107344 .000103705 .000105391 .000107077 Method 2 .000150624 .000145220 .000148588 .000151956 Method 3 ,000108860 .000105024 .000107052 .000109081 End No Lag 30-Day Lag 45-Day Lag 60-Day Lag ,0000542747 .0000604188 .0000634909 .0000665630 .0000789113 .0000890318 .0000940920 .0000991523 .000055018 .000062313 .000065961 .000069608 TEH 0530117 DUP050031030 - V-23 - The v.alues presented in Table V-9 may be used to compute the change in exposure at 61 sites during the four-year NHANES II survey. This change then is multiplied by the respective regression coefficients, from models where gasoline lead exposure was untransformed, to get a blood lead contribution from each exposure term. The contributions of each exposure term then are summed to evaluate the total blood lead decline attributable to the gasoline lead exposure terms used in that particular model. For models where the gasoline lead exposure terms appear in log1Q form, the values appearing in Table V-9 need to be appropriately altered. For Methods 1 and 3, the logarithm of the values in Table V-9 was computed from which the difference between log exposures was applied to the regression coefficients. For Method 2, however, the computational formula was altered by averaging the 1 logarithm of the quantity in braces. These values at the eight exposure times are given below in Table V-10. Table V-10 Total Log Gasoline Lead Exposure Values for 61 Survey Sites Method 2 Start End No Lag -4.2670 -4,5493 30-Day Lag -4.2840 -4.4953 45-Day Lag -4.2743 -4.4714 sis 60-Day Lag -4.2649 -4.4484 For Adjustment Sets 2 and 2W, the dependent variable is on a natural log scale. The exposure regression coefficients, therefore, signify change in ln(blood lead) per change in exposure. Multiplying the regression coefficients by the change in exposure provides an estimated change in ln(blood lead). However, what is desired is the change in blood lead and this cannot be obtained by exponentiation of the change in ln(blood lead). The change in blood lead (ABlood Pb) is easily shown to be given by the expression j ABlood Pb * Bs(l-exp(-bA{Exposure)) TEH 0530118 DUP050031031 - V-24 where B$ is the predicted site mean blood lead value at the first mean examination date (Day 16,46 of survey) from a regression of Adjustment Set 2 or 2W on site mean examination date. Further, b is the gasoline lead exposure regression coefficient and ^Exposure reflects the change in exposure to gasoline lead. The values used for 8$ are 16,184 ug/dl for Adjustment Set 2 and 16.087 ug/dl for Adjustment Set 2W. V.B.2.b. Discussion of Results It was noted in Section V.B.l that between-site Model A provided the highest adjusted Revalues among models where the gasoline lead exposure terms were untransformed and Models G, F, and E were best among models where the gasoline lead exposure terms were log-transformed. Gasoline lead exposure contributions to the reported blood lead decline based on regression coefficients for Models A, E, F and G and each of the computational methods were evaluated. The gasoline lead exposure regression coefficients are given in Table V-l.l for these models, based on Adjusted Sets 1, 1W, 2 and 2W. The estimated contributions by gasoline lead exposure to the reported blood lead decline during NHANES II are summarized in Table V--12. The results associated with Adjustment Sets 2 and 2W were exponentiated so all contribution estimates are in terms of ug/dl. TEH 0530119 DUP050031032 Coefficients of Gasoline Lead Exposure Terms co CO CD < -J to CD E S0) H- CD CO $- 3 CM t/i CD O< CL _J X CD LU 4O V ir> o 4- CD (/) C .id CD h* cn o on on r-H CO co CM | rH LO on CM CO CM 1 O on .9 co co 1 CO co cr> to *-H ONcc *0t*t CO CM rD CO CO 0> do .* CO rH 01 co CO <\J CM IN df CO CO CO CM 1 CM IN. CO d-* co CM 1 CO r-H rH to CO 1 ^a- co co o O co co r-H H CO CO O O^f * : rH CO O CO 00 CO CM CO H rH IN rH 1 CO CO rH rH CM l oo IN dT IN CM i o> co rN rH CO CO rH VO CM CM iH CO CM CO CM CM rH IN *3O IN r rH 1 LO CO on o CM 1 m or rH IN CM 1 OOlNCJ h* co oo ' ro o <M r- CO CM CO CM CM H CO CM on On |N r CO dr 00 IN CD a* VO CO CM ca: to co On On LO VO 1 1 CD rH rH <V S- CO CO rH IN rH o rN .* </) CM CM CO IN IN o CD CO CO ' 3- o XCL < on o CM 00 CM rH CO rH UJ CD CM CM 1 1 U o CO 4- IN V> CD crd c i. CD CM . IN IO co VO CO 00 *d IN CM on co O co on CM co 1 on K. CM CM 1 *nCO 5T co o co co oo on dr Oi O CM CO ' <j- *3* os fNrtl^NOlVO on co co <d* 00 On CO CM O =3 HNOlfs N, LO CO CM IS. CM CO CM NNOlO O IO rH in o ia- co CM CO CO CM CM to in CM CD HIDO M-CQCOO CM H rH CM H H CM CM dfr CM CM I c <V r-- <3US-(PD TD3 +0->> -CrO- sO oo <lxl U.CD <OJU-<D < LU Ll CD < UJ U. CD cO .Q OfClOL +J <Z o; co `n co id 13 co <c TEH 0530120 DUP050031033 Estimated Contributions to Reported Blood Lead Decline By Gasoline Lead ExposureU) s 014o- CO O -J tco to -o s- o _c p E 2! 4vfT-3i ih C0 91HO O') 0> CD CM CM CM VO CM VO CM 45 o o>CO T-H CM < 00 CM CM *3v> co fv CM < lO CM VO 00 CO to CM H O 00 co ro VO CM tf> CM VO tO ^ VO 00 O CM tO CM rH O 00 CO CO CM VO tO ^ E 0tam cn40 to --1 CM <0 * O 4-> E (V 4 CO 2: to jh to O LO to ?* O *3* r-4 .. 00 CM CM CM i"M CT> rH co O Z vo v VO CM l>s CM O 00 00 * CO CM CM CM tO -l CM 00 OMSVO .# O CM H CO to pi 00 rs. CM CM CM CM O) OVCM U)NN 1 CM CM CM CMOOlO CM 00 O' O) 00 i v VO CO 00 VO 1 . >4- V) -J <0 S- O x: os2O 4V~) >to C^O Oh> 0vc0 CvoO CM CM CM i-H CO CO CM VC ^ CJO* CM CVCO CVOO CM CM CM ^ CO OV5f CM VO ^ co n to rs to o> CO c> CM CM CM CO t-- 00 CM CM VC ^ to CO CO 10 01 00 r>. CM CM CM M1 ONiH CM VO ^ 'tj' c1 (SU+J*rD" P *r* O to s: CD -Q CL *<fOO/> C*!"oQ>+</J> cp ac < UJ Li. O <C Lul Ll_ O < UUU. QD < UJ la- UJ C o Veoo)> "O oCT>> > 4c->n , ^ tO ,-S. -2Q -o hto* U~ 1 .n3 a? .- X vt3uoo X3 u5 Vf- %>b^ .^5 <</v> t &- to to Pc to 1" T5 0 r-- (0 44- Li O ft U UJ V) O P-- to to T3 S- 55) %m O 0 to im 3 4-> to 0 S CL r-- X P to UJ " to iH TEH 0530121 DUP050031034 - V--27 The results displayed in Table V-ll, which are based on regression coefficients of gasoline lead exposure terms, lack the consistency of the results reported in Table V-5, which are based on a comparison of residual trends. The estimated contribution to the reported blood lead drop for Model A ranges between .24 and .52 ug/dl, somewhat comparable to the Model A results in Table V-5 where the drop was from .14 to .35 yg/dl. However, the results for Models E, F and G are substantially different from those in Table V-5. A closer inspection of the results in Table V-12for Models E, F and G reveals why these values are erroneous. In computing the estimated blood lead decline, contributions from each gasoline lead exposure term are evaluated separately and summed. For example, the change in blood lead associated with changes in each exposure term may be written ABlood Pb a A(Exposure) + b A(lag Exposure) where a and b are the estimated regression coefficients associated with the respective exposure terms. For the situation here the b~coefficient is negative (see Table V-ll) for Models E, F and G because of the high correlation between the two exposure terms (see VlF's in Table V-3 for these models). Further, both coefficients are driven away from zero although their sum is close to the regression coefficient based on a model with a single exposure term. The result of this is an expression for evaluating ABlood Pb which is inadmissible since the true coefficient for the lagged exposure must be nonnegative; otherwise, an increase in a(Lag Exposure) serves to reduce ABlood Pb. To show this anomaly another way, note that the change in current exposure (GCUR75) is greater than the change in any of the lagged exposures (to see this compute exposure changes based on the data in Tables V-9 and V--10.). This is true for untransformed or transformed exposures regardless of exposure calculation method. This results in an upper bound on ABlood Pb as follows: ABlood Pb < (a+b) A(Exposure). TEH 0530122 DUP050031035 - V-28 - Thus, applying the change in current exposure to the sum of the coefficients provides an upper bound to the contribution to the reported blood lead decline due to exposure to gasoline lead. For comparison purposes, these results are shown in Table V-13. Note these conservative estimates are all well below the corresponding values for Models E, F and G in Table V-12. The range of upper bound estimates is .23 to .56 ug/dl. The corresponding range based on the comparison of residual trend results in Table V-5 for the models is .32 to .85 ug/dl. The agreement is now remarkably similar. Table V-13 Upper Bounds to Estimated Contributions to Reported Blood Lead Decline by Gasoline Lead Exposure Based on Between- Method 1 Method 2 Method 3 Adj BPb Site No Log No Log No Log Set Model Transform Transform Transform Transform Transform Transform 1E F G .26 .47 ,35 .45 .25 .48 .33 .44 .24 .49 .32 ,45 .26 .49 .25 .48 .24 .49 1W E F G .25 .48 .34 .44 .24 .47 .33 .43 .23 .49 ,31 .45 ,26 .48 .25 .47 .23 .49 2E F G .25 .54 .34 .50 .24 .53 .33 .49 .23 .54 .31 .50 .25 .54 .25 .53 ,23 .54 2W E F G .25 .55 .34 .51 .24 .54 .33 .50 .23 .56 ,31 ,52 .25 .55 .25 .54 .23 .56 Results based on ridge regression estimates for Model G are discussed in Section VI.B.2. The estimated contributions due to gasoline lead exposure are smaller than those presented in Table V-13. TEH 0530123 DUP050031036 - V-29 - One further set of analyses was done using the regression coefficient of GCUR75 from models which excluded the between-site effects of survey demographics. These coefficients, along with those previously reported for Model A (Table V-13), are summarized in Table V-14. Note that the gasoline lead exposure (GCUR75) coefficients, with one exception, are larger when between-site survey demographics are not accounted for. This is not surprising since certain demographic factors and gasoline lead exposures have been shown to be related to time and blood lead. Consequently, the gasoline lead exposure coefficient attempts to account for aTl_ time related changes due to survey demographics, gasoline lead exposure, and other time-related causes. The estimated contributions to the blood lead decline are given in Table V--15 based on the blood lead/gasoline lead exposure slope for models not accounting for between-site survey effects. These values which are conservative show a range of contribution estimates from .29 to .59 vg/dl. Table V-14 Coefficients of Gasoline Lead Exposure Terms From Betweer-Site Models Not Accounting for Survey Demographics Based on Adj BPb Set Between- Site Model Gasoline Lead Expose Not Transformed Log Transformed 1 Model A 4513.4 No Survey Dem 5486.0 1.6044 1.5523 1W Model A 4479.5 No Survey Dem* 5463.5 1.6124 1.7422 2 Model A No Survey Dem 274.9 383.1 .1109 .1143 2W Model A No Survey Dem* 279.4 375.4 .1170 .1270 Except Lead Wt TEH 0530124 DUP050031037 - V-30 Table V--15 Estimated Contributions to Reported Blood Lead Decline by Gasoline Lead Exposure Effects of Between-Site Survey Demographics Excluded Computational Based on Method Adj BPb Set . Method 1 1 1W 2 2W Method 2 1 1W 2 2W Method 3 1 LW 2 2W V.B.3 Use of "Time11 Coefficient Form of Exposure Term No Transform Log Transform .29 .46 .29 .52 .32 .54 .32 .59 .39 .44 .39 ,49 .44 .51 .43 ,57 .30 .46 .29 .52 .33 .54 .32 .59 Analyses were performed on Between-Site Models A and G with a time term (Days__Pb) added to estimate the time coefficient adjusted for survey demographics and gasoline lead exposure. These analyses are similar to the ones discussed in Section III.E.2 except that now terms for gasoline lead exposure are included. Ostensibly* such a time coefficient could be used to quantify the contribution to the reported blood lead decline not due to survey demographics and gasoline lead exposure* However, it was noted in Sections I.B and III.E.2 that this does not occur. This time coefficient will capture all the linear time components associated with all other model terms not themselves corrected for time. TEH 0530125 DUP050031038 - V--31 - The results of the analyses with time are included for completeness. They illustrate the above fact on the interpretation of the time coefficient as well as present additional Insight into the relationships among survey demographics, gasoline lead exposure and time. Table V-16 presents the regression summaries from these analyses for Model A (results for Model G were similar). As was noted in reference to the analogous Table V-16 Between-Site Regression Results of Model A with Time Term No Transform Root MSE n2 rV N Error Degrees of Freedom Max VIF Max Cook's D GCUR75 Coefficient Time Coefficient Time VIF 1 2.57 .79 61 36 JDdbttU un nujuvumsnv oci 1W 2 2.61 2.91 .78 .80 61 61 35 36 2W 2.93 .80 61 35 6.91 .75 2192,7 -.00373* 3,74 7.87 .70 2227.4 -.00373* 3.75 6.91 .44 99.59 -.000281* 3.74 7.87 ,40- 108.5 -.000283* 3.75 LogioTransform Root MSE oZ kV N Error Degrees of Freedom Max VIF Max Cook's D Log1QGCUR75 Coefficient Time Coefficient Time VIF COo 2.51 61 36 10.45 .21 1.118* -.00386* 3.47 Flagged as significant at p<_.05 2.54 .79 61 35 10.80 .19 1.188* 2.78 .82 61 36 10.45 .19 .0752* -.00388* 3.49 -.000283* 3.47 2.78 ,82 61 35 10,80 ,15 .0856* -.000287* 3.49 TEH 0530126 DUP050031039 {iiiiaiM i: - V-32 - summaries in Table III-10, inclusion of a time term greatly improved the prediction precision. Residual regressions against time from these analyses demonstrated no time-related effects remained. The variance inflation factors (VIF) associated with time indicate over 70 percent of the variation in time & is explainable by survey demographics and gasoline lead exposure. Table V-17 summarizes these estimated blood lead declines for the variations of Model A analyses, using the time coefficient adjusted for survey demographics and gasoline lead exposure. It is seen that these declines are comparable to the declines associated with the adjusted site mean blood leads (see Table III-8). Consequently, these results illustrate that the time coefficient, even though adjusted for survey demographics and gasoline lead exposure, accounts for time-related effects of both survey demographics and gasoline lead exposure. Table V-17 Estimated Blood Lead Decline (pg/dT) Based on Time Regression Coefficient Exposure Term for Gasoline Lead Model A Results Based on Adjustment Set 1 1W 2 2W a Untransformed 5.36 5.36 5.38 5.37 T ransformed 5,54 5.57 5.41 5.44 The impact on the regression coefficients of Model A results before and after, including a time term, is shown in Table V-18. As was concluded from a $gfj w similar comparison shown in Table III--12, the addition of a time term changes m many (10 to be exact) of the t-values of the survey demographic effects by at least one. The corresponding impact on the gasoline lead coefficient is more clearly identified by comparing these values in Table V-16 with those in ffi Table V--1.1 for Model A,. Here it is seen that the gasoline lead coefficient is substantially reduced after inclusion of a time term - by a factor of more than two in most cases. Refer to Section V.D for further discussion on the relevance of this observation. t ''j f .&J TEH 0530127 DUP050031040 m' > M - V-33 - Table V-18 Coefficients Compared from Between-Site Model A Results With and Without Time Using Adjustment Set 2W Without "Time" Coefficient t-value With "Time" Coefficient t-va.iue t-values differing by at least Black Male Child teen Income Bl_MA BL_CH BL_TN BL_IN MA_CH MA_jN MA_IN CH IN T N_IN Urban CC Winter Spring Summer South West Northeast lead_Wt GCUR75 1og10GCU.R75 Days_Pb .20 .52 .24 1.34* .52* 7,39 .16 -.62 1.73 -9.86 4.77 -.46 -.46 -.91 .08 -.14 -.14* .01 .06 -.07 .15 .07 1,16 1.04 .71 2,24 2,47 1.85 .12 -.21 1.39 -1.91 .35 -.14 -.20 -.19 .76 -1.25 -2.19 .15 1,02 -.93 2.02 1.29 27.5(xl0"7) -.41 .12* 2.11 ,41* ,06 -.27 .76 -.11 3.16 .98 -1,12 -1.10 -6.76 -8.81 -2.52 -1.70 1.58 3,48 .17 -1,15 1,90 -.67 1.18 1.15 -.57 -1.21 -1.99 -.97 -1.13 -1.12 .51 -.06 -.03 -.11* -.02 -.12* .10* .06 -.78 -.44 -.25 -.47 -.47 -2.31 2.06 1.56 49.1(xl0-7 .086* 2.34 -.000287* -7.00 CM r~i i H 1 COM t X X X X X X X X X Flagged as significant at p.05 TEH 0530128 DUP050031041 - V--34 - V.C Estimation of Blood Lead Decline Attributable to National Gasoline Lead Use The unsuitability of national gasoline lead use as an exposure correlate to NHANES II blood lead data was demonstrated in Section IV. There it was shown tnat the gasoline lead exposure trend, as encountered by the survey site itinerary, is considerably different from the trend in national gasoline lead use during the survey period. Consequently, the fact that national gasoline lead use does not account for site-to-site variation in exposure limits the suitability of this exposure correlate. It may be argued that some global measure exposure needs to be incorporated in order to account for such factors as import of lead contaminated food inside, or personal travelling outside, a geographic location. To this extent, incorporation of national gasoline lead use in between-site models with survey demographics should provide upper bound estimates of the real contribution of gasoline lead exposure. Between-site analyses were performed based on survey demographic terms and national gasoline lead use. The national gasoline lead use values were taken from [3]. Table V-19 presents a summary of the residual blood lead time declines and portions of reported blood lead declines attributable to national gasoline lead use. These summaries were obtained in the same manner as those in Table V-5. The results show that national gasoline lead use contributes between .78 and 1.12 ug/dl to the reported blood lead decline. The upper bound estimates are approximately twice those when using the site specific gasoline lead exposure correlate. TEH 0530129 DUP050031042 O .* r- VO xi <d co O Z P 0) 3 t t/7 J3 P =D rr <d U SS'TJ P id -POO < P P r-- XJ Id Q- O 3C 3 3*1*r- O '-- vo O O <L> r* Q) QiCQO i VO LO H CM H i-H d* d" CO CO CO vO O r~ Vi OJ J3 o Id CD C po 3 </> CVJ DWD rH aJ a r d s- Z5*p i H =D 4-> <d POO 155-s0 4-) CSJ <C p P O VO r--,0 Id Q- O 3C g 3CTl Sog "g ^ C4> co T3 T3 *r* r- o -- vO LO "5CiOn/3j v> o o O ** O OS 00 O o r- i/7 -H d* a|>I S- _ JU <d Id CD PO 3 J* VI S QJ sj "ftOt/1J<0 o-Q P id O .r0* P<0 ID S. Z 13 p id 1 rH| Z 03 p o o <pp r>* 00 ' <r> VO T-H " co ,o5>3! C*Hrd .2 J SX -p r- 5 oo p-- 43 Id Q_ O 3c 0 3^ `i~' O iVI o o <D p- O o co o a> * r* V) xi <d <d CD pO 3 </ DP3 r- fd *- 55*0 P id Poo <-p J CM VO rH 1 Sf LO .* r** O * H rH CD 00 r*>< r- Q id Q. O .i 3C *3 T3 " *- o -- CSJ VO LO to <cdo* V0 O O O I-- o t-H CO O * C? H V) oi/J 33 q j id 53 p => l Q O CD Q id S JO >> >> O >i a. <v p-* ;* o o O > >> O P v) > id ID O 3) > S- #-- Lz S- P V) O '!- .3 C 3 JO 3 *d .,^1\ co 1*0 s: CO O co -f a. 00 + CD u fl ki TEH 0530130 DUP050031043 V.O Summary A variety of analyses and approaches are reported herein which address the contribution of gasoline lead exposure to the reported 5-6 vg/dl blood lead decline during NHANES II. Collectively and consistently, these analyses suggest that, while gasoline lead exposure is significantly associated with blood lead levels, its contribution to the decline is only between .25 and .75 ug/dl. The results based on the best explanatory models, where the natural logarithm of blood lead was used as the dependent variable and site specific gasoline lead exposure (ie, densities) were expressed in terms of base 10 logarithms, was about .50 vg/dl, This value is remarkably consistent with that obtained by multiplying the (crudely) estimated air lead decline during NHANES II of ,32 ug/m^ [8] with the widely agreed blood-1ead/air-lead slope range of 1-2 m3/dl [9], The measure of exposure to gasoline lead used in these analyses (except for Section V.C) reflects exposure at each survey site at the time that site was sampled. This aspect is of considerable importance since it was determined that the gasoline lead exposure time trend corresponding to survey itinerary differs considerably from the four-year trends seen nationally or, for that matter, at any of the individual survey sites. Naturally, no index based on state or local lead use, population and area can be expected to accurately reflect individual exposures. To do this, personal monitoring data would be required which clearly is unavailable. Consequently, some specification error in exposure will be present which would have the effect of underestimating these regression Coefficients, Summarizing in more detail, three approaches were investigated for estimating the contribution of gasoline lead exposure. In the first, the difference between residual time declines was made based on models with and without gasoline lead exposure terms. Effects of four exposure terms were investigated - one reflecting current exposure and the others reflecting 30, 45 and 60-day lagged exposures - in eleven between-site models. Each model TEH 0530131 DUP050031044 - V--37 - was analyzed using adjusted site mean blood lead sets from within-site analyses 1, 1W, 2 and 2W. Exposure terms were expressed in untransformed and log transformed form .in each analysis variation. The best predictive models were those containing just the current exposure term or the current with one other lagged term. The estimated contribution due to gasoline lead exposure ranged from .11 to .67 jig/dl, with .52 ug/dl being the value associated with the preferred models. A further between-site analysis was performed where survey demographic effects were excluded. By comparing the residual decline m with the decline of the adjusted blood lead site means, the contribution of gasoline lead exposure was found to be between ,27 and .75 ug/dl depending on analysis variation. These results may be considered conservative in that survey demographics were not addressed. The second approach used the gasoline lead exposure regression coefficients to evaluate the blood lead decline by multiplying them by the change in exposure. The exposure change was computed to reflect the four-year change that occurred at all survey sites, regardless of when each was visited by the survey caravans. Three different computational methods were used to reflect collective survey site exposure changes and all gave comparable results. Based on a model which incorporated current gasoline lead exposure, the estimated contributions ranged from .24 to .55 ug/dl. The estimated contributions based on models which included more than one term for exposure proved to give inadmissible results, resulting from negative coefficients due to high correlations among exposure terms. Admissible upper bounds for contributions based on these models ranged from .23 to .56 ug/dl. A contribution was also estimated based on the coefficient from the between-site analysis where no survey demographics were included. These values ranged between .29 and ,59 ug/dl. It was noted in Section V.B.3 that inclusion of a time term in models with a term for gasoline lead exposure reduced the gasoline lead exposure coefficient by a factor of two. This smaller coefficient is the correct least squares estimate because it is adjusted for all other terms in the model (see, for example [11]) including time. However, the second approach used the larger I\ ij TEH 0530132 iJ DUP050031045 - V-38 - (biased) coefficient to estimate the gasoline lead contribution to the reported blood lead decline. The conservative value used would, in some sense, compensate for the effect of specification error on the regression coefficient noted above. The third approach was based on use of the regression coefficient for "time" in models with terms for survey demographics and gasoline lead exposure. It has been noted that this approach is incorrect for estimating the portion of the reported blood lead trend not due to either survey demographics or exposure to gasoline lead. Based on the results in Table V-5, it appears highly likely that causes other than survey demographics and gasoline lead exposure were responsible for Some of the reported decline. This unexplained decline was significantly different from zero and ranged between .96 and 1.61 yg/dl depending on model and analysis. Likely candidates accounting for the unexplained decline include improved sample handling and collection during the survey, improved quality control, and other sources of lead exposure. Unfortunately, even marginally satisfactory data are not available on any of these candidates except improved quality control. Blind control sample results, available only after the first eleven months of the survey, provided a hint of a downward bias - at best, explaining only a portion of the unexplained decline. Although it wa;$ concluded in Section III that national gasoline lead use is an unsuitable correlate to NHANES II blood lead data, its contribution to the reported blood lead decline was estimated between .78 and 1.12 ug/dl. These estimates are approximately twice that obtained when using the site specific measure of gasoline lead exposure and probably reflect an upper bound to the true effect of gasoline lead use. Accurately and precisely estimating the true blood lead decline due to exposure to gasoline lead is not possible from these data due to inherent confounding among factor effects. It may be argued that a portion of the time related survey effects such as black, urban and income representation, actually incorporate some component of gasoline lead exposure, as well as TEH 0530133 DUP050031046