Environmental Health Perspectives Vol. 34, pp. 213-217, 1980



# Relation of 

# Pediatric Blood 

# Lead 

# Levels to 

# Lead in 

# Gasoline by 

# I. H. 

# Billick,* A. 

# S. 

# Curran,t and 

# D. R. 

# Shiert

Analysis ofa largedata set ofpediatric blood lead levelscollected inNew York City (1970-1976) shows a highly significant association between geometric meanblood lead levels and the amount of leadpresent in gasline soldduring the same period. This association was observed forall age and ethnic groups studied, andit suggeststhatpossibleexposure pathways other thanambient airshouldbeconsidered. Evenwithout detailedknowledgeoftheexactexposurepathways, suffcient informationnowexistsforpolicyanalysisand dedsions relevant to controls and standards related to lead in gasoline and its effect on subsets of the population.

Bloodlead levelsprovide ameasure ofhumanlead exposure 

### resulting from all 

### environmental sources. The 

### quantification of relations between environ

### mental exposure and blood 

### lead levels, 

### especially in 

### children, is of

### considerable 

### importance for

### assessing the 

### relative contributions of 

### various sources 

### of en

### vironmental lead and 

### for 

### judging the adequacy of 

### control measures 

### (1-3). The present report is part of a research program 

### exploring several 

### large data sets of 

### pediatric blood 

### lead levels collected 

### by local lead poisoning screen

### ing programs. We have 

### previously reported (4) on the 

### analysis of venous blood 

### lead levels of 178,533 New York 

### City children screened for the 

### first time 

### during 1970-1976. 

### This 

### investigation revealed a 

### sig

### nificant 

### relationship between 

### geometric mean (GM) blood lead levels and

### ambient airleadmeasurements 

### obtained from a 

### single sampling station in Manhattan. 

### We now 

### expand upon 

### and 

### refine these 

### findings by 

### considering another 

### possible indicator of lead exposure: 

### lead in 

### gasoline. The 

### protocol for 

### analysis of the New 

### York City data

### base was to 

### studyrelatively homogeneous sub

### populations defined 

### according to 

### ethnic group, age, 

### and 

### quarterly 

### sampling date. The blood lead levels

*Environmental Research Group, Department ofHousing and Urban Development, Washington, D.C. 20410. tCommissioner of Health, Westchester County Health Department, White Plains, New York 10601. lCenter for Applied Mathematics, National Bureau of Standards, Washington, D.C. 20234. February 1980 

### within each 

### subpopulation, which 

### closely 

### approximated a lognormal 

### distribution (5), were charac

### terized

### bytheir

### geometric mean 

### (GM). A

### typical plot of GM blood lead level 

### against quarterly 

### sampling date is shown 

### forblack and 

### Hispanic children, aged 25-36

### months, in

### Figure 1. The 

### GMblood lead levels 

### follow a 

### consistent seasonal 

### pattern 

### superimposed

on an overall 

### decreasing trend from 1970 to 1976. Also 

### graphed in 

### Figure 1 

### is the 

### (quarterly averaged) ambient air lead level over the same 

### time 

### period, measuredata

### singlemonitoringstationinManhattan by 

### the U.S. Department of 

### Energy, 

### Health, and 

### Safety Laboratory (6). Additional details 

### concerning the

### underlying data base and the 

### statistical 

### analyses performed are 

### described elsewhere 

### (4). An indication of the amount of lead present in 

### gasoline was 

### derived from 

### industrydata on 

### monthly 

### retail gasoline sales by 

### grade and state (7), 

### and from 

### the Bureau 

### of Mines semiannual survey 

### of motor 

### gasoline (8). The latter source reports the 

### gasoline lead 

### concentration in 

### grams/gallon by grade on a 

### regional basis. Data 

### for District 2 

### (Mid-Atlantic 

### Coast) have beenused in the present 

### study; 

### gasoline lead 

### concentrations were 

### obtained on a 

### quarterly basis 

### by 

### interpolating the 

### reported semi-annual values. 

### Figure 2 

### graphs the 

### resulting estimates of total amount of

### leadpresent in

### gasoline sold inNew

### York, New 

### Jersey, and 

### Connecticut over the 

### time 

### period 1970-1976, as well as the same 

### time series of 

### GM blood lead levels 

### given in 

### Figure 1. The 

### similarity in seasonal

### patternandoverall declinebetweenthe GM

21335

- BLACK
HISPANIC

E 1 AIR LEAD--

4m 30-

4 252.5

o ~~~~~~~~~~~~~~m

1970 1971 1972 1973 1974 1975 1976

children >

35

- BAC 10 1

_ \.0

1970 1971 1972 1973 1974 1975 1976

QUARTERLY SAMPLING DATE

FIGURE 1. Geometric mean blood lead levels of New York City children (aged 25-36 months) byethnic group, and ambient air lead concentration versus quarterly sampling period, 1970- 1976.

35 -BLACK
HISPANIC
E GASOLINE LEAD

30

W ~~~~~~A,

< 

### /5

O


### ~ 6.0>

0



### cog an sas bevdfr l h te g n ethnic\groups. This similarity still5.0 pr

~~~ 'V ~~~~~~~m

015A
0 V \

- .~~~~~~~~~~~~~~~ ~ 4.0 /

10 3.0_

1970 1971 1972 1973 1974 1975 1976

QUARTERLY SAMPLING DATE

FIGURE 2. Geometric mean blood lead levels of New York City children (aged 25-36 months) by ethnic group, and estimated amount of lead present in gasoline sold in New York, New Jersey, and Connecticut versus quarterly sampling period, 1970-1976.

blood lead levels and the 

### gasoline lead is 

### quite strik

### ing, and is also observed for all the other age and ethnic groups. This 

### similarity still 

### persists whether thetotal 

### gasoline leadforNewYork, NewYork

### plus NewJersey, orNewYorkplus Connecticut is used. Moreover, the sharp peak in GM blood lead level observed for all age and ethnic groups during the
summer of 1973 is paralleled by a similarpeak in the level ofgasoline lead at that time. 

### Significantly, the graph of air lead levels in Figure 1 does not reflect 

### this 

### sharp peak. Regression analysis has been performed on the 

### data

### using two similarmodels to 

### explore the correlation GM blood lead levels 

### with age, race, season, 

### ambient air lead and 

### gasoline lead. The 

### first model 

### chosen 

### for'study was the 

### simplified additive model used 

### earlier (4):

Y= 

### ato + aj



### tXj + e j= (1) where Y is the quarterly 

### geometric mean for the 

### subpopulation defined by the age 

### dummy variables x1,

. . ., X6, and 

### ethnic group 

### dummyvariables X7, X8. The 

### final 

### variable, Xs represents the 

### environmental lead variable and 

### analysis was 

### performed using 

### either, quarterly ambient air lead levels 

### (in 

### ,ug/m3), or 

### quarterly 

### gasoline lead 

### consumption (in billions ofgrams). The terme represents the 

### statistical 

### disturbance. The second model selected was

9 12 Y= ao + E 

### ajXj + X 

### ajXjZ + e

j= I j= 10 (2) where Xi,.


### .., X6 are the age dummy

### variables, X7,



### ..., Xs season dummy 

### variables, 

### X1o,

. . ., X12 the
race dummy variables. The 

### variable Z represents 

### either ambient air level or 

### gasoline lead consump

### tion. Results from several analyses 

### using these two models are

### giveninTable 1. Models

### A, C, andE used
an

### equation similarto Eq. 

### (1), while B, D, 

### and F

### used

an 

### equation similar to Eq. (2). There 

### is no a

### priori reason 

### for 

### selecting one ofthe models over the other. Model F appears to 

### provide the 

### highest statistical 

### correlation of the 

### observed data. 

### Estimated values for the parameters of 

### Model F are shown inTable 2. 

### This model 

### explains some 

### 75% ofthe total 

### variation in GMblood lead level as a 

### function ofage, race, season, and

### gasoline lead, with

a

### residual standard 

### deviation of 1.74 

### ,ug/100 ml. It is

seen that GM blood lead level 

### first increases mono

### tonically and thendecreases 

### monotonically with age group, 

### reaching a

### peak for 25-36 

### month-old 

### children. Also, the 

### estimated slope 

### (with respect to 

### gasoline lead) for blacks 

### is significantly greater than that 

### for 

### Hispanics, which

### is 

### significantlygreaterthanthatfor 

### whites. This table also 

### provides ameans 

### of

### estimating the GM blood lead level for various subpopula

### tions.

Environmental Health Perspectives 214Table 1. Linear models relating GM blood lead level to age, race, season, air lead, and gasoUne lead.

Explanatory variables

Model Affecting intercept Affecting slope Environmental R2

A Age, race Air lead 0.599 B Age Race Air lead 0.610 C Age, race Gas lead 0.706 D Age Race Gas lead 0.718 E Age, race Air lead, gas lead 0.708 F Age, season Race Gas lead 0.745

Table 2. Regression of GM blood lead level on age, season, race, and gasoline lead, 1970-1976.

Coefficient Standard Significance Variable value deviationa t ratio level

Intercept Constant 7.01 0.519 13.5 <0.0001 Age dummies 13-24 months 2.37 0.274 8.6 <0.0001 25-36 months 3.11 0.274 11.4 <0.0001 37-48 months 2.73 0.274 10.0 <0.0001 49-60 months 2.32 0.274 8.5 <0.0001 61-72 months 1.73 0.274 6.3 <0.0001

> 72 months 1.06 0.274 3.9 <0.0001 Season Quarter 2 -1.37 0.226 -6.1 <0.0001 Quarter 3 -0.101 0.244 -0.41 0.68 Quarter 4 -0.175 0.221 -0.79 0.43 Slope (with respect to gasoline lead) White 2.66 0.117 22.7 <0.0001 Black 3.48 0.117 29.7 <0.0001 Hispanic 2.84 0.117 24.3 <0.0001

aResidual Standard Deviation = 1.74; R2 = 0.745.



## Discussion
By far the greatest source ofleadreleased into the environment is from the combustion of leadcontaining gasoline additives. In 1968 over 90%o of the estimated lead emissions in the United States

were from this source (9). While the amount of lead from mobile sources has been decreasing (as illustrated in Fig. 2), automotive lead still represents the single most important dynamic source of lead into the environment. Research, monitoring and control oflead in the environment, with regard to effects on human lead levels, have for the most part concentrated on individual pathways of exposure, e.g. combustion-inhalation or combustion-+air-+soil deposition--ingestion (1, 9), rather than on demonstrating relationships between environmental

sources and biological response. Exceptions to this approachhave beenthose studieswhichrelateblood lead levels andproximity to roadways or traffic volume ( ).
February 1980 

### The 

### distribution of products 

### emitted from auto

### mobile usage 

### of tetraethyllead has been 

### estimated (10). 

### Approximately 24% 

### is 

### retained in the car, 

### and the 

### remainder is emitted to 

### the atmosphere 

### where 

### it isdepositedorremovedbythewind. Ofthetotallead 

### originally consumed, 50% is 

### deposited while 26% 

### remains in the 

### ambient air. 

### The 

### quantitative distribution of lead 

### traveling the 

### different pathways 

### is not yet 

### known. At 

### best, the 

### evidence indicates that a

### positive relationship exists betweenbloodand

### airlead

### levels, althoughtheexact 

### functional 

### relationshiphas notyet

### been

### clarifiedand that 

### blood lead levels also 

### begin to 

### increase at 

### soil lead levels from 500 to 

### 1,000 ppm. 

### Currently, it 

### is 

### estimated that 

### blood lead 

### levels increase by 1 to 2 

### ,ug/100 ml 

### for every 

### 1 

### ,ug/m3 increase in air lead 

### concentration. Also the mean percent 

### increases in 

### blood lead 

### levels, 

### given a 

### twofold 

### increase in soil 

### lead 

### levels, ranging from 3 to 6 (1). 

### The data 

### presented here 

### demonstrate that 

### blood lead levels in 

### children are very significantly corre

### 215

### latedwithameasure

### of

### gasoline lead

### consumption. It
can

### be further 

### argued that the 

### independent variable, 

### gasoline lead 

### consumption in New 

### York State (or NewYork, NewJersey, and

### Connecticut), provides

a

### useful surrogate 

### for average exposure 

### ofthe popu

### lation studied in New York 

### City. Indeed, the true 

### relation between this surrogate 

### variable and the ac

### tual amount of lead in 

### gasoline consumed in New 

### York

### Cityisnot

### presentlyknown, but, forthe

### period covered 

### it is not unreasonable to suppose that it 

### is 

### highly correlated. 

### Our regression models 

### have 

### indicated that am

### bient air lead levels 

### contribute very 

### little to 

### explainingvariations inblood lead levels, after the 

### effect of 

### gasoline lead has been taken 

### into account. 

### This ob

### servation canbe 

### interpreted either in

### physical terms 

### and/or as a 

### result of the 

### regression analysis itself. Several 

### uncertainties about lead measurement 

### exist. Lead 

### inambient airaccounts for

### onlya

### thirdof the 

### lead 

### products not 

### retained in the 

### vehicle after 

### combustion; furthermore there are problems 

### with measurement of the 

### ambient air lead. 

### Some of the 

### uncertainty in the latter 

### arises from the most common method of 

### air 

### sampling, the 

### high-volume sam

### pler, which collects 

### particulates only in the 0.1-10 

### ,4m range 

### and does not 

### sample vapor 

### phase lead. It 

### has been observed that 40-60% of the mass of col

### lected

### particulate lead

### is below 0.4 ,um, whereas less 

### than 

### 20% is below this diameter at 

### the exhaust 

### pipe (10). 

### This raises uncertainties as toboth the fraction 

### of lead lost due to 

### deposition between the 

### sampling 

### site and the 

### emitter, as well as, the 

### fraction which passes 

### through the 

### filter. The 

### organic phase, 

### while small, is nonetheless 

### significant and may range as 

### high as 

### 13% of the total lead 

### in urban 

### air (11). Fur

### thermore, some of

### the lead measured maybe due to 

### re-entrainment (12), 

### possibly including non

### automotive 

### generated lead, and may not 

### be 

### directly correlated with 

### gasoline lead. The values we 

### used for air-lead measurement are 

### from a 

### single source at a 

### height of 56 m above the street 

### (4). Thus the values used may not 

### be rep

### resentative ofexposure 

### either at street 

### level, at 

### that 

### location, oratother

### locations inthe

### cityorevenas an average 

### for the 

### city as a whole. 

### Our 

### regression analysis between 

### automotive 

### gasoline lead

### consumption and 

### ambientairleaddoes not show a 

### high correlation, nor 

### have other 

### studies (13). Moreover, what 

### is more 

### relevant in 

### assessing the 

### relative contributions of air lead and 

### gasoline lead in the 

### models of 

### Table 1 

### is not the 

### ordinary 

### correlation between these two 

### variables, but 

### rather 

### their 

### partial correlation coefficients. The 

### observation that there 

### is little improvement in 

### explanatory power 

### (R2) between the 

### regression of blood lead ongas lead 

### (Model C), and blood lead on 

### bothgas lead, 

### and air lead (Model E) simply 

### reflects the 

### fact that the 

### partial correlation coefficient rBA.G between blood lead and air lead, correcting for the effect ofgas lead, is rather small. On the other

### hand, by comparing models A and E of Table 1, one can 

### show that 

### there is a highly 

### significant increase in 

### explanatorypowerbetween the regressions ofblood 

### lead on 

### air lead, andblood lead on air lead, gas 

### lead; 

### this just confirms that the 

### partial correlation 

### coeffi

### cientrBG.Abetween

### blood lead and gas lead, correctingforthe effectofairlead, 

### is 

### statistically significant 

### (14). While there are many plausible 

### explanations for 

### the 

### relatively small role 

### played by air lead in ex

### plaining observed 

### blood lead level, 

### this finding is consistentwiththehypothesis that inhalationoflead 

### from ambient air is only a small 

### contribution to the blood lead level (3). During the period of 1974-1976,
mean blood 

### lead levels were 

### approximately 20-25 

### ,ug/100ml 

### and

### ambientairleadlevelsnever

### exceeded 1.3 

### ,ug/m3. Even 

### ifwe double 

### air lead 

### concentration tocompensate 

### for

### heightofthe 

### sampling station, 

### this could account for only 

### for 2.6-5.2 ,ug/100 ml blood lead, on the average, 

### leaving 15-20 

### ug/100 ml 

### of blood 

### lead to be 

### explained by other sources, 

### which could very 

### well come from 

### gasoline through other 

### pathways. In 

### reality, the exposure 

### mechanisms are 

### probablyconsiderablymore 

### complex (1, 2). 

### The lack 

### ofdataon

### the roleof

### secondary sources, suchas

### dust and 

### dirt can 

### only lead to 

### speculation. Further re

### search into these 

### pathways is needed. The present 

### analysis does not

### provide insight into the 

### mechanisms or routes 

### of children's exposure, other than 

### suggesting that the 

### total flux of 

### lead into the 

### environment may be more 

### important than 

### the 

### concentration in any 

### single 

### primary or 

### secondary 

### medium of exposure or transport. Whatever 

### the 

### specific 

### explanation turns out to be, however, 

### it is not

### neededfor

### policy

### analysis and

### decisions forcon

### trol and standards for lead 

### emissions. The present 

### analysis suggests that 

### emissions control rather than 

### ambient standards are more 

### appropriate, at least 

### for the case 

### of 

### controlling blood lead levels 

### in 

### specific 

### populations, such as 

### urban children. 

### Strong arguments can 

### be made for 

### using statistical analysis for such 

### policy decisions rather than 

### waiting for more 

### detailed 

### experimental data on 

### pathways (15).

The authors acknowledge the assistance of G. Provenzano, who kindly provided us with the data on gasoline sales by grade andstate. The contents ofthis paperdo notnecessarilyreflect the official views andpolicies, expressed or implied, ofthe organizations involved.

REFERENCES 1. U.S. EPA. Air Quality Criteria for Lead, EPA-600/8-77-017, U.S. Environmental Protection Agency, Washington, D.C., December 1977.
216 Environmental Health Perspectives2. Behar, J. V., Schuck, E. A., Stanley, R. E., and Morgan, G. B. Integrated exposure monitoring. Environ. Sci. Technol. 13; 34 (1979). 3. Chamberlain, A. C., Heard, M. J., Little, P., Newton, D., Wells, A. C. and Wiffen, R. D. Investigations into lead from motor vehicles. AERE-R 9198, United Kingdom Atomic Energy Authority, Harwell, England, November 1979. 4. Billick, I. H., Curran, A. S., and Shier, D. R. Analysis of pediatric blood lead levels in New York City for 1970-1976. Environ. Health Perspect. 31: 183 (1979). 5. Kendall, M. G., and Stuart, A. The Advanced Theory of Statistics, Vol. 1, Charles Griffin, London, 1%3, p. 168. 6. Environmental Quarterly, HASL-321, U.S. Department of Energy, Health and Safety Laboratory, New York, New York, July 1977. 7. Wheeler, G. L., Provenzano, G., and Resek, R., Environmental Contamination by Lead and Other Heavy Metals. Volume V. Synthesis and Modeling.Final Report NSF RANN grants GI-31605 and ERT 74-24276, University of Illinois at Urbana-Champaign, July 1977. 8. Shelton, E. M., etal. MotorGasolines. U.S. EnergyResearch and Development Administration, Bartlesville Energy Research Center, Bartlesville, Oklahoma, various years. 9. Jenkins, D. W., Ed. Design of Pollutant-Oriented integrated Monitoring Systems. A Test Case: Environmental Lead. EPA-600/4-76-018, U.S. Environmental Protection Agency, Las Vegas, Nevada, April 1976. 10. Huntzicker, J. J., Friedlander, S. K., and Davidson, C. I. Material balance forautomobile-emitted lead in Los Angeles Basin. Environ. Sci. Technol. 9: 448 (1975). 11. Grandjean, P., and Nielsen, T. Organolead compounds: environmental health aspects. Residue Revs. 72: 98 (1979). 12. Maxwell, C. M., andNelson, D. W. ALeadEmission Factor forReentrained Dust from a Paved Roadway. EPA-450/3-78- 021, U.S. Environmental Protection Agency, Research Triangle Park, N.C., April 1978. 13. Edwards, H. W., andWheat, H. G. Seasonal trends inDenver atmospheric lead concentrations. Environ. Sci. Technol. 12: 687 (1978). 14. Johnston, J. Econometric Methods, 2nd ed. McGraw-Hill, New York, 1972, pp. 61-64. 15. Lave, L. B., and Seskin, E. P. Epidemiology, causality and public policy. Am. Scientist 67; 178 (1979).

February 1980 217