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 of a large data set of pediatric blood lead levels collected in New York City (1970-1976) shows a

highly significant association between geometric mean blood lead levels and the amount of lead present in

gasline sold during the same period. This association was observed for all age and ethnic groups studied,

and it suggests that possible exposure pathways other than ambient air should be considered. Even without

detailed knowledge ofthe exact exposure pathways, suffcient information now exists for policy analysis and

dedsions relevant to controls and standards related to lead in gasoline and its effect on subsets of the

population.

Blood lead levels provide a measure of human lead

exposure resulting from all environmental sources.

The quantification of relations between environmental exposure and blood lead levels, especially in

children, is of considerable importance for assessing

the relative contributions of various sources of environmental 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 screening 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 significant relationship between geometric mean (GM)

blood lead levels and ambient air lead measurements

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 study relatively homogeneous subpopulations defined according to ethnic group, age,

and quarterly sampling date. The blood lead levels

*Environmental Research Group, Department of Housing 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 characterized by their geometric mean (GM). A typical plot

of GM blood lead level against quarterly sampling

date is shown for black and Hispanic children, aged

25-36 months, in Figure 1. The GM blood 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,

measured at a single monitoring station in Manhattan

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 industry data 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 been used 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 lead present in gasoline sold in New 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 pattern and overall decline between the GM

213
35 - BLACK

HISPANIC

E 1

AIR LEAD--

4m 30-

4 252.5

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

1970 1971 1972 1973 1974 1975 1976

children >

35 - BAC

10 _ \.0 1

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) by ethnic 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 ~~~'Vsimilarity ~~~~~~~m still5.0 pr

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 striking, and is also observed for all the other age and

ethnic groups. This similarity still persists whether

the total gasoline lead for New York, New York plus

New Jersey, or New York plus 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 similar peak in the

level of gasoline 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 similar models 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 + tXj aj + e

j= (1)

where Y is the quarterly geometric mean for the

subpopulation defined by the age dummy variables

x1, . . ., X6, and ethnic group dummy variables 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 of grams). The term e 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 consumption.

Results from several analyses using these two

models are given in Table 1. Models A, C, and E used

anequation similar to Eq. (1), while B, D, and F used

an equation similar to Eq. (2).

There is no a priori reason for selecting one of the

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 in Table 2. This model explains some

75% of the total variation in GM blood lead level as a

function of age, 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 monotonically and then decreases 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 significantly greater than that for

whites. This table also provides a means of estimating the GM blood lead level for various subpopulations.

214 Environmental Health Perspectives
Table 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 of lead released 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

of lead 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

approach have been those studies which relate blood

lead levels and proximity to roadways or traffic volume ( ).

February 1980

The distribution of products emitted from automobile usage of tetraethyllead has been estimated

(10). Approximately 24% is retained in the car, and

the remainder is emitted to the atmosphere where it

is deposited or removed by the wind. Ofthe total lead

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

between blood and air lead levels, although the exact

functional relationship has not yet been clarified and

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 corre215
lated with a measure ofgasoline lead consumption. It

can be further argued that the independent variable,

gasoline lead consumption in New York State (or

New York, New Jersey, and Connecticut), provides

a useful surrogate for average exposure of the population studied in New York City. Indeed, the true

relation between this surrogate variable and the actual amount of lead in gasoline consumed in New

York City is not presently known, but, for the period

covered it is not unreasonable to suppose that it is

highly correlated.

Our regression models have indicated that ambient air lead levels contribute very little to explaining variations in blood lead levels, after the effect of

gasoline lead has been taken into account. This observation can be interpreted either in physical terms

and/or as a result of the regression analysis itself.

Several uncertainties about lead measurement

exist. Lead in ambient air accounts for only a third of

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 sampler, 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 collected particulate lead is below 0.4 ,um, whereas less

than 20% is below this diameter at the exhaust pipe

(10). This raises uncertainties as to both 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). Furthermore, some of the lead measured may be due to

re-entrainment (12), possibly including nonautomotive 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 representative of exposure either at street level, at that

location, or at other locations in the city or even as an

average for the city as a whole.

Our regression analysis between automotive

gasoline lead consumption and ambient air lead does

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

both gas 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 of gas 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

explanatory power between the regressions of blood

lead on air lead, and blood lead on air lead, gas lead;

this just confirms that the partial correlation coefficient rBG.A between blood lead and gas lead, correcting for the effect of air lead, is statistically significant

(14).

While there are many plausible explanations for

the relatively small role played by air lead in explaining observed blood lead level, this finding is

consistent with the hypothesis that inhalation of lead

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/100 ml and ambient air lead levels never exceeded

1.3 ,ug/m3. Even if we double air lead concentration

to compensate for height of the 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

probably considerably more complex (1, 2). The lack

ofdata on the role of secondary sources, such as dust

and dirt can only lead to speculation. Further research 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 needed for policy analysis and decisions for control 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

and state. The contents of this paper do not necessarily reflect the

official views and policies, expressed or implied, of the organizations involved.

REFERENCES

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U.S. Environmental Protection Agency, Washington, D.C.,

December 1977.

216 Environmental Health Perspectives
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February 1980 217