894 VOLUME 113 | NUMBER 7 | July 2005 • Environmental Health Perspectives

Research | Children’s Health

The preponderance of experimental and

human data indicates that there are persistent

and deleterious effects of blood lead levels

> 10 μg/dL on brain function, including lowered intelligence, behavioral problems, and

diminished school performance (Baghurst

et al. 1992; Bellinger et al. 1992; Cory-Slechta

1997; Dietrich et al. 1993; Ernhart et al. 1989;

National Research Council 1993; Needleman

and Gatsonis 1990; Pocock et al. 1994; Rice

1993; Wasserman et al. 1997; Yule et al.

1981). Lead toxicity, defined as whole blood

lead ≥ 10 μg/dL, was based on numerous

cross-sectional and prospective studies

[Bellinger et al. 1987; Centers for Disease

Control and Prevention (CDC) 1991; World

Health Organization (WHO) 1995]. These

studies generally, but not always, found

adverse consequences of childhood lead exposure (CDC 1991; WHO 1995). Still, most of

the children in those studies had blood lead

levels > 10 μg/dL. The WHO and the CDC

recognized that there was no discernable

threshold for the adverse effects of lead exposure, but too few studies had examined children with blood lead levels < 10 μg/dL to

support any firm conclusions (CDC 1991;

WHO 1995).

There is emerging evidence that leadassociated intellectual deficits occur at blood

lead levels < 10 μg/dL. In the Rochester

Longitudinal Study, there was an estimated

reduction of 7.4 IQ points associated with an

increase in lifetime mean blood lead from

1 to 10 μg/dL (Canfield et al. 2003). In a

reanalysis of a Boston, Massachusetts, cohort,

a similar finding was observed among children whose maximal blood lead level was

< 10 μg/dL (Bellinger and Needleman 2003).

Questions about an effect of lead at blood

lead levels < 10 μg/dL persist, however,

because of the relatively small numbers of

children with maximal blood lead levels

< 10 μg/dL in the Rochester Longitudinal

Study (Rogan and Ware 2003). Other studies

were limited because they involved children

whose blood lead levels may have exceeded

10 μg/dL at some point in their lifetime or

because important covariates, such as maternal

IQ scores, were not always available (Fulton

et al. 1987; Lanphear et al. 2000; Schwartz

1994; Schwartz and Otto 1991; Walkowiak

et al. 1998). Because of the policy implications of this research, it is critical to estimate

with greater precision the exposure–response

relationship at blood lead levels < 10 μg/dL.

The primary objective of this pooled analysis was to estimate the quantitative relationship

between children’s performance on IQ tests

and selected measures of blood lead concentration among children followed prospectively,

from infancy through 5–10 years of age in

seven prospective cohort studies. We also

sought to test whether the lead-associated IQ

deficit was greater for a given change in exposure among children who had maximal blood

lead levels < 10 μg/dL compared with children

who had higher blood lead concentrations.

Materials and Methods

We contacted investigators for all eight

prospective lead cohorts that were initiated

before 1995, and we were able to retrieve data

sets and collaboration from seven. The participating sites were Boston (Bellinger et al.

1992); Cincinnati (Dietrich et al. 1993) and

Cleveland, Ohio (Ernhart et al. 1989);

Mexico City, Mexico (Schnaas et al. 2000);

Address correspondence to B.P. Lanphear, Cincinnati

Children’s Hospital Medical Center, 3333 Burnet

Ave., Mail Location 7035, Cincinnati, OH 45229-

3039 USA. Telephone: (513) 636-3778. Fax: (513)

636-4402. E-mail: bruce.lanphear@cchmc.org

This study was funded, in part, by the National

Institute of Environmental Health Sciences, the

Centers for Disease Control and Prevention, and the

U.S. Environmental Protection Agency.

The authors declare they have no competing

financial interests.

Received 22 October 2004; accepted 17 March

2005.

Low-Level Environmental Lead Exposure and Children’s Intellectual Function:

An International Pooled Analysis

Bruce P. Lanphear,1,2 Richard Hornung,1,2,3 Jane Khoury,1,2 Kimberly Yolton,1 Peter Baghurst,4 David C. Bellinger,5

Richard L. Canfield,6 Kim N. Dietrich,1,2 Robert Bornschein,2 Tom Greene,7 Stephen J. Rothenberg,8,9

Herbert L. Needleman,10 Lourdes Schnaas,11 Gail Wasserman,12 Joseph Graziano,13 and Russell Roberts14

1Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, USA; 2Department of Environmental Health, University of Cincinnati

College of Medicine, Cincinnati, Ohio, USA; 3Institute for Health Policy and Health Services Research, Department of Environmental

Health, University of Cincinnati, Cincinnati, Ohio, USA; 4Women and Children’s Hospital, North Adelaide, South Australia; 5Department 

of Neurology, Children’s Hospital Boston and Harvard Medical School, Boston, Massachusetts, USA; 6Division of Nutritional Sciences,

Cornell University, Ithaca, New York, USA; 7Department of Biostatistics and Epidemiology, Cleveland Clinic Foundation, Cleveland, Ohio,

USA; 8Center for Research in Population Health, National Institute of Public Health, Cuernavaca, Morelos, Mexico; 9Drew University, Los

Angeles, California, USA; 10University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA; 11National Institute of

Perinatology, Mexico City, Mexico; 12Department of Child Psychiatry, Columbia University, New York, New York, USA; 13Department of

Environmental Health Sciences, Columbia University, New York, New York, USA; 14School of Applied Psychology, Griffith University,

Queensland, Australia

Lead is a confirmed neurotoxin, but questions remain about lead-associated intellectual deficits at

blood lead levels < 10 μg/dL and whether lower exposures are, for a given change in exposure, associated with greater deficits. The objective of this study was to examine the association of intelligence test scores and blood lead concentration, especially for children who had maximal measured

blood lead levels < 10 μg/dL. We examined data collected from 1,333 children who participated in

seven international population-based longitudinal cohort studies, followed from birth or infancy

until 5–10 years of age. The full-scale IQ score was the primary outcome measure. The geometric

mean blood lead concentration of the children peaked at 17.8 μg/dL and declined to 9.4 μg/dL by

5–7 years of age; 244 (18%) children had a maximal blood lead concentration < 10 μg/dL, and

103 (8%) had a maximal blood lead concentration < 7.5 μg/dL. After adjustment for covariates,

we found an inverse relationship between blood lead concentration and IQ score. Using a loglinear model, we found a 6.9 IQ point decrement [95% confidence interval (CI), 4.2–9.4] associated with an increase in concurrent blood lead levels from 2.4 to 30 μg/dL. The estimated IQ

point decrements associated with an increase in blood lead from 2.4 to 10 μg/dL, 10 to 20 μg/dL,

and 20 to 30 μg/dL were 3.9 (95% CI, 2.4–5.3), 1.9 (95% CI, 1.2–2.6), and 1.1 (95% CI,

0.7–1.5), respectively. For a given increase in blood lead, the lead-associated intellectual decrement for children with a maximal blood lead level < 7.5 μg/dL was significantly greater than that

observed for those with a maximal blood lead level ≥ 7.5 μg/dL (p = 0.015). We conclude that

environmental lead exposure in children who have maximal blood lead levels < 7.5 μg/dL is associated with intellectual deficits. Key words: blood lead concentration, children, environment,

epidemiology, intelligence, lead, lead toxicity. Environ Health Perspect 113:894–899 (2005).

doi:10.1289/ehp.7688 available via http://dx.doi.org/ [Online 18 March 2005]
Port Pirie, Australia (Baghurst et al. 1992);

Rochester, New York (Canfield et al. 2003);

and Yugoslavia (Wasserman et al. 1997). The

Sydney, Australia, study was not included

because we were unable to contact the investigators (Cooney et al. 1989). The data for the

Rochester Longitudinal Study and for Mexico

City, collected when the children were about

6 years of age, have not been published elsewhere. The eligibility criteria and methods for

each of the cohorts are described elsewhere

(Baghurst et al. 1992; Bellinger et al. 1992;

Canfield et al. 2003; Dietrich et al. 1993;

Ernhart et al. 1989; Schnaas et al. 2000;

Wasserman et al. 1997). All studies were

approved by their respective institutional

review boards.

Outcome measures. The primary outcome

measure was the full-scale IQ, which is a composite score of verbal and performance tests.

The children were administered a version of the

Wechsler Intelligence Scales for Children

[Wechsler Intelligence Scale for Children–

Revised (WISC-R; Wechsler 1974), Wechsler

Intelligence Scale for Children–III (WISC-III;

Wechsler 1991), Wechsler Preschool and

Primary Scales of Intelligence (WPPSI; 1967),

and Wechsler Intelligence Scale for Children–

Spanish Version (WISC-S; Wechsler 1981)]

under uniform conditions within each study.

The IQ test was administered when the children

were between 4 years 10 months and 7 years of

age for all but one cohort. In the Boston cohort,

we used blood lead tests taken at 5 years of age

and the nearest available full-scale IQ score,

which was done at 10 years of age.

Venous or fingerstick capillary blood samples were obtained using standard protocols.

Cord blood lead was collected in a subsample

of the subjects. During each child’s examination, demographic and health information

were obtained from the parent (usually the

biologic mother). IQ tests were administered

to the mother. We also obtained data on other

factors that might confound the relation of

lead exposure and IQ, including child’s sex,

birth order, birth weight, maternal education,

maternal age, marital status, prenatal alcohol

exposure, prenatal tobacco exposure, and the

Home Observation for Measurement of the

Environment (HOME) Inventory score. The

HOME Inventory is an index that reflects the

quality and quantity of emotional and cognitive stimulation in the home environment

(Caldwell and Bradley 1984).

Measures of exposure. We examined four

measures of blood lead: concurrent blood lead

(defined as the blood lead measured closest

to the IQ test), maximum blood lead level

(defined as the peak blood lead measured at

any time before IQ test), average lifetime blood

lead (defined as the mean blood lead from

6 months to concurrent blood lead tests), and

early childhood blood lead (defined as the

mean blood lead from 6 to 24 months). The

blood sampling intervals varied across studies.

To enhance comparability across studies, we

used the following blood sampling intervals

(based on children’s age): 6, 12 (or 15), 36, 48,

and 60 months. We used mean blood lead

rather than area under the curve (AUC) to

maintain the same units of analysis for all four

lead indices. The AUC and mean provided

essentially the same information about children’s lead exposure (r = 0.97).

Statistical methods. To estimate the quantitative relationship between children’s performance on IQ tests and selected measures of

blood lead concentration, we examined the

potential confounding effects of other factors

associated with IQ scores using multiple

regression analysis. Ten factors were available

from individual sites: HOME Inventory,

child’s sex, birth weight, birth order, maternal

education, maternal IQ, maternal age, marital

status, prenatal smoking status, and prenatal

alcohol use.

The development of the regression model

involved a multistep process beginning with a

simple unadjusted model relating each blood

lead measure to IQ while controlling for site.

The first step was to test whether the linear

model of the relationship between blood lead

and IQ, applied in most of the individual

cohort analyses, provided a good fit over the

wider range of blood lead levels represented in

the pooled data. First, a linear model adjusted

for the seven sites was estimated, and then

quadratic and cubic terms for blood lead were

added to test for linearity. A restricted cubic

spline function was fit to the data to produce

a curve that followed the data in the absence

of any assumptions about the functional form

of the relationship.

After an initial model was chosen, we

examined each of the 10 available confounders

individually and in combination with the

other covariates to assess potential confounding of the IQ–blood lead relationship. Careful

attention was paid to the stability of the parameter estimates as each additional term was

added. This process was halted when either no

more significant terms (p < 0.10) entered the

model or the inclusion of additional terms

caused no substantial change (i.e., > 10%) in

the blood lead coefficient.

In all models, we tested the interaction

of blood lead and site to determine whether

a summary measure of the IQ–blood lead

relationship could be used for all cohorts.

After an initial model was selected, the tests

of linearity and the restricted cubic spline

models were recomputed to ensure that our

initial model was still appropriate after adjustment for covariates (Harrell 2001). We also

produced separate linear models for each of

the seven cohorts adjusted for the covariates

selected in the combined model.

After the multiple regression models

were developed, regression diagnostics were

employed to ascertain whether the lead coefficient was affected by collinearity or influential

observations (Belsley et al. 1980). After regression diagnostics were examined and homogeneity of the blood lead coefficients across

sites was evaluated, the fit of all four measures

of blood lead was compared using the magnitude of the model R2. The blood lead measure

with the largest R2 (adjusted for the same

covariates) was selected a priori as the preferred

blood lead index relating blood lead to IQ.

Several approaches were investigated to

evaluate the stability of the final model.

Although the seven cohorts were not randomly

sampled from a larger population of studies, an

assumption could be made that they were representative of a larger population of children.

Accordingly, we evaluated the results of applying a random-effects model (with sites random) rather than a fixed-effects model (Littell

et al. 1996). We also examined the effect of

any one site on the overall model by calculating the blood lead coefficient in seven identical

models, each omitting one of the seven cohorts

(Efron and Tibshirani 1993).

After the final model was selected using the

full-scale IQ as the outcome variable, we fit

similar models for verbal and performance

IQ scores. We also examined interactions of

covariates with blood lead concentration (effect

modification) and tested the effect of including

race as a confounder in the U.S. cohort studies.

Finally, we examined the relationship of prenatal lead exposure (cord blood) and IQ score in

the subsample for which cord blood lead tests

were available.

Results

Of the 1,581 eligible children from the seven

cohorts, data on all 10 covariates were available

for 1,308 (83%) children; 1,333 (84%) children had data on the four major covariates that

were selected for the final model (Table 1).

Blood lead levels were highest in Yugoslavia

and lowest in Rochester and Boston for all lead

exposure indices (Table 2). The median peak

or maximal blood lead concentration was

18 μg/dL; the mean age when children’s blood

lead levels peaked was 2.5 years. By 5–7 years

of age, the median blood level had declined to

9.7 μg/dL (concurrent blood lead concentration). The lifetime average blood lead concentration was 12.4 μg/dL; 244 (18%) children

had a maximal blood lead concentration

< 10 μg/dL, and 103 (8%) had a maximal

blood lead concentration < 7.5 μg/dL.

The mean IQ of all children was approximately 93. Child IQ was highest in the Boston

cohort and lowest in the Yugoslavia cohort

(Table 2). In univariate regression analyses, children’s IQ was significantly related to site, maternal IQ, the HOME score, maternal education,

Childhood lead exposure and intellectual function

Environmental Health Perspectives • VOLUME 113 | NUMBER 7 | July 2005 895
marital status, birth weight, maternal age, birth

order, race (for U.S. cohorts only), and prenatal tobacco exposure. In contrast, child’s sex

and prenatal alcohol consumption were not

significantly associated with a deficit in IQ

score (Table 3).

We examined the relationship of the four

blood lead indices with IQ (Table 4). Although

all four blood lead measures were highly correlated (r range = 0.74–0.96), the concurrent

blood lead variable exhibited the strongest

relationship with IQ, as measured by R2.

Although the means differed for the different

blood lead indices, the results of the regression analyses were very similar. In all subsequent analyses and figures, the concurrent

blood lead measure was used as the primary

lead exposure index.

The shape of the exposure–response relationship was determined to be nonlinear insofar

as the quadratic and cubic terms for concurrent

blood lead were statistically significant (p <

0.001 and p = and 0.003, respectively). Because

the restrictive cubic spline indicated that a loglinear model provided a good fit to the data, we

used the log of concurrent blood lead in all subsequent analyses of the pooled data (Figure 1).

The multivariable analysis resulted in a sixterm model: log of concurrent blood lead, site,

maternal IQ, HOME Inventory, birth weight,

and maternal education, which we consider

our preferred model (Table 4). Linear models

of concurrent blood lead and IQ are shown for

each of the seven cohorts, adjusted for the

same covariates (Figure 2). The additional six

terms we considered (child’s sex, birth order,

maternal age, marital status, prenatal smoking

status, and prenatal alcohol use) contributed

very little to the overall fit of the model, and

their inclusion in the model resulted in virtually no change to the coefficient for blood lead

(i.e., < 5%). None of the six terms was statistically significant (data not shown).

The shape of the log-linear model and the

spline function indicated that the steepest

declines in IQ were at blood lead levels

< 10 μg/dL (Figures 3 and 4). The log-linear

model estimated a decrement of 6.9 IQ points

[95% confidence interval (CI), 4.2–9.4] for an

increase in concurrent blood lead levels from

2.4 to 30 μg/dL, representing the 5th to the

95th percentile for blood lead values in the data

set (Table 4). But the lead-associated decrement

was greatest in the lower ranges of blood lead.

The estimated IQ decrements associated with

an increase in blood lead from 2.4 to 10 μg/dL,

10 to 20 μg/dL, and 20 to 30 μg/dL were 3.9

(95% CI, 2.4–5.3), 1.9 (95% CI, 1.2–2.6), and

1.1 (95% CI, 0.7–1.5), respectively (Table 4).

To investigate further whether the leadassociated decrement was greater at lower blood

lead concentrations, we divided the data at two

cut-points a priori (i.e., maximal blood lead

above and below 10 μg/dL, and maximal blood

lead above and below 7.5 μg/dL) (Figure 4).

We then fit separate linear models to the data

in each of these ranges and compared the blood

lead coefficients for the concurrent blood lead

index. The coefficient for the 103 children

with maximal blood lead levels < 7.5 μg/dL

was significantly greater than the coefficient for

the 1,230 children with a maximal blood lead

Lanphear et al.

896 VOLUME 113 | NUMBER 7 | July 2005 • Environmental Health Perspectives

Table 2. Characteristics of 1,333 children and their mothers in seven cohort studies of environmental lead exposure and IQ.

Boston Cincinnati Cleveland Mexico Port Pirie Rochester Yugoslavia

Characteristic (n = 116) (n = 221) (n = 160) (n = 99) (n = 324) (n = 182) (n = 231)

Percent femalea 60 (51.7) 108 (48.9) 73 (45.6) 50 (50.5) 174 (53.7) 89 (48.9) 115 (49.8)

Birth weightb (g) 3,412 ± 510 3,144 ± 457 3,199 ± 498 3,254 ± 432 3,393 ± 502 3,226 ± 506 3,328 ± 526

Gestation at deliveryb (weeks) 40.0 ± 1.8 39.6 ± 1.7 39.6 ± 1.2 40.2 ± 1.1 39.9 ± 1.7 39.1 ± 1.8 39.3 ± 2.9

Birth orderb 1.6 ± 1.0 2.6 ± 1.4 2.2 ± 1.1 1.8 ± 0.9 2.0 ± 1.1 2.4 ± 1.4 2.6 ± 1.7

IQ test WISC-R WISC-R WPPSI WISC-S WISC-R WPPSI WISC-III

IQ scoreb 116.0 ± 14.2 87.0 ± 11.4 86.7 ± 16.2 107.8 ± 11.0 106.0 ± 13.7 84.9 ± 14.4 74.2 ± 13.3

Age at IQ testing (years) 10 7 4.8 7 7 6 7

Blood lead concentrationsc

Concurrent blood lead 5.4 7.5 14.2 7.0 13.0 4.0 15.9

(0.8–12.7) (3.5–20.0) (7.0–28.5) (3.0–16.5) (6.0–24.0) (1.5–12.0) (4.7–47.8)

Peak blood lead 12.0 17.9 18.0 15.0 27.0 9.0 23.8

(5.4–27.0) (9.0–38.0) (9.0–34.0) (6.0–40.0) (15.0–46.0) (3.5–23.3) (7.6–61.5)

Early childhood 8.1 12.0 13.4 11.4 20.5 5.8 14.1

(3.3–18.0) (6.6–26.6) (7.9–24.8) (4.3–26.8) (11.0–33.3) (2.4–13.1) (4.3–44.0)

Lifetime mean 7.6 11.7 14.5 10.6 18.6 5.5 15.8

(3.6–15.2) (5.8–24.9) (8.1–25.3) (4.5–21.3) (10.8–30.2) (2.4–12.8) (5.6–49.3)

Peak blood lead < 10 μg/dLa 41 (35.3) 23 (10.4) 11 (6.9) 20 (20.2) 0 (0.0) 103 (56.6) 46 (19.9)

Peak blood lead < 7.5 μg/dLa 13 (11.2) 1 (0.4) 1 (0.6) 8 (8.1) 0 (0.0) 69 (37.9) 11 (4.8)

Maternal characteristics

Age at delivery (years)b 30.5 ± 4.2 22.7 ± 4.3 22.2 ± 3.8 27.1 ± 5.9 26.0 ± 4.2 24.8 ± 6.6 26.6 ± 5.1

Race (nonwhite)a 5 (4.3) 197 (89.1) 69 (43.1) NA NA 130 (71.4) NA

Maternal IQb 124.2 ± 16.2 75.2 ± 9.4 73.4 ± 13.2 93.4 ± 11.9 94.4 ± 11.0 81.1 ± 12.6 87.3 ± 14.8

Education at delivery (grade)b 15.2 ± 2.0 11.2 ± 1.4 10.6 ± 1.6 11.4 ± 3.5 10.6 ± 1.0 12.2 ± 2.0 8.8 ± 3.9

HOME scoreb 50.5 ± 3.5 32.7 ± 6.2 38.1 ± 6.7 36.8 ± 6.7 42.3 ± 4.6 31.9 ± 6.3 30.4 ± 6.8

Marrieda 107 (92.2) 30 (13.6) 82 (51.2) 88 (88.9) 298 (92.0) 60 (33.2) 231 (100)

Tobacco use during pregnancya 29 (25.0) 111 (50.2) 128 (80.0) 6 (6.1) 79 (24.6) 41 (22.6) 59 (25.5)

Alcohol use during pregnancya 61 (52.6) 31 (14.0) 75 (46.9) 6 (6.1) 82 (25.3) 9 (5.5) 14 (6.1)

NA, Not applicable. HOME score was standardized to preschool scale. Concurrent blood lead tests taken at 5 years of age were used as the concurrent blood lead test for the Boston

cohort, and the IQ test was done at 10 years. Test scores of children in the Yugoslavia cohort are low because of adjustments in adapting tests where no standardization existed; rather

than deriving appropriate analogues, some culturally driven items were removed, resulting in lower scores.

aNo. (%). bMean ± SD. cGeometric mean (5th–95th percentiles).

Table 1. Characteristics of the children and of their

mothers in the pooled analysis (n = 1,333).

Characteristic Value

Child characteristics

Femalea 669 (50.2)

Birth weightb (g) 3,286 ± 503

Gestation at deliveryb (weeks) 39.6 ± 1.9

Birth orderc 2.0 (1–5)

Blood lead concentrationc

Concurrent 9.7 (2.5–33.2)

Peak 18.0 (6.2–47.0)

Early childhood 12.7 (4.0–34.5)

Lifetime average 12.4 (4.1–34.8)

Peak blood lead 244 (18.3)

concentration < 10 μg/dLa

Peak blood lead 103 (7.7)

concentration < 7.5 μg/dLa

IQb 93.2 ± 19.2

Age at IQ testingb (years) 6.9 ± 1.2

Maternal characteristics

Age at deliveryb (years) 25.4 ± 5.4

Maternal IQb 88.2 ± 18.5

Education at deliveryb (grade) 11.1 ± 2.8

HOME scoreb 37.0 ± 8.4

Marrieda 896 (67.3)

Smoked during pregnancya 453 (34.1)

Alcohol use during pregnancya 278 (21.2)

HOME score was standardized to preschool test. Early

childhood blood lead concentration was defined as the

mean of 6- to 24-month blood lead tests. Lifetime average

blood lead concentration was defined as the mean of blood

lead tests taken from 6 months through the concurrent

blood lead test.

aNo. (%). bMean ± SD. cMedian (5th–95th percentiles).
≥ 7.5 μg/dL [linear β = –2.94 (95% CI, –5.16

to –0.71) vs. –0.16 (95% CI, –2.4 to –0.08);

p = 0.015]. The coefficient for the 244 children

who had a maximal blood lead < 10 μg/dL was

not significantly greater than the coefficient for

the 1,089 children who had a maximal blood

lead ≥ 10 μg/dL [linear β = –0.80 (95% CI,

–1.74 to –0.14) vs. β = –0.13 (95% CI, –2.3 to

–0.03); p = 0.103].

To assess the model stability, we employed

a random-effects model with sites assumed to

be randomly selected from a larger set of populations. Results were similar to the preferred

fixed-effects model, with the random-effects

model producing a blood lead coefficient that

was 3.7% lower (–2.6 vs. –2.7). As an additional measure of model stability, we fit seven

identical log-linear models with each model

omitting data from one of the sites. The range

of coefficients leaving one site out at a time

was –2.36 (Rochester) to –2.94 (Yugoslavia),

or a percent change ranging from –2.6 to

+8.9%. These analyses provide evidence of

the stability of our final preferred fixed-effects

model and indicate that the results of the

pooled analysis did not depend on the data

from any single study.

We also examined the relation of blood

lead concentration to verbal and performance

IQ scores, adjusting for the same covariates

used in the full-scale IQ model. The coefficient

for the log of blood lead related to performance

IQ was similar to the coefficient for log of

blood lead in the full-scale IQ model (β =

–2.73 vs. –2.70), whereas the coefficient for

log of blood lead related to verbal IQ was

somewhat lower than the coefficient for the log

of blood lead in the full-scale IQ model (β =

–2.07 vs. –2.70). The difference between the

coefficient for verbal and performance IQ was

not statistically significant (p = 0.196).

We did not identify any significant interactions between the covariates and the log of

concurrent blood lead. In the U.S. sites, race

was not significantly associated with IQ after

inclusion of the four covariates in the preferred

model, nor did it alter the estimated relationship of blood lead concentration and IQ. In

unadjusted analyses involving the 696 children

who had cord blood lead levels, the log of cord

blood lead concentration was significantly associated with child’s IQ (β = –1.69, SE = 0.60;

p = 0.005). After adjusting for the log of concurrent blood concentration, the log of cord

blood lead was no longer associated with children’s IQ scores (p = 0.21). In contrast, the log

of concurrent blood lead was significantly associated with children’s IQ scores even with log

cord blood lead concentration in the model

(β = –1.73, SE = 0.74; p = 0.019). Finally, we

identified and removed 65 potentially influential observations from the data and refit the

model. The change in the coefficient for log of

blood lead was 1.4%, from –2.70 to –2.74.

Discussion

Before 1970, undue lead exposure was defined

by a blood lead level of 60 μg/dL or higher—a

level often associated with overt signs or symptoms of lead toxicity, such as abdominal colic,

anemia, encephalopathy, and death. Since

then, the blood lead concentration for defining

undue lead exposure has been reduced: from

60 to 40 μg/dL in 1971, to 30 μg/dL in 1978,

and to 25 μg/dL in 1985 (CDC 1991). In

1991, the CDC, and subsequently the WHO

(1995), further reduced the blood lead value

defining undue lead exposure to 10 μg/dL

(CDC 1991). These ongoing reductions in the

Childhood lead exposure and intellectual function

Environmental Health Perspectives • VOLUME 113 | NUMBER 7 | July 2005 897

Table 3. Concurrent blood lead concentration and mean IQ scores by characteristics of children and their

mothers (n = 1,333).

Median concurrent

blood lead (μg/dL)

Covariate No. (5th–95th percentiles) IQ ± SD

Child

Female 669 9.0 (2.4–31.4) 93.8 ± 18.3

Male 664 9.9 (2.6–35.7) 92.5 ± 20.0

Birth weight (g)

< 3,000 359 10.0 (2.2–28.7) 88.6 ± 18.0

3,000 to < 3,500 519 9.9 (2.4–34.2) 93.6 ± 19.3

≥ 3,500 455 9.1 (2.8–34.7) 96.3 ± 19.3

Gestation at delivery (weeks)

< 38 144 8.9 (3.1–37.9) 83.5 ± 18.6

38 to < 42 1,071 9.8 (2.5–33.2) 94.1 ± 18.6

≥ 42 115 10.0 (3.2–24.8) 96.3 ± 22.1

Birth order

1 479 9.0 (2.1–32.6) 96.7 ± 18.9

2 407 10.0 (2.6–31.4) 93.6 ± 19.2

≥ 3 446 10.0 (3.0–36.9) 89.0 ± 18.7

Maternal

Race (only U.S. cohorts)

White 278 7.9 (1.3–22.0) 100.6 ± 20.1

Nonwhite 401 7.1 (2.8–21.5) 84.9 ± 12.8

Age at delivery (years)

< 25 650 10.5 (3.0–32.0) 89.6 ± 17.2

≥ 25 683 9.0 (2.1–34.7) 96.5 ± 20.3

Maternal IQ

< 85 618 10.0 (2.9–32.0) 83.3 ± 15.0

≥ 85 715 9.0 (2.1–34.3) 101.6 ± 18.3

Education at delivery (grade)

< 12 710 12.0 (4.1–35.5) 90.4 ± 18.8

12 397 8.7 (2.4–34.3) 91.1 ± 17.7

≥ 12 226 5.5 (1.1–15.2) 105.5 ± 18.0

HOME score

< 30 276 9.4 (3.0–43.0) 77.9 ± 14.9

30 to < 40 561 10.0 (2.8–32.2) 88.3 ± 15.4

≥ 40 496 9.5 (2.0–22.0) 107.0 ± 15.8

Married

Yes 896 10.0 (2.7–37.5) 96.2 ± 20.5

No 436 8.1 (2.4–22.0) 87.0 ± 14.3

Prenatal smoking

Yes 453 11.5 (3.2–33.2) 89.5 ± 17.2

No 876 8.7 (2.2–33.6) 94.9 ± 19.9

Prenatal alcohol ingestion

Yes 278 10.1 (2.2–25.0) 99.3 ± 19.4

No 1,035 9.5 (2.7–34.3) 91.7 ± 18.8

Table 4. Mean unadjusted and adjusteda changes in full-scale IQ score associated with an increase in

blood lead concentration (log scale), from the 5th to 95th percentile of the concurrent blood lead level at

the time of IQ testing.

Blood lead IQ deficits

Unadjusted Adjusted concentration [5th to 95th

estimates estimates (5th to 95th percentile

Blood lead variable [β (95% CI)] [β (95% CI)] percentile, μg/dL) (95% CI)]

Early childhood –3.57 (–4.86 to –2.28) –2.04 (–3.27 to –0.81) 4.1–34.8 4.4 (1.7–7.0)

Peak –4.85 (–5.16 to –3.54) –2.85 (–4.10 to –1.60) 4.0–34.5 6.1 (3.4–8.8)

Lifetime average –5.36 (–6.69 to –4.03) –3.04 (–4.33 to –1.75) 6.1–47.0 6.2 (3.6–8.8)

Concurrent –4.66 (–5.72 to –3.60) –2.70 (–3.74 to –1.66) 2.4–33.1 7.1 (4.4–9.8)

aAdjusted for site, HOME score, birth weight, maternal IQ, and maternal education. The addition of child’s sex, tobacco

exposure during pregnancy, alcohol use during pregnancy, maternal age at delivery, marital status, and birth order did

not alter the estimate, and these were not included in the model. The estimates for the covariates in the concurrent blood

lead model were HOME score (β = 4.23, SE = 0.54), birth weight/100 g (β = 1.53, SE = 0.35), maternal IQ (β = 4.77, SE = 0.57),

and maternal education (β = 1.12, SE = 0.46).
acceptable levels of children’s blood lead were

motivated by evidence showing that blood lead

concentrations as low as 10 μg/dL were associated with adverse effects, such as lower intelligence (CDC 1991; WHO 1995).

In this pooled analysis, we found evidence

of lead-related intellectual deficits among

children who had maximal blood lead levels

< 7.5 μg/dL. Indeed, we found no evidence of

a threshold. Other studies reported a similar

finding, but questions about the relationship at

lower levels remained because they involved

smaller numbers of children with blood lead

< 10 μg/dL or they did not adjust for important covariates (Canfield et al. 2003; Fulton

et al. 1987; Lanphear et al. 2000; Schwartz

1994; Schwartz and Otto 1991; Walkowiak

et al. 1998). In the pooled analysis, we estimated the blood lead–IQ relationship with

data from the 5th to 95th percentile of the concurrent blood lead level at the time of IQ testing, which tends to underestimate the adverse

effects of blood lead levels. For the entire

pooled data set, the observed decline of 6.2 IQ

points (95% CI, 3.8–8.6) for an increase in

blood lead levels from < 1 to 10 μg/dL was

comparable with the 7.4 IQ decrement for an

increase in lifetime mean blood lead levels from

< 1 to 10 μg/dL observed in the Rochester

Longitudinal Study (Canfield et al. 2003).

Consistent with other studies (Bellinger

and Needleman 2003; Canfield et al. 2003;

Fulton et al. 1987; Lanphear et al. 2000;

Schwartz 1994; Schwartz and Otto 1991;

Walkowiak et al. 1998), the lead-associated

IQ deficits observed in this pooled analysis

were significantly greater at lower blood

lead concentrations. In a meta-analysis, the

observed decrement was greater in study

cohorts in which children with blood lead

levels < 15 μg/dL were more heavily represented (Schwartz 1994). In the Rochester

Longitudinal Study, there was an estimated

reduction of 7.4 IQ points for an increase in

lifetime mean blood lead from 1 to 10 μg/dL

(Canfield et al. 2003). In contrast, IQ scores

declined 2.5 points for an increase in blood lead

concentration from 10 to 30 μg/dL (Canfield

et al. 2003). The larger sample size of this

pooled analysis permitted us to show that the

lead-associated intellectual decrement was significantly greater for children with a maximal

blood lead of < 7.5 μg/dL than for those who

had a maximal blood lead of ≥ 7.5 μg/dL.

Although the difference in coefficients associated

with the IQ decrement for children who had a

maximal blood lead concentration < 10 μg/dL

versus ≥ 10 μg/dL was not statistically significant, the results were consistent with the analysis

using 7.5 μg/dL as a cut-point.

We found that concurrent blood lead levels or average lifetime estimates of lead exposure were generally stronger predictors of

lead-associated intellectual deficits than was

maximal measured (peak) or early childhood

blood lead concentration. Although this finding conflicts with the widely held belief that

2-year (or peak) blood lead levels are the most

salient measure of lead toxicity, there is

increasing evidence that lifetime mean blood

lead and concurrent blood lead levels are

stronger predictors of IQ in older children

(Baghurst et al. 1992; Canfield et al. 2003;

Dietrich et al. 1993; Factor-Litvak et al.

1999). The stronger effects of concurrent and

lifetime measures of lead exposure may be

due to chronicity of exposure (Bellinger and

Dietrich 1994). Alternatively, the weaker

association with blood lead measured during

early childhood may be due to exposure misclassification from the greater within-child

variability of blood lead in younger children.

Nevertheless, because blood lead concentrations taken in early childhood track closely

with subsequent blood lead levels (Baghurst

et al. 1992; Canfield et al. 2003; Dietrich

et al. 1993), we cannot entirely resolve the

question of whether children are more vulnerable to lead exposure during the first 2 years

of life. Still, young children do ingest more

lead during the first 2 years of life and may

absorb it more efficiently than do older children and adults (Clark et al. 1985; Lanphear

et al. 2002; Ziegler et al. 1978). Thus, efforts

to prevent lead exposure must occur before

pregnancy or a child’s birth.

The specific mechanisms for lead-induced

intellectual deficits have not been fully elucidated. There are several plausible mechanisms

for the greater lead-associated intellectual

deficits observed at blood lead levels < 10 μg/dL

(Lidsky and Schneider 2003; Markovac and

Goldstein 1988; Schneider et al. 2003), but it is

not yet possible to link any particular mechanism with the deficits observed in this pooled

analysis. Nevertheless, efforts can be taken to

reduce environmental lead exposure without

full elucidation of the underlying mechanism

(Wynder 1994).

The observational design of this study

limits our ability to draw causal inferences.

Instead, we must rely on the consistency of

findings from numerous epidemiologic and

experimental studies in rodents and nonhuman

primates, including evidence that environmental lead exposure is associated with intellectual deficits at blood lead levels < 10 μg/dL.

There are potential limitations of the tools we

used to measure important covariates. The

HOME Inventory was not conducted at the

same age for children in all of the sites, and the

HOME Inventory and IQ tests have not been

validated in all cultural or ethnic communities.

Nonetheless, because these covariates were

standardized and adjusted for study site, these

problems do not pose any limitations to the

interpretation of the pooled analysis results.

Lanphear et al.

898 VOLUME 113 | NUMBER 7 | July 2005 • Environmental Health Perspectives

Figure 1. Restricted cubic splines and log-linear

model for concurrent blood lead concentration.

The dotted lines are the 95% CIs for the restricted

cubic splines.

105

100

95

90

85

0 5 10 15 20 25 30 35 40 45 50

Concurrent blood lead (μg/dL)

IQ

Log-linear model

5 knot spline

95% CI

Figure 2. Linear models for each cohort study in the

pooled analysis, adjusted for maternal IQ, HOME

score, maternal education, and birth weight. The

figure represents the 5th to 95th percentile of the

concurrent blood lead level at the time of IQ testing.

120

110

100

90

80

70

Concurrent blood lead (μg/dL)

IQ

0 10 20 30 40 50 60

Boston

Mexico

Port Pirie

Cleveland

Cincinnati

Rochester

Yugoslavia

Figure 3. Log-linear model (95% CIs shaded) for

concurrent blood lead concentration, adjusted for

HOME score, maternal education, maternal IQ, and

birth weight. The mean IQ (95% CI) for the intervals

< 5 μg/dL, 5–10 μg/dL, 10–15 μg/dL, 15–20 μg/dL,

and > 20 μg/dL are shown.

105

100

95

90

85

Concurrent blood lead (μg/dL)

IQ

0 10 20 30 40

Figure 4. Log-linear model for concurrent blood

lead concentration along with linear models for

concurrent blood lead levels among children with

peak blood lead levels above and below 10 μg/dL.

105

100

95

90

85

0 10 20 30 40 50

Concurrent blood lead (μg/dL)

IQ

Log-linear model

Peak blood lead ≥ 10 μg/dL

Peak blood lead < 10 μg/dL
Childhood lead exposure and intellectual function

Environmental Health Perspectives • VOLUME 113 | NUMBER 7 | July 2005 899

There are other predictors of neurodevelopmental outcomes that we did not examine in

this pooled analysis, such as maternal depression. The omission of unmeasured variables

may produce residual confounding (Pocock

et al. 1994). Still, in studies that did examine

other relevant covariates, such as breast-feeding

and iron status, the estimated effect of lead was

not altered appreciably (Canfield et al. 2003;

Needleman et al. 1990; Tong and Lu 2000).

Finally, each of the cohorts has unique limitations that raise questions about the validity and

generalizability of their findings. Nevertheless,

the results of these analyses indicate that the

results are robust and not dependent on the

data from any one site.

The impact of low-level environmental

lead exposure on the health of the public is

substantial. This pooled analysis focused on

intellectual deficits, but environmental lead

exposure has been linked with an increased

risk for numerous conditions and diseases that

are prevalent in industrialized society, such as

reading problems, school failure, delinquent

behavior, hearing loss, tooth decay, spontaneous abortions, renal disease, and cardiovascular disease (Borja-Aburto et al. 1999;

Dietrich et al. 2001; Factor-Litvak et al. 1999;

Lin et al. 2003; Moss et al. 1999; Nash et al.

2003; Needleman et al. 2002; Schwartz and

Otto 1991). Although only a few studies have

examined the association of these conditions

or diseases among individuals with blood

lead levels < 10 μg/dL (Borja-Aburto et al.

1999; Lanphear et al. 2000; Moss et al. 1999;

Schwartz and Otto 1991), the evidence is

growing.

In conclusion, the results of this pooled

analysis underscore the increasing importance

of primary prevention as the consequences of

lower blood lead concentrations are recognized.

Although blood lead concentrations < 10 μg/dL

in children are often considered “normal,” contemporary blood lead levels in children are

considerably higher than those found in preindustrial humans (Patterson et al. 1991).

Moreover, existing data indicate that there is no

evidence of a threshold for the adverse consequences of lead exposure. Collectively, these

data provide sufficient evidence to eliminate

childhood lead exposure by banning all

nonessential uses of lead and further reducing

the allowable levels of lead in air emissions,

house dust, soil, water, and consumer products

(Lanphear 1998; Rosen and Mushak 2001).

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