Exposure to Lead and Specific
Attentional Problems in Schoolchildren
Barbara Minder, Edith A. Das-Smaal,
A pilot study was carried out to investigate the relationship between exposure to lead and attention
in children. The participants were 43 boys, 8 to 12 years of age, attending special schools for
children with educational and/or learning problems (so called LOM schools). Children with
probable causes of attentional or memory problems other than lead contamination were excluded from
the study. Various aspects of attention were measured using neuropsychological tests. As an
assessment of body lead burden, lead concentration in the boys' hair was measured by means of the
Synchrotron Radiation-Induced X-ray Fluorescente technique (SXRF). Information was collected
about variables that possibly could influence attention and/or body lead burden (confounding
factors). A multiple regression analysis was used to determine the contribution of lead to variante in
performance, after correction for confounding factors. The results showed that children with
relatively high concentrations of lead in their hair reacted significantly slower in a simple
reaction-time task than did children with relatively low concentrations of lead in their hair. In
addition, the former were significantly less flexible in changing their focus of attention, even after
correction for the influence of their delayed reaction time.
A ttentional deficits are are ongoing
topic of interest for many researchers
from a diversity of disciplines
because these deficits represent one
of the most prevalent childhood
problems. Although there has been
much speculation as to the cause of
attentional problems, little is certain
on this point. It is clean, however,
that children with an attentional
deficit do not foren a homogeneous
group (Quai, Routh, & Shapiro,
1987). The selection of a treatment
approach depends on a proper assessment of the nature and cause of the
problem; therefore, it is very important
to
discriminate
among
various
sub-types of deficits and to sort out
the underlying factors.
as a causative factor. Lead, and occasionally some other heavy metals, has
been mentioned for its possible
ad-verse
effects
on
cheldren's
behavior and cognitive functioning
(e.g., Moon, Marlowe, Stellern, &
Errera, 1985). Studies on this topic
have been critically reviewed by
Rutter (1983), Lansdown (1986),
Grant and Davis (1989), and others.
As these reviews indicate, most of the
research
fendings
suffer
from
methodological
and
statistica)
shortcomings. Hówever, considering
the results from different types of
well-designed studies, both human
and anima), it can be concluded that
the weight of evidence points to some
link between low-level exposure to
Lires of research on etiological factors
lead and performance. A recent
range from neurologica) to socialmeta-study
by
Needleman
and
Gatsonis (1990) has added to the
evidence.
pedagogical studies (Ross & Ross,
1982). One possible hypotheses focuses
on environmental polluting influences
Eddy E J. M. Brand, and
Jacob E Orlebeke
In examining the relationship between exposure to lead and children's
behavior, many transsectional studies
have used a "broadband" approach
and measured a variety of behavioral
effects in a relatively shallow way.
Often, questionnaires were used, or
measures such as IQ, which is an
integrated score that reflects various
cognitive functions together. In a relatively uninvestigated area like the
present one, such studies are important in providing first indications.
One important cognitive function that
seems to be implicated is the attentional factor (David, Hoffman,
Clark, Grad, & Sverd, 1983; Fergusson, Fergusson, Horwood, & Kinzett,
1988; Needleman et al., 1979; Selva,
Hughes, Williams, & Faed, 1988; Yule,
Urbanowicz, Lansdown, & Millar,
1984). The next step should be directed at further specifying the relationship between low-level exposure to
lead and attention. Measures of attention other than questionnaires should
be used and a further distinction be
made among different aspias of attention. This is an important issue for further envestigation.
Another point is that the relationship
between low-level exposure to lead
and cheldren's performance seems to
be a very wenk one when measured in
samples that are representative of the
JOURNAL OF LEARNING DISABILrrIES
VOLUME 7J, N U M B E R 6 , J U N E I J U L Y 1 9 9 4
PAGES 393-399
394
whole
population (Fergusson et al., 1988).
Although even a very small effect on
the whole population may not be
without
socioeconomical
consequences, the issue may be more relevant to some subgroups of children.
Within specific groups of children with
some behavioral or cognitive impairment, especially impairment with no
known etiology, the relationship may
show up in a more distint way.
The present study investigates lead
contamination as a possible specific
cause of attentional problems among
a selected group of children. With our
selection process we hoped to provide
a more efficient design for estimating
the possible effect of lead on attention,
independent of any other adverse effect on attention. The examination was
intended as a pilot study for more intensive investigations. The subjects
were selected from a group of children
with learning and other school-related
problems, for which they attended a
special education school. At special
schools there is a substantial number
of children with attentional problems,
the causes of which often remain
unidentified. The selection of children
implies a screening in advance of possible causes of attentional problems
other than ecologica) factors, but not
of attentional problems themselves.
These were later measured by the
test- procedure. As a result, a group
of children were examined whose attentional problems, if any, were of
unknown etiology. It was hypothesized that for the children with attentional problems in this group, lead
played an important role in the etiology. n a t is, it was expected that the
effect of lead would show up in
disturbances of attention, and that this
might be
further
specified
in
particular aspects of attention.
Attention is not a unitary concept,
and it is generally accepted that various types of attention can be distinguished. Important aspects are
selective attention, divided attention,
sustained attention, and flexibility of
attention. The relevante of such a
distinction has been demonstrated,
JOURNAL OF LEARNING DISABILITTES
both regarding attentional problems
at school (Brand, Das-Smaal, & de
Jong, 1992; de Jong, 1991) and
among various clinical groups with
attentional deficits (e.g., Brouwer,
1985; Derix, 1991). In the present
study, we were interested in
whether attention is related to lead
exposure, and if so, what aspects are
implicated. To our knowledge, no
results are known on the lat-ter
topic.
For each attentional aspect, we
chose
a
test
for
which
neuropsychological studies have
already indicated a sensitivity in
discriminating
children
with
attentional problems from control
children (Berndsen-Peeters & van der
Vlugt, 1986; Lezak, 1983; Rourke,
Bakker, Fisk, & Strang, 1983;
Spreen & Strauss, 1991). In
addition, we measured reaction time
as a direct indicator of processing
time.
Pazental and teacher questionnaires
provided an indication of behavior at
home and in school. Furthermore, a
body of information was collected
with respect to possible confounding
factors that appeared to be important
in other work on this subject (e.g.,
Fergusson et al., 1988). Relevant
factors were statistically controlled.
Blood lead concentrations, dentine
lead concentrations, and hair lead
concentrations are generally used as
estimators of lead exposure. Each of
these measures has its limitations.
Current level of blood lead reflects
exposure over a short period of time,
as the halflife of lead in human
blood is about 30 days. Dentine lead
estimates
suffer
from
other
problems, for example, varying lead
concentrations in different places in
the same tooth, differences in lead
concentrations among tooth types in
the same mouth, and differences in
the age at which children loose their
teeth. Furthermore, measurement of
the possible behavioral effects of the
lead exposure may come at a much
later time than the loss of the teeth.
Lead concentration in the hair com-
pared to in the blond is relatively insensitive to short-term fluctuations of
lead exposure. On the other hand, lead enced by exposure from the environlevels in hair are also directly influment. Along with the structure of hair,
its color and washing procedures may
influence lead concentration. Nevertheless, in this study hair analysis was
chosen as a diagnostical tooi to estimate exposure to lead because of its
advantage of being noninvasive, and
being more easily obtained than other
estimators. We took the precautions of
using stainless-steel scissors and taking the sample from the nape of the
neck, as close to the scalp as possible.
Method
Subjects
Subjects were boys, 8 to 12 years of
age, from two special education
schools (Grades 4 to 8). The following
categories of children were excluded:
children with a history of pre- or perinatal complications, serious infections,
feverish convulsions, acute poisoning,
concussion or head trauma, meningitis, or frequent otitis media; children
on medication; or children having
oude physiological, visual, auditory, or
motor defects. Children with the following in their family history were
excluded: a hereditary factor for attentional problems (i.e., parental attention
deficit-hyperactivity disorder), obvious Jack of educational opportunity,
low socioeconomic status (SES), or
problems at home. Finally, the child's
IQ had to be within the range of 80 to
130. The selections were made by the
school doctors and principals; 45 children were chosen. Of this group, 43
children were allowed by their pazents
to participate in the study. They were
aged 8.3 to 12.0 years (mean = 10.2);
their (total) IQ ranged from 85 to 123
(mean = 100).
Tests
A battery of psychometric tests covering various aspects of attention,
memory, and motor speed was used.
The battery contained both computerized and paper-and-pentil tasks. These
1. Eye-Hand Coordination. In this task, fill in the code corresponding to each
a sine-wave-shaped lire projected digit.
Underlining. A target pattern must
induded selected tests from the Neurobe memorized. Next, this pattern
behavioral Evaluation System (NES)
(Baker & Letz, 1986) and the Wechsler 7. must be underlined on a form with
Intelligence Scale for Children-Revised
a series of different patterns. A
(WISC-R) (Wechsler, 1974).
limited time period is allotted.
The NES is a computerized battery ofStroop Test. Color names are printpsychometric tests, adapted fored in conflicting colors on a card.
The task is to name the color of the
use in the Netherlands by Emmen, 8.
print and to r e s t distraction from
Hoogendijk, Hooisma, Orlebeke, and
the conflicting word name.
Uijtdehaage (1988). The following tests
were employed:
Trail Making Tests A and B (TMTA
and TMTB). In TMTA, circles
on a computer screen must be 9.
con- digits 1 to 15 scattered
moved vertically by a joystick in
over a piece of paper are to be consuch a way that a horizontally
nected as quickly as possible. In
moving dot stays as close as posTMTB, the child is asked to altersible to that lire. The task consists
nately connect circles with digits
of four trials; the first trial serves
and letters, in counting order and
as practice.
alphabetical order, respectively.
2. Simple Reaction Time (RT) Task.
Beert' Test. In this paper-and-pendl
Subjects are asked to react as
test, the child has to copy figures
quickly as possible to the appear- 11.of increasing complexity. The figance of a square on the screen by
uren remgin in sight.
pushing a button. A total of 72
Dichotic Listening. In each trial, foor
stimuli are presented at intervals
digits are presented via headvarying between 2.5 and 5.0 secphone to the left ear and, simul13.
onds. The first 28 stimuli serve as
taneously, four are presented to
practice.
the right ear, at a rate of two pairs
per second. The child is asked to
repeat as many digits as possible
3. Choice Reaction Time Task. Letters
from both ears. This test contains
are projected one by one onto a
16 trials.
computer screen with a fixed
inter-val of 1 second. The letters
flash for about 50 milliseconds on
the display. The child has to
Table 1 summarizes the tests
respond as quickly as possible
that were used, their origins, the
exclusively
to
a
previously psychological aspects they were
specified target let-ter and is intended to measure, and the kinds
asked to make no mis-takes. A of scores derived from them.
total of 60 target stimuli are
presented; the first 4 stimuli serve
as practice.
Psychological Factors
4. Mazel. In this paper-and-pencil
test, the child is asked to trace a
mate as quickly as possible, and
with few errors, without entering
into blind alleys. The complexity of
the mazel increases.
5. Digit Span. Series of digits increasing in length are given auditorily.
The child is asked to repeat the
digits in the same order.
6. Coding. Several digits are shown.
Below each digit is a visual code.
Afterward, the child is asked to
VO LUM E 77, NUMBER 6, JUNEIJULY 1944
Information about psychologica) factors was derived from teacher and
parental questionnaires. The teacher
questionnaire used was the Dutch
School Behavior Questionnaire (de
Sonneville, 1988). This checklist consists of 28 items measuring the following leven factors: attention, activity,
verbal impulsivity, motivation, personal appearance, self-confidence, and
variable task application. The list was
supplemented by nine questions about
395
flexibility of attention, impulsivity, and
emotional problems. For the parental
questionnaire, the two questions with
the highest loading for each factor Erom
the teacher list were adapted for the
home environment.
Confounding Factors
Information about potential confounding factors was obtained Erom
school records and from the parental
questionnaire. This questionnaire contained 27 questions about potential
confounders. The following factors
were implicated: IQ (WISC-R), SES,
school, pica (history, frequent'), passive smoking, environmental noise,
television viewing habits, sleeping
habits, emotional problems, restless
behavior, allergy, place in birth order,
and family site.
Hair Analysis
Hair samples were analyzed by
means
of
Synchrotron
Radiation-Induced
X-ray
Fluorescence (SXRF), under the
supervision of Dr. R. D. Vis of the
Department of Physics at Vrije
Universiteit Amsterdam. The procedure for determining trace elements
with this method has been described
elsewhere (van Langevelde, Tros, &
Vis, 1989). Bulk analysis was performed, and the hair samples were
examined for lead concentration.
Procedure
The children were tested individually by two test assistants in separate
rooms at school. The tests ware administered in the following order:
Eye-Hand
Coordination,
Simple
Reaction Time, Choice Reaction Time,
Dichotic
Listening,
Underlining,
Stroop, Coding, Digit Span, Mazes,
Trail Making A and B, and Beery.
On the day of testing, hair samples
were carefully collected from the nape
of each child's nacc, as dose to the scalp
as possible, using stainless-steel
scissors and the appropriate means to
further treat the hair samples. The
sam-
396
JO UR NAL OF LEAR NING D IS ABILITIES
TABLE 1
Tests Used in the Study
Test
Origin/reference
Aspect of
psychological functioning
Eye-Hand Coordination
NES
Visual-motor functioning,
processing speed
Simple Reaction Time
NES
Visual-motor functioning,
processing speed
Choice Reaction Time
NES
Selective and sustained
attention
Mazes
WISGR
Digit Span
WISGR
Coding
WISGR
Underlining Test (shortened
version)
Stroop Test
Trait Making Tests A and B
Beery Test
Dichotic Listening Test
Measure
Accuracy
Speed variability
Speed variability, number of
false responses
Planning behavior
Short-term memory
Number of correct responses
Concentration, visual search
Rourke & Petrauskas(1977)
Selective and sustained
attention
Hammes (1978)
Response-inhibition, sensitivity
to interference
Accuracy
Number of correct responses
Number of correct responses
Speed
Flexibility of attention
Reitan & Davison (1974)
Visual-motor integration
Beery & Buctenica (1967)
Speed
Divided attention
Number of correct responses
Bakker, Vlugt, & Claushuis
(1978)
Total correct responses (left
and right)
Note. WISGR = Wechsler Intelligence Scale for Children-Revised; NES = Neurobehavioral Evaluation System.
pies were subsequently submitted to
the Department of Physics at Vrije
Universiteit Amsterdam for lead
analysis.
Results
able was taken into the multiple
regression model if p < .10 for the
correlation with lead and/or a
neuropsychological measure. Irrespective of this, because of their putative
importance, age, SES, IQ, and pica
were taken as covariates into the
regression equation.
Mean lead concentration in hair was
1.26 parts per million (ppm), with a
One outlier with a high concentra- standazd deviation of 1.09. Lead contion of lead in his hair was removed centration range was 4.10 ppm. SimErom the dataset. An outlier was de- ple Reaction Time ranged Erom 288 to
fined as a case falling at least 3 stan- 580 milliseconds.
dazd deviations Erom the mean hair
lead concentration. As far as necessary,
the raw scores of the variables were
From the correlational analysis the
transformed to approximate normal following results were obtained. Lead
distribution. The same transformation hair concentration was significantly
was employed in variables of the same correlated with performance time on
test if they were measured in the same three tests: Simpte Reaction Time (r =
unit (e.g., speed in Trait Making A and .37, p = .008); Trail Making Test A (r
B). Next, correlations between vazi- = .29, p = .032); and Trait Making Test
ables were calculated. The influence of B (r = .40, p = .004). Correlations beother factors on the differences in per- tween lead concentration in hair and
formance was paztialed out in a sub- the possible confounding factors were
sequent analysis. In this analysis, the not significant, although lead concencontribution of lead to performance tration in hair tended to be lower in the
differences was calculated by mean of older children (p = .097). There was
a multiple regression analysis. A varialso a tendency for older children to
have lower IQs in the present sample
(p = .090).
The following was found regarding
the correlations between the test van ables related to lead (i.e., RT, TMTA,
TMTB) and the possible confounding
factors. TMTB and RT showed a negative correlation with age (p = .022 and
p = .001, respectively). This means
that the older children completed both
tests more quickly. Furthermore, the
children with lower IQs tended to execute Trail Making Test A more slowly (p = .082). None of the three test
vaniables showed a significant relationship with any other possible confounding factor at p < .10.
In the multiple regression analysis,
age, SES, IQ, pica, and, as the last vanable, lead (Pb) were entered into the
model. This analysis revealed that after
correction for confounding factors, significant correlations existed between
lead and reaction time and between
lead and speed on Trait Making Test
B (p < .05). The higher the lead con-
397
V O L UM E 27, N UM B E R 6, J U N E / J U L Y 1 9 4 4
centration in hair, the longer the reaction time and the poorer the performance on Trail Making Test B. After
correction for reaction time, the correlation between TMTB and lead was stil)
significant (p < .05). This implies that
the higher the lead concentration in
hair, the slower the execution of Trail
Making Test B, even after correction
for the possible influences of age, SES,
IQ, pica, and reaction time.
Table 2 shows to what degree the
variables explained the differences in
performance among children. The
table shows the proportion of
test-score variance among children
explained by age, SES, IQ, and pica
together; the proportion of test-score
variance among children explained by
these variables but including lead; the
proportion of test-score variance
among children explained just by lead
after removal of the contribution of the
other variables ("increase by Pb"); and
the p value of the additional variance
explained by lead.
From Table 2 it can be seen that
21.4% of the variance in performance
of the Simple Reaction Time Task was
explained by age, SES, IQ, and pica
together. Lead alone explained another
8.3% (p = .046). After correction for
age, SES, IQ, and pica, the contribution of lead to explaining the variance
in performance on Trail Making Test
A was not significant. For Trail Making Test B, however, lead explained
11.7% of the variance in performance
(p = .022), in addition to the 14.7% of
variance explained by the four confounding factors. Even after correction
for reaction time, lead explained
another 9.9% (p = .037).
Discussion
This study aimed to Eind out whether
ecologica) factors are relevant to the
investigation of causes of specific attentional problems. The investigation
focused on lead, as this heavy meta)
has been frequently mentioned for its
supposed adverse effects on cognitive
functioning. Results show that, with-
TABLE 2
Variance of the Test Scores in Proportions, Explained by Variables
Age, SES,
IQ, pica
RT
TMTA
TMTB
TMTCa
21.4
9.8
14.7
16.5b
Idem +Pb
29.7
14.8
26.4
26.4
Increase
by Pb
8.3
5.0
11.7
9.9
Sign of increase
(p value)
.046
.155
.022
.037
out correction for possible confounding factors, performances on Trail
Making Tests A and B and the Simple
Reaction Time Task had significant
negative relationships with lead concentration in hair.
Two confounding factors were identified, the most important one being
age. Some test variables appeared to
be related to age, which is not
surprising Biven the age range of the
children (8 to 12 years). It is known
that in that age range, tasks are
performed better as children age. The
second confounding factor was IQ. It
appeared that for the older children,
IQ tended to be lower. This
phenomenon is not unknown in
special education schools (van den
Bos, 1988); van den Bos attributed it
to a stagnation of verbal development
that increases with age in these
children, due to differences in
learning strategies. In the present
study, performance did not seem to be
influenced by SES. A possible explanation could be that in the population
investigated, the children's SES was
rather homogeneous. Also, pica was
not of influence.
In all, the results on confounding
variables showed that in the analysis
of the test results, it was important to
correct for age and IQ. At the risk of
overcorrection, a correction was also
made for SES and pica because this is
usually done in this type of study.
After this correction, a small but significant effect still seemed to be attributable to lead in the Simple Reaction Time Task and in Trail Making
Test B. Children with a relatively high
concentration of lead in their hair had
a slower reaction speed on the Simple
Reaction Time Task. This has allo been
found in other studies (e.g., Hunter,
1985; Needleman, 1979). Speed of
reaction may affect speed of performance on Trail Making Tests A and B.
In a study on the factor structure of
standard attention tests for children,
de Jong and Das-Smaal (1991) showed
that common attention tests measure
either perceptual speed or working
memory functioning. The laffer factor
has been identified with attentional
control (Baddely, 1986). Thus, the
speed factor should be distinguished
Erom attentional control. In the present
study, after correction for reaction
speed, Trail Making Test B was stil) significantly correlated with lead, which
mean that apart Erom speed, attention
was less flexible in children with
higher hair lead levels. Considering
the small number of children and the
low variance in lead concentration,
these results are remarkable. However,
it should be noted here that the present
methodological approach (Le., the
selection of a specific sample) heightens the chance of finding a relationship. A consequence of this approach
is that the results can be generalized
only to a comparable group of subjects.
The relationhip with reaction time
shows that lead effects can be found at
a basic level. Reaction time provides a
reliable and valid measure of the functional integrity of the centra) nervous
system. Simple reaction time is probably less sensitive to learning and confounding social factors than are other
measures of psychologica) functioning.
This is an important advantage be-
398
JO URNAL OF LEAR NING D IS ABILITIES
cause confounding factors can severely hamper conclusions in studies on
the subtle effects of low-level exposure
to lead (Yule, 1986).
ABOUT THE AUTHORS
Apart Erom reaction time, flexibility
of attention, as measured by Treil Making Test B, was related to lead. Flexibility of attention is an aspect of
attentional control (Stuss & Benson,
1986). An attentional-control deficit in
connection with lead has also been
shown in experiments with monkeys
(Rice, 1984, 1985). Lead-teeated monkeys made a significantly greater number of errors than nontreated monkeys
in a matching task that required the
monkeys to remember a stimulus and
subsequently choose it out of three
samples. The errors of the treated
monkeys turned out to be due to interference Erom responses made on
previous trials (Rice, 1984). Moreover,
in a spatial-memory task in which
responses had to be alternated after increasing delays between trials, treated
monkeys were deficient compazed to
controls. They tended to perseverate
after the Longest delay time (Rice,
1985). Perseveration refers to a failure
in shifting attentional focus when that
is required. It is generally considered
to be the opposite of flexible attentional
control (e.g., Shallice, 1988). In
con-trast to experiments with humans,
the animal experiments reported here
pro-vide evidence for the causality of
the relationship between low-level lead
exposure and flexibility of attention, as
a group of animals was exposed to lead
and subsequently compared to a nonexposed group. Rice's (1985) results
and those of the present study converge on the specific influence of lead
on flexibility of attention.
her PhD thesis, which is in the area of behavioral toxicology. Edith A. Das-Smaal is an de Jong, P. F. (1991). Het meten van aandacht
assistant professor in cognitive psychology and [The assessment of attention]. Unpuba senior investigator at Vrije Universiteit of lished doctoral dissertation, Vrije UniAmsterdam. She is cosupervising several re- versiteit Amsterdam, Amsterdam, the
search projects on attention and attentionl Netherlands.
deficits. Eddy F. J. M. Brand is a research as- de Jong, P. F., & Das-Smaal, E. A. (1992).
sistant and PhD candidate at Vrije Universiteit
Factor structure of standerd attention tests for
of Amsterdam, working on a thesis on the meachildren: A distinction between perceptual
surement of different types of attentional deficits.
speed and working memory. Unpublished
Jacob F. Orlebeke is a professor of physiological
manuscript.
psychology at Vrije Universiteit of Amsterdam,
cosupervising several projects in the areas of Derix, M. M. A. (1991). Neuropsychological
stress, behavior genetics, attention, and attendifferentiation of dementia. Unpublished
tional deficits. Address: Barbara Minder, Vrije
doctoral dissertation, Universiteit van
Universiteit, Amsterdam, DeBoelelaan 1111,
Amsterdam, Amsterdam, the Netherlands.
1081 HV Amsterdam, The Netherlands.
de Sonneville, L. M. J. (1988). Information
processing and neonetel neurological optimality. Amsterdam: Free University Press.
David, O. J., Hoffman, S. P., Clazk, J.,
Grad, G., & Sverd, J. (1983). The relationBarbara Minder is a junior investigator in the ship of hyperactivity to moderately eleDepartment of Physiologwal Psychology at Vrije vated lead levels. Archives of Environmental
Universiteit of Amsterdam. This article is part of Health, 38, 341-346.
AUTHORS' NOTE
We are grateful to the children, parents, and
teachers who were involved in this study, and to
the
Health
Institution
DGD
Midden
Kennemerland, for their cooperation.
Emmen, H. H., Hoogendijk, E. M. G.,
Hooisma, J., Orlebeke, J. F., & Uijtdehaage, S. H. J. (1988). Adaptation of two
standardized international test batteries for use
in the Netherlands for detection of exposure to
neurotoxic compounds (Tech. Rep. MBL,
TNO). Rijswijk, the Netherlands.
Fergusson, D. M., Fergusson, J. E.,
Hor-wood, L. J., & Kinzett, N. G. (1988).
A longitudinal study of dentine lead level,
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