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Centre for International Child Health, Institute of Child Health, London WC1N 1EH, UK and * Institute of Nutrition and Food Science, University of Dhaka, Dhaka 1000, Bangladesh
3To whom correspondence should be addressed.
 |
ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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45 nmol/L (hypothyroid)] with children who had not
had low T4 levels [T4 
70 nmol/L
(euthyroid)]. The children were matched for school and grade level and
came from the same iodine-deficient regions in rural Bangladesh.
They were given a battery of cognitive, motor and school achievement
tests. We also measured their nutritional status, examined their stools
for geohelminths and assessed their home environments. A factor
analysis of cognitive and motor function tests yielded two factors, a
general cognitive factor and a fine motor factor. The children's
height and arm circumference, experience of hunger, parental
characteristics and stimulation in the home made independent
contributions to their test scores. Controlling for these variables,
the hypothyroid children performed worse than the euthyroid children on
reading and spelling and the general cognitive factor. These findings
indicate that a large number of disadvantages including hypothyroidism
are related to the poor development of these children.
KEY WORDS: • iodine deficiency • academic achievement • cognitive function • school children
|
INTRODUCTION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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). Intrauterine
iodine deficiency is well established as the cause of cretinism and
lesser degrees of cognitive and motor disability (Pharoah and Connolly 1994
), but little is known about the concurrent effect
of hypothyroidism on the intellectual performance of school-aged
children. There is a suggestion that low serum thyroxine
(T4),4
secondary to iodine deficiency, is linked to poor intellectual
performance of the people residing in iodine-deficient areas
(Hetzel 1994
). Hypothyroid patients show slowing of
intellectual function and speech and have memory deficits
(Larson and Ingbar 1992
). In addition, a study of
hypothyroid adults found significant correlations between
T4 levels and scores on cognitive tests;
improvements in cognition occurred with treatment (Osterweil et al. 1992
). A possible mechanism is suggested by the finding in
rats of a brain gene whose expression at the RNA level is influenced by
postnatal hypothyroidism (Iniguez et al. 1992
).
Research in animals has shown that intracerebral triiodothyronine
(T3), the active thyroid hormone, is generated
locally in the brain from T4 and is closely
correlated with serum T4 but not serum
T3 (Morreale de Escobar et al. 1994
). In addition, the cerebral gene (RC3 mRNA), which is
reduced in hypothyroid adult rats, can be reversed to normal levels
with oral T4 (Iniguez et al. 1992
). Serum T4 is therefore probably a
good indicator of cerebral T3.
In a number of observational studies, school-aged children living
in iodine-deficient villages were found to have poorer levels of
IQ, cognitive and motor function than school children in
iodine-sufficient villages (Azizi et al. 1993 and 1995
, Bleichrodt et al. 1987
, Boyages et al. 1989
, Fenzi et al. 1990
, Querido et al. 1978
, Tiwari et al. 1996
, Vermiglio et al. 1990
). However, villages differ in many other factors
that may affect children's development. These include accessibility
and quality of education, economic development and remoteness. Although
researchers have often taken into account macromeasures of
socioeconomic status of the children's families, other factors that
may also affect their development such as stimulation in the home and
children's nutritional and health status (PAHO, TMRU and World
Bank 1998
, Sameroff et al. 1993
) have not
usually been considered. Intervention studies, which are themselves the
most valid way of examining the relationships between iodine and
cognition in school-aged children, have proved to be difficult due
to spillover of iodine (Bautista 1982
).
In this study, we examined the association between biochemical hypothyroidism, secondary to iodine deficiency, and cognitive and motor function and school achievement in Bangladeshi children. We also examined the relationship between the outcome variables and a wide range of health, nutritional, sociocultural and socioeconomic factors and took them into account when examining the effect of hypothyroidism. To our knowledge, no previous study, has controlled for the coexistence of all of these factors. In this study, we matched children with low T4 levels with children in the same school and grade level who had high T4 levels. We therefore avoided confounding the results because of differences between villages.
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SUBJECTS AND METHODS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Three rural areas in Bangladesh (Gopalpur, Shibpur and Sirajgonj) that
had been identified as severely iodine deficient in a recent national
survey (INFS 1993
) were selected. These areas are
located in the flood-prone and plain zones of the country. All of
the children attending 21 schools in grade 1 and 2 from these areas
were requested to participate in a finger-prick blood sampling
procedure from September to November, 1994. We obtained samples from a
total of 2003 children. Eleven months after screening, all children in
two areas (Gopalpur and Shibpur) who had had T4 <45 nmol/L
on screening were enrolled in the hypothyroid group (n
= 170) and were matched for school and grade with 170 children who
had had T4 >70 nmol/L (euthyroid group). We did not study
the third area because there were not enough euthyroid children to
match the hypothyroid children.
The clinical cut-offs for T4 and
thyroid-stimulating hormone (TSH) levels are not well established
in school-aged children. On reviewing the literature, we found that
in neonatal hypothyroidism, children with T4 levels <43
nmol/L subsequently showed low IQ levels (Tillotson et al. 1994
). We therefore chose 45 nmol/L as our cut-off, which
allowed us to obtain data from170 children. This number was sufficient
to provide a significant difference between the groups of 0.5
SD in all of the educational and cognitive function tests
at the 5% level at 80% power, allowing a loss of 10%. When more than
one euthyroid child was available for matching a hypothyroid child, the
child with the highest T4 level was selected. Children with
obvious physical or mental handicaps were excluded from enrollment.
The study protocol was approved by the Bangladesh Medical Research Council's ethical review committee and the ethical review committee of Great Ormond Street Hospital for Sick Children, Institute of Child Health, London. Verbal consent was given by both parents and children.
Anthropometric measures.
Height, weight, mid-upper arm circumference (MUAC) and head
circumference were measured with the use of standard techniques
(United Nations 1986
). The anthropometric measurements
were done by two people. Before the study, 30 children were measured
separately by both observers; interobserver reliability was high
(height = 0.99; weight = 0.99; MUAC = 0.95; and head
circumference = 0.94).
Blood T4 and thyroid-stimulating hormone (TSH).
At screening, Guthrie cards were used to collect blood spots, and during enrollment, a 5-mL venous blood sample was collected from most of the children. Both the blood spots and venous samples were analyzed for serum T4 and TSH in the biochemistry laboratory of Great Ormond Street Hospital, London. This laboratory runs routine diagnostic assays for detection of hypothyroidism in the UK. The T4 samples were assayed by a RIA:coat-a-count neonatal T4 assay technique, which is a solid phase 125I RIA. The values were expressed as nmol/L. TSH samples were assayed by Gamma-BCT-Neo-TSH IRMA technique, which is a two-site immunoradiometric assay (IRMA); values were expressed as mU/L. The kits for both T4 and TSH were supplied by Diagnostic Products (Los Angeles, CA). All assays were performed by the same technician using the same kits. All assays used internal quality control standards that were introduced at the beginning, middle and end of each batch. The intra-assay coefficients of variation (CV) were 7.7, 6.2 and 4.9% at a concentration of 45, 104 and 205 nmol/L respectively. Interassay CV were 12.6, 7.4 and 7.3% for 48, 104 and 189 nmol/L, respectively. Similarly, TSH assay had a sensitivity of 0.5 mU/L and intra-assay CV were 6.6, 8.2 and 5.5% for a concentration of 20.1, 29.9 and 58.4 mU/L, respectively. Interassay CV were 6.6, 8.2 and 9.9% for a concentration of 13.1, 28.3 and 53.3 mU/L of TSH, respectively.
Hemoglobin.
Hemoglobin (Hb) was measured in the field by the Hemocue system in g/L. The calibration was checked daily by using the control cuvette supplied with the photometer.
Urinary estimation of iodine.
Casual urine samples were measured at the Institute of Nutrition and
Food Science, Dhaka University by the wet digestion method adapted by
Dunn et al. (1993)
. Values were expressed as
µmol/L and interassay CV were between 2.8 and 5.9%.
Parasite infections.
Stool samples were examined for egg-loads of Ascaris
lumbricoides, Trichuris trichiura and
Ancylostoma duodenale (hookworm) with the use of a
formol ether concentration technique (Hall 1981
). As a
quality control, 10% of the total samples were checked by a second
examiner in the laboratory; there was 90–95% agreement between the
examiners.
School attendance.
School attendance rates were obtained from school records. Generally, attendance rates were high in all schools because there was an ongoing food for education campaign program in these areas, which provided food supplements to families whose children attended school.
Socioeconomic measures.
Parents were given an in-depth interview at home, and information was sought concerning the family's sociocultural and socioeconomic conditions. Children's ages were recorded from interviewing parents on a local events calendar. The questionnaire was given by six interviewers and interobserver agreement was high. Training of each interviewer continued until there was complete agreement with the trainer in a minimum of 90% of the questions in 10 consecutive interviews.
For analyses, the responses to each question were rated with poor being low and good higher. The items were then grouped into seven indices on theoretical considerations and the ratings in each index were summed. The indices included a hunger index (weekly frequency of going to school with insufficient food, frequency of insufficient food after returning from school and frequency of going to bed hungry); stimulation activities index (frequency of reading stories or newspapers to the child, helping with home work, an adult playing with the child, taking trips outside the village, watching TV, number of toys made for the child); stimulation materials index (presence of children's books, adult books and bought toys); possession index (possession of radio, TV, cassette player, beds, tables and chairs); house index (condition of roof and walls, source of drinking water, presence of electricity, type of latrine and number of people per room) and animal index (possession of chickens, pigeons, ducks, goats and cows). The housing index was normally distributed but the other indices were not. The educational level, occupation and reading and writing ability of the parents were also determined.
Wide Range Achievement Test (WRAT).
School achievement was measured with the Wide Range Achievement Test
(Jastak and Bijou 1946
). The test comprised three
subsets of reading, spelling and arithmetic. The test was translated
into local language and was modified for Bangladesh. After extensive
piloting of the test, words for reading and spelling were rearranged in
order of difficulty for this population.
Cognitive and motor function tests.
A range of cognitive functions were measured. Some tests of speed of
processing were chosen because speed may be affected more than other
cognitive functions by biological insults in general (Connolly and Kvalsvig 1993
) and hypothyroidism in particular
(Osterweil et al. 1992
). In addition, some of the tests
that were found sensitive in previous iodine studies (Azizi et al. 1993
Bleichrodt et al. 1987
, Pharoah et al. 1981
, Sherestha 1994
) and in a
neonatal hypothyroid follow-up study in the UK (Fuggle et al. 1991
) were selected. In addition, tests that had been
sensitive to short-term food deprivation (Simeon and Grantham-McGregor 1989
) and parasitic infections
(Nokes et al.1992
, Simeon et al. 1994
) in
Jamaican children were included.
The following cognitive function tests were used:
Verbal fluency.
This test measures the speed of semantic processing and is considered
to be an indicator of the central executive component of working memory
(Baddeley 1986
). The child has to repeat as many words
as possible in 1 min in two categories, animals and things to eat.
Digit span.
The test measures the phonological loop component of working memory
(Baddeley 1986
,Baddeley et al. 1995
). The
child has to repeat strings of numbers of increasing length.
Visual search.
This test measures the speed of visual information processing and
sustained attention (Kvalsvig et al.1991
, Logie and Baddeley 1985
). The child has to search rows of different
pictures on a page and mark target pictures with a pencil as fast as
possible.
French learning test.
This test is a measure of paired associate learning (Baddeley et al. 1995
). It consists of pictures whose names are to be
learned in an unfamiliar language (French), in a set number of trials.
Corsi blocks.
This is a measure of the visuospatial sketch-pad component of
working memory (Milner 1971
). The child is presented
with a quasi-random array of black blocks and has to touch a series
of them in a specific order. The series is increased in length until
the child makes errors.
Ravens Coloured Progressive Matrices.
This is a standard test that measures visual reasoning ability and is
often used as a measure of IQ (Raven et al. 1986
).
Symbol modalities test (SSMT).
This test measures paired associate learning and the speed of
information processing. The Symbol Digit Modalities Test (Smith 1973
), used in the adult hypothyroid study (Osterweil et al. 1992
), was modified for use with children. The children are
presented with a key consisting of two shapes that are each paired with
a picture. The children are then given two pages of randomly placed
shapes in several rows and are asked to name the pictures paired with
them as fast as possible. The average speed of correctly naming a shape
is the score.
Modified Stroop. This test measures the speed of information processing and ability to inhibit responses. The test consists of two pages of six rows of black and white circles arranged randomly. The child has to touch each circle and name the opposite color, i.e., when touching black, the child calls out white. The average speed of correctly naming a circle is the score.
Upper limb speed and dexterity (ULSD).
The child has to make dots with a pencil in three rows of small circles
as fast as possible. This was modified from a subtest of the
Bruinincks-Oseretsky Test of Motor Proficiency (Bruincks
1978
). The time taken to dot all circles is the score.
The Lafayette peg board.
This is a measure of fine motor co-ordination (Lafayette
Instrument 1989
). The pegs have small protrusions along one
side, like keys, that must be rotated to match the holes before they
can be inserted.
The tests were extensively piloted and adapted where necessary for Bangladesh. Six graduates in psychology or education were trained to give the tests. The tests were administered individually on two consecutive days, with the cognitive function tests given on the first day followed by school achievement tests.
Reliability.
Before the study, each tester tested 20 children twice at an interval
of 7 d; test/retest reliability reached r 0.7 for each cognitive function test and r 0.9
for each school achievement test for each tester. Ten percent of all
tests given by each tester throughout the study were observed by a
second tester and scored independently. The testers rotated among the
group and the intertester correlations were all r
0.98.
Analyses.
Heights were expressed as Z-scores of the National Center for
Health Statistics (NCHS) reference data (Hamill et al. 1977
) and body mass index (BMI) was calculated from weight
(kg)/height2 (m2).
The data were examined for normality, and the appropriate transformation was made where necessary. The reading and spelling scores were combined into a combined reading/spelling score; this combined score and those for mathematics and four cognitive/motor tests (visual search, Stroop, peg board dominant and nondominant) were log transformed. To compare the groups, t tests and ANOVA were carried out for normally distributed variables; for nonparametric data, a chi-square test with continuity correction and the Mann-Whitney U test were used. A factor analysis of the cognitive and motor test scores was carried out to reduce any overlap among the data and identify underlying constructs, resulting in two main factors.
To assess the independent contribution of the T4 group, taking into account all confounding variables, a series of stepwise multiple regression analyses of all the school achievement and cognitive test scores were calculated. Age and sex were entered in the first step; then the social background variables, which were significant in bivariate correlations (stimulation activity, stimulation material, possessions, house index, father's education, mother's education and father's occupation), followed by biological variables (hunger index, BMI, height-for-age, MUAC and head circumference) were offered stepwise in two subsequent blocks. After this, the thyroid group (hypothyroid = 0 and euthyroid = 1) was forced to enter into the equation. The two factors were also used as dependent variables in similar multiple regressions.
The prevalence of geohelminths and Hb levels were used as additional biological independent variables in separate analyses because of the smaller sample available.
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RESULTS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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All of the children in the study gave blood samples for T4 and TSH assay. One child in the hypothyroid group and four children in the euthyroid group did not have urinary iodine measures because of scanty samples. One hundred thirty-eight (138) hypothyroid children and 129 euthyroid children gave finger prick samples for Hb estimation; 134 hypothyroid children and 131 euthyroid children gave stool samples for geohelminth egg count examination.
As expected, screening T4 concentrations were
significantly lower in the hypothyroid group than the euthyroid group,
and the hypothyroid group had significantly higher mean values for
screen TSH than the euthyroid group (Table 1
).
|
.
Although the hypothyroid group improved the most, the euthyroid group
still had significantly higher T4 concentrations
than the hypothyroid group on enrollment in the study (P
< 0.001). With groups combined, the relative position of the
children remained similar and the test/retest correlation was
r = 0.52 (P < 0.0001); the
within-group correlations were r = 0.24
(P < 0.002) for the hypothyroid group and r
= 0.21 (P < 0.007) for the euthyroid group. Only
two children had T4 < 45 nmol/L. Serum TSH
declined significantly in both groups between screening and enrollment
(paired t test for both groups; P < 0.001). The median urinary iodine excretion in the hypothyroid group (0.32 µmol/L, moderately deficient) was significantly lower (P < 0.05) than the euthyroid group (0.41 µmol/L, mildly deficient).
The hypothyroid children were slightly but significantly older than the euthyroid children (P = 0.001), and had larger MUACs (P < 0.05); however, in height-for-age, BMI and head circumference, there were no significant differences between the groups. Around 18% of the children were anemic (<110 g/L). There were no differences between the groups in the percentage of anemic children or in the prevalence of Ascaris, hookworm or Trichuris ova; ~21–35% of the children had some form of worms in their stool samples. The intensity levels of worms of all three species were low. The results were as follows: 80% had <500 eggs per gram (epg) of Ascaris; only 5% had 2000–5900 epg. For hookworm, 90% had <250 epg; and only 4% were between 500 and 1270. For Trichuris, 90% had <110 epg and only 4% were between 200 and 772 epg. Because the intensities were so low, we used only prevalence (yes = 1 and no = 0) in subsequent analyses.
Socioeconomic variables.
The children's home environments were generally poor. They had
few books, games or toys and their parents had low levels of literacy.
In addition, their standard of housing was poor; 32.6% had no
sanitation and the average number of people per room was four. There
were no significant differences in the hunger, animal and house indices
between the groups, but the euthyroid children had more stimulation
activity (P < 0.001), more stimulation material
(P < 0.05) and more possessions (P < 0.001) in their homes than the hypothyroid children (Table 2). Significantly more fathers and mothers (P < 0.001 for both) of the hypothyroid group had no formal educational
experience. There was no significant difference between the groups in
the percentage of fathers who were day laborers, the lowest paid
occupation.
|
The euthyroid group had better scores in reading and spelling
(P < 0.001) and mathematics (P < 0.01) compared with the hypothyroid group (Table 3). The euthyroid group had significantly better scores in the
French learning test (P < 0.01), but there was no
group difference in any of the other cognitive or motor tests.
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The relationships between the biological and socioeconomic variables on the one hand and school achievement tests and cognitive function tests on the other hand were examined in a series of bivariate correlations. There were many significant associations. To determine the independent contribution of the thyroid group, allowing for other significant socioeconomic and biological variables, a series of multiple regressions were conducted using each cognitive, motor and school achievement test score in turn as the dependent variable. Geohelminth infection and Hb levels were not included in these analyses because there were too many subjects with missing data.
The thyroid group made an independent contribution to the
reading/spelling score (P < 0.05) and the French
learning task (P < 0.01), even after allowing for all
significant biological and socioeconomic variables, with the euthyroid
group doing better than the hypothyroid group. Table 4 shows significant regression coefficients and standard errors from
multiple regressions of reading/spelling, mathematics and French
learning test scores. The model predicted 26% of the variance in
reading/spelling (R2 = 0.26) with age
(P < 0.001), stimulation activity (P
< 0.05), stimulation materials (P < 0.01),
father's education (P < 0.01) and hunger index
(P < 0.05) all making significant independent
contributions to the variance. In the analysis of the mathematics
score, the model predicted 30% of the variance
(R2 = 0.30); the older children
(P < 0.001) and boys (P <0.001) performed
better. Stimulation activities in the homes (P < 0.01), mother's education (P < 0.01), height-for-age
(P < 0.001) and hunger index (P < 0.01) significantly predicted performance. Allowing for all of these
independent variables, the thyroid group no longer significantly
predicted performance.
|
This model was repeated with each of the other cognitive function tests, but the thyroid group was not significantly associated with any of the outcomes.
Factor analysis.
To identify underlying constructs and remove overlap between the
scores, all of the cognitive and motor function test scores were pooled
for both groups of children and a principal component factor analysis
with varimax rotation was conducted. Two factors were identified
(Table 5), a general cognitive factor (factor 1) and a motor factor (factor
2). Variables loading more than 0.46 were accepted. Nine variables
loaded on Factor 1 as follows: digit span, Corsi block, Raven's
Progressive Matrices, French learning test, verbal fluency, Stroop,
visual search, ULSD and SSMT. Four variables, i.e., pegboard of both
hands, ULSD and visual search loaded on Factor 2, which was
predominantly a fine motor factor, although visual search also involved
attention and speed of visual information processing.
|
). Other significant variables were age (P = 0.001), stimulation activity (P < 0.05),
stimulation material (P < 0.05), mother's
education (P < 0.01) and MUAC (P
< 0.01). Thyroid group did not make a significant contribution to
the fine motor factor, whereas height-for-age (P < 0.01), age (P < 0.001), sex (boys doing better,
P < 0.05) and father's occupation
(P < 0.05) all made significant independent
contributions.
|
We repeated the multiple regression analyses of the two school achievement variables and the two factors (general cognitive and motor) using only children who had both stool and Hb examinations. There was a possibility of a loss of control for school because of missing data. In these analyses, therefore, schools were used as independent "dummy" variables and grade level (2/3) as another independent variable, keeping the same model as used previously. These new variables were offered separately in a step-wise fashion in a 4th block before the thyroid group was entered. The Hb values were used as a continuous variable and Ascaris, hookworm or Trichuris as "dummy" variables in the biological block. Neither hemoglobin nor prevalence of any geohelminth made significant contributions in any of the regressions.
|
DISCUSSION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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These findings concur with previous studies (Azizi et al. 1993 and 1995
, Bleichrodt 1987
, Boyages et al. 1989
, Fenzi et al. 1990
, Tiwari et al. 1996
, Vermiglio et al. 1990
). In all of these
studies, children in iodine-deficient villages were compared with
those in iodine-sufficient villages. In this study, we controlled
for a more comprehensive array of biological, sociocultural and
socioeconomic conditions than had been considered previously. Further,
this is the first study to control for area of residence, school and
grade level. Taking into account the consistency of the findings across
studies and countries and our rigorous control of confounders, it is
reasonable to suggest that iodine deficiency and poor school
achievement and cognition are linked causally. However, we cannot
exclude the possibility that intrauterine levels of iodine deficiency
are related to levels of iodine deficiency and low
T4 in childhood and thus account for the
association with poor cognition.
Although the paired associate learning test (French test) was the only cognitive test that differed between the groups, findings from the analysis of the cognitive factor indicates that there was a small global effect of hypothyroidism on cognition. The greatest difference between the groups was seen in reading/spelling, which is more likely than current functioning to reflect a long-term cumulative process of the children's learning. The school achievement lags may be more difficult to correct than cognitive ones without specific remedial programs.
Social background.
A number of sociocultural factors were found to be significantly
associated with school achievement and cognitive functions. Stimulation
appeared to be particularly important, and stimulation activity or
materials were significantly associated with reading, spelling and
mathematics, as well as the general cognitive factor. A number of
studies have shown that stimulation in homes was associated with better
performance in school achievement and cognitive function tests
(Walker et al. 1998
).
The level of parental education significantly predicted children's
performance in reading and spelling, mathematics and the general
cognitive factor. The importance of parental education to the child's
cognitive and educational performance has been demonstrated frequently
(Birdsall 1980
, Kiras et al. 1975
, Lockheed and Verspoor 1991
) and emphasizes
the need to push for universal access to education. It was remarkable
that even though both groups came from the same iodine-deficient
area, some differences were apparent between the groups in school
achievement and cognition with the hypothyroid group being worse off.
Biological factors.
The children's nutritional status was poor; >50% had heights
<-2 SD of the reference standards (NCHS) and a mean BMI
<14 kg/m2. Poor nutrition was associated with poor
performance in several tests. The children who experienced more hunger
(shortage of food) did worse in both school achievement tests. The
children were not hungry during the test because they were all given a
snack before testing. It appears that shortage of food may be a serious
obstacle to these children's ability to achieve in school, and
suggests that school feeding programs should be encouraged. This is
especially important in populations in which undernutrition is endemic
because their cognition is more vulnerable to the detrimental effects
of hunger than that of adequately nourished children (Pollitt et al. 1998
, Simeon and Grantham-McGregor 1989
).
Stunting or MUAC predicted children's performance in mathematics,
cognitive and motor function, which concurs with previous studies
(Grantham-McGregor and Walker 1998
).
Neither anemia nor geohelminthic infections were major problems in this
community, which may explain why they were not associated with school
achievement or cognitive or motor function tests. Anemia is often
associated with poor school achievement (Watkins and Pollitt 1998
). Similarly, studies elsewhere (Nokes et al. 1992
, Simeon et al. 1994
) have shown
associations between poor school achievement and geohelminthic
infections.
An important finding was the number of disadvantages these children
experienced in addition to iodine deficiency. Correcting hypothyroidism
is likely to benefit children's cognition; however, if they are to
benefit fully from education, comprehensive programs are necessary,
including school feeding and social development, which lead to an
improved home environment. The need for comprehensive programs is now
being acknowledged by many international agencies and professionals
(PAHO, TMRU and World Bank 1998
).
|
ACKNOWLEDGMENTS |
|---|
|
FOOTNOTES |
|---|
2 Funded by a Ph.D. scholarship from the Islamic
Development Bank, Jeddah, Saudi Arabia.
4 Abbreviations used: BMI, body mass index; epg,
eggs per gram; Hb, hemoglobin; IRMA, immunoradiometric assay; MUAC,
mid-upper arm circumference; T3, triiodothyronine; T4,
thyroxine; TSH, thyroid-stimulating hormone; ULSD, upper limb speed
and dexterity; WRAT, Wide Range Achievement Test.
Manuscript received July 15, 1998. Initial review completed September 1, 1998. Revision accepted January 20, 1999.
|
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|---|
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