Brain development parameters and intelligence in Chilean high school graduates

Intelligence 32 (2004) 461–479

Brain development parameters and intelligence in Chilean

high school graduates

Daniza M. Ivanovica,*, Boris P. Leivaa, Carmen G. Castroa, Manuel G. Olivaresa,

Joan Manuel M. Jansanaa, Veronica G. Castroa, Atilio Aldo F. Almagiab,

Triana D. Torob, Marıa Soledad C. Urrutiac, Patricio T. Millerd,

Enrique O. Boschd, Cristian G. Larraınd, Hernan T. Pereza

aPublic Nutrition Area, Institute of Nutrition and Food Technology (INTA), University of Chile, Santiago, Chile,

Avda. Macul 5540 (Entrada El Lıbano 5524), Santiago, ChilebLaboratory of Physical Anthropology and Human Anatomy, Institute of Biology, Catholic University of Valparaıso,

Avda Brasil 2959, Valparaıso, ChilecPan American Sanitary Bureau, Regional Office of the World Health Organization,

Pan American Health Organization (PAHO), Washington, DC, USAdDepartment of Magnetic Resonance Imaging Service, German Clinic of Santiago, Avda. Vitacura 5951, Santiago, Chile

Received 26 November 2003; received in revised form 7 July 2004; accepted 8 July 2004

Abstract

The hypothesis that independently of sex, brain volume (BV) and head circumference (HC) are positively and

significantly associated with intellectual quotient (IQ) was examined in a sample of 96 high school graduates of

high [Wechsler Intelligence Scale for Adults—Revised (WAIS-R)N120] and low IQ (WAIS-Rb100) (1:1), from

high and low socioeconomic stratum (SES), and of both sexes (1:1) from the Chile’s metropolitan region. Brain

development was assessed by magnetic resonance imaging (MRI) and anthropometric measurements were made

applying standardized procedures. Results showed that, in general, no significant differences were observed

between absolute and adjusted brain parameters by body size. Differences in BV and HC can be more properly

attributed to differences in IQ and not to SES both in males and females. Independently of sex, BV was the only

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nding author. P.O. Box 138-11. Tel.: +56 2 678 1459; fax: +56 2 221 4030.

resses: [email protected], [email protected] (D.M. Ivanovic).

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D.M. Ivanovic et al. / Intelligence 32 (2004) 461–479462

brain parameter that contributed to explain IQ variance. These findings confirm the hypothesis that independently

of sex, BV and HC are positively and significantly associated with IQ.

D 2004 Elsevier Inc. All rights reserved.

Keywords: Intelligence; Education; Brain; Head; Corpus callosum; Magnetic resonance imaging; Image processing

1. Introduction

In the last years, using in vivo magnetic resonance imaging (MRI), several studies have been carried

out to understand the variability of human brain structure sizes during development as well as their

interrelationship with intelligence (Gignac, Vernon, & Wickett, 2002; Ivanovic, Almagia et al., 2000;

Ivanovic et al., 2002; Ivanovic, Leiva et al., 2000; Ivanovic, Forno, Castro, & Ivanovic, 2000; Lange,

Giedd, Castellanos, Vaituzis, & Rapoport, 1997; Nopoulos, Flaum, O’Leary, & Andreasen, 2000;

Vernon, Wickett, Bazana, & Stelmack, 2000; Wickett, Vernon, & Lee, 1994; Wickett, Vernon, & Lee,

2000).

A significant gender effect on intracranial volume has been described, male brains being larger

compared to females, and these differences are more evident in the cortex. Although the functional

significance of these differences is unclear, it is possible to postulate that this may represent the

differential effects of gonadal hormones during brain growth and development (Goldstein et al., 2001;

Lephart et al., 2001; Nopoulos et al., 2000).

Brain development during childhood and adolescence is characterized by both progressive

myelination and regressive pruning processes. Males have more prominent age-related gray matter

decreases and white matter volume and corpus callosal area increases compared with females. These

results suggest that there are age-related sex differences in brain maturational processes (De Bellis et al.,

2001).

Several authors have demonstrated a positive and significant association between brain size (or head

circumference) and intelligence concluding that the differences in human brain size are relevant in

explaining differences in intelligence. Related to this, genetic and environmental factors such as the

birthing process itself, nutrition at an early age, stress, and stimulation have also been involved in these

interrelationships (Andreasen et al., 1993; Botting, Powls, Cooke, & Marlow, 1998; Desch, Anderson, &

Snow, 1990; Diamond & Hopson, 1998; Eliot, 1999; Fisch, Bilek, Horrobin, & Chang, 1976; Gibson,

2002; Hack & Breslau, 1986; Hack et al., 1991; Ivanovic, Almagia et al., 2000; Ivanovic et al., 2002;

Ivanovic, Leiva et al., 2000; Ivanovic et al., 2003, in press; Ivanovic, Forno et al., 2000; Jensen &

Johnson, 1994; Johnson, 1991; MacLullich et al., 2002; Nelson & Deutschberger, 1970; Ounsted, Moar,

& Scott, 1988; Reiss, Abrams, Singer, Ross, & Denckla, 1996; Reynolds, Johnston, Dodge, DeKosky, &

Ganguli, 1999; Rushton, 2000; Rushton & Ankney, 1996, 2000; Strauss & Dietz, 1998; Susanne, 1979;

Van Valen, 1974; Vernon et al., 2000; Wickett et al., 2000; Willerman, Schultz, Rutledge, & Bigler,

1991). Studies carried out in monozygotic and dizygotic twins underline the impact of genetic factors on

both brain development and intellectual functions (Biondi et al., 1998; McGue & Bouchard, 1998; Mohr,

Knauth, Weisbrod, Stippich, & Sartor, 2001). However, this is controversial because some studies a few

of them in twins, have reported either significant or nonsignificant associations between these variables

(Anderson, 1999; Pennington et al., 2000; Schoenemann, Budinger, Sarich, & Wang, 2000; Teasdale &

D.M. Ivanovic et al. / Intelligence 32 (2004) 461–479 463

Pakkenberg, 1988; Tramo et al., 1998; Yeo, Turkheimer, Raz, & Bigler, 1987). Even more, animals

possess some of the attributes we label as dintelligentT in humans. dInsightT and dreasoningT have been

demonstrated in chimpanzees, monkeys, raccoons, rats, mice, elephants, ravens, and pigeons. In the rat,

the animal species best characterized psychologically and neuroanatomically, reasoning ability

correlates with other cognitive capacities and brain size (Anderson, 2000; Cozzi, Spagnoli, & Bruno,

2001).

The objectives of this study were to describe some brain development parameters in Chilean high

school graduates of both sexes from high and low socioeconomic stratum (SES) and to confirm the

hypothesis that independently of sex and SES, brain volume (BV) and head circumference (HC) are

positively and significantly associated with intellectual quotient (IQ).

2. Materials and methods

2.1. Subjects

The sample of 96 right-handed high school graduate students (mean age 18.0F0.9 years) born at

term was chosen from among 1817 school-age children, the total high school graduate population who

attended public and private schools in the richest and the poorest counties of the Chile’s metropolitan

region applying the UNICEF classification (United Nations International Children’s Fund, 1994).

School-age children selected in the sample had no history of alcoholism or antecedents or symptoms of

brain damage, intrapartum fetal asphyxia, hyperbilirubinemia, epilepsy, or heart disease and their

mother had no history of smoking, alcoholism, and drug intake before and during pregnancy. IQ

[Wechsler Intelligence Scale for Adults—Revised (WAIS-R)], SES, and sex were considered for

sample selection. Two groups of high school graduates were formed and compared: Group 1, high IQ

(z120 WAIS-R); and Group 2, low IQ (b100 WAIS-R). The total IQ of the school-age children from

Group 1 (125.4F5.5; n=47) was significantly higher than in those from Group 2 (91.4F6.8; n=49)

(Student’s t test=26.934; df=94; Pb.0001) and this was observed for verbal and nonverbal IQ (Ivanovic

et al., 2002). The same proportion of school-age children according to SES (high and low) (1:1) and

sex (1:1) were included in each IQ group (Ivanovic et al., 2002). This study was approved by the

Committee on Ethics in Studies in Humans of the Institute of Nutrition and Food Technology (INTA),

University of Chile. The subjects’ consent was obtained according to the norms for Human

Experimentation, Code of Ethics of the World Medical Association (Declaration of Helsinki) (The

World Medical Association, 1964).

2.2. Intellectual quotient

IQ (total, verbal, and nonverbal) was assessed in children by means of the WAIS-R adapted for

Chilean population and was carried out at the school (Hermosilla, 1986; Wechsler, 1981). WAIS-R

consists of a set of six verbal and five nonverbal subtests that are individually administered requiring

about 1.5 h and yield an age-corrected estimate of IQ. To avoid examiner bias, the WAIS-R was

administered separately to each child in quiet rooms by a team of educational psychologists specially

trained in this type of study. Before each item, the psychologist provided a clear explanation to each

child in order to clarify the problem to be solved.


2.3. Socioeconomic stratum

SES was determined with the Graffar-modified method adapted for Chilean urban population that

considers items such as schooling, job held by the head of the household, and characteristics of the

house (building materials, ownership status, water supply, sewerage, and ownership of durable goods)

(Alvarez, Muzzo, & Ivanovic, 1985). This scale classifies a population into six socioeconomic strata:

1=high; 2=medium–high; 3=medium; 4=medium–low; 5=low; and 6=extreme poverty. In the present

study, only high (1+2) (20.8% and 29.2% of the sample, respectively) and low (4+5) (45.8% and

4.2% of the sample, respectively) SESs were considered because they represent the extremes of SES

conditions. None of the school-age children belonged to the extreme poverty category.

2.4. Brain development study

Brain development was evaluated at the German Clinic of Santiago by MRI according to standardized

techniques (Willerman et al., 1991). Using the lowest margin of the cerebellum in a midsagittal view to

align the first axial (horizontal) MRI slice, 18 mixed-weighted images (spin-echo pulse sequence with a

TR of 2000 ms and a TE of 30 ms) were obtained from a Signa MRI General Electric unit with a field

strength of 1.5 T. All images were 5 mm thick and separated by 2.5 mm. Each image was 256�256

pixels with 256 levels of gray. The MRI tape was read into a VAS computed and the image analyzed

after removing identifying information. A trained specialist without foreknowledge of IQ or sex carried

out analyses. For each slice, a Roberts gradient traced the boundary of the scalp by outlining large-

intensity differences between adjacent pixels. All gray scale intensity values of b96 within this boundary

were converted to zero. This deleted the skull, most of the meninges, and the interhemispheric fissure;

other brain membranes were deleted manually with a cursor. The computer then counted all pixels with

nonzero gray scale values for brain size in each slice, their summed value serving as the index for overall

brain size. Cortex thickness data, BV, absolute and adjusted for effects of sex and body size (weight and

height), anteroposterior (APD) and biparietal diameters (BD), corpus callosum (CC) length absolute and

adjusted for effects of BV and sex, thickness of genu (CCGT), body (CCBT), and splenium (CCST),

absolute and adjusted for effect of CC length and sex (Frodl et al., 2001; Matano & Nakano, 1998), the

presence of neuronal migration disorders, qualitative and quantitative evaluation of white matter,

hippocampal volume, cortical and basal subarachnoid space, and ventricular system size were measured.

From the measurements of each subject in the different slices, the one whose diameter was the greatest

was used as representative to assess APD and BD. Thus, APD was measured in the axial slice in the

medial line from the frontal to the occipital bones under a standard protocol to assure standardized

measurements for all subjects. In the same slice, BD was obtained by means of a reading perpendicular to

APD. Brain parameters were adjusted using ANCOVA (Guilford & Fruchter 1984), despite the fact that

some authors had pointed out that, at present, there is no meaningful basis for the comparison of brain

sizes within and between racial groups and sexes; the control for body size across racial groups (and

sexes) is rendered difficult because bodies do not just differ only in height and weight (Peters et al., 1998).

2.5. Anthropometric measurements

The measurements of weight (W), height (H), and HC were made at school applying standardized

procedures, and all the instruments were verified before measuring each subject (Gibson, 1990). W was


measured in a platform beam balance with an accuracy of 100 g. H was determined with a vertical rod

with a measuring scale of 2 m high and with an accuracy of 0.5 cm. When measuring height, the subject

stood straight looking ahead with the Frankfurt plane horizontal and shoulders blades, buttocks, and

heels almost together touching measurement board, arms at sides, legs straight, knees together, and feet

flat (Gibson, 1990). Weight-for-age Z score (Z-W) and height-for-age Z score (Z-H) were not considered

since most of the sample was older than 18 years and the WHO tables (World Health Organization,

1980) cannot be applied. HC was measured with a narrow (less than 1 cm wide), flexible, nonstretch

tape made of fiber glass and with an accuracy of 0.1 cm. The head was steadied and the greatest HC

measured by placing the tape firmly round the frontal area just above the supraorbital ridges, passing it

round the head at the same level on each side and laying it over the maximum occipital prominence at

the back. HC was compared with the tables of Ivanovic, Olivares, Castro, and Ivanovic (1995), Nellhaus

(1968), Roche, Mukherjee, Guo, and Moore (1987), and Tanner (1984) and also was expressed as Z

score (Z-HC). Z-HC values are the same when applying the different tables because the correlation

coefficient between these patterns was .98 (Ivanovic et al., 1995). Despite of this, Z-HC values shown in

this study were those obtained comparing with the tables of Roche et al. (1987). HC absolute values

were adjusted for sex and body size (weight and height) through ANCOVA (Guilford & Fruchter, 1984).

2.6. Statistical analysis

Data were analyzed by means of ANCOVA (PROC GLM), ANOVA (PROC ANOVA), paired or

unpaired Student’s t test for comparison of means, correlation (PROC CORR), and multiple regression

(PROC GLM ERROR TYPE III) using the Statistical Analysis System (SAS) package (Guilford &

Fruchter 1984; SAS, Institute, 1990).

Table 1

Absolute and adjusted brain parameters and HC of Chilean high school graduates by sexa

Brain parameters and HC Absolute value Adjusted value Student’s t paired test

Males (47)

CC Length (mm) 71.5F4.8 71.8F1.8 NS

CCGT (mm) 11.4F1.7 11.1F0.3 NS

CCBT (mm) 6.2F0.9 6.2F0.4 NS

CCST (mm) 11.4F1.6 11.3F0.9 NS

BV (cm3) 1480.3F125.4 1470.3F39.7 NS

HC (cm) 55.7F1.7 55.6F0.8 NS

Females (49)

CC Length (mm) 70.8F4.9 70.5F1.3 NS

CCGT (mm) 10.9F1.6 11.1F0.3 NS

CCBT (mm) 6.5F0.8 6.1F0.3 **

CCST (mm) 11.3F1.6 11.3F0.9 NS

BV (cm3) 1394.4F88.9 1404.0F37.1 NS

HC (cm) 54.4F1.2 54.4F0.8 NS

NS=Not significantly different.a Results are expressed as meanFS.D. The number of cases is indicated between parentheses. CC: corpus callosum; CCGT:

genu thickness; CCBT=body thickness; CCST=splenium thickness; BV=brain volume.

** Pb.01.


3. Results

After adjustment for the effects of sex, body height, and body weight, adjusted values for BVand HC

did not differ significantly from absolute values both males and females, as is indicated in Table 1. The

adjustment by ANCOVA, for effects of sex and BV, revealed that adjusted CC length values did not

differ significantly from absolute values in both sexes. As regards to CCGT, CCBT, and CCST for

effects of sex and CC length showed that only in females, absolute CCBT was significantly higher than

adjusted CCBT (Pb.01). As there were practically no significant differences between absolute and

adjusted values for brain parameters, only absolute values are shown in this study.

Table 2 describes the absolute brain parameters, anthropometric measurements, IQ, and age by sex.

Males had absolute BV (Pb.001), BD (Pb.05), APD (Pb.05), absolute HC (Pb.0001), body W

(Pb.0001), and body H (Pb.0001) significantly higher compared with the females. Total, verbal, and

nonverbal IQ and age did not differ significantly by sex.

The absolute brain parameters, anthropometric measurements, IQ, and age by sex and SES are shown

in Table 3. With the exception of absolute CCBT that was significantly higher in males of the high SES

compared with their peers of the low SES (Pb.01), absolute CC parameters did not differ significantly

Table 2

Absolute brain parameters, anthropometric measurements, IQ, and age of Chilean high school graduates by sexa

Males (47) Females (49) Student’s t test

Absolute brain parameters

CC Length (mm) 71.5F4.8 70.8F4.9 0.746, NS

CCGT (mm) 11.4F1.7 10.9F1.6 1.318, NS

CCBT (mm) 6.2F0.9 6.5F0.8 1.580, NS

CCST (mm) 11.4F1.6 11.3F1.6 0.109, NS

BV (cm3) 1480.3F125.4 1394.4F88.9 3.886***

BD (mm) 132.4F6.6 129.6F6.2 2.133*

APD (mm) 164.6F6.6 161.8F5.6 2.267*

Absolute anthropometric measurements

HC (cm) 55.7F1.7 54.4F1.2 4.061****

Z-HC �0.12F1.32 �0.32F0.94 0.872, NS

Body W (k) 65.2F8.7 56.9F8.7 4.649****

Body H (cm) 170.9F6.3 159.4F6.1 9.156****

IQ

Total 108.0F18.8 108.1F17.7 0.039, NS

Verbal 108.0F19.5 107.6F18.0 0.085, NS

Nonverbal 107.0F16.3 107.9F16.7 0.260, NS

Age (years) 18.0F0.9 18.0F0.8 0.246, NS

NS=Not significantly different.a Results are expressed as meanFS.D. The number of cases is indicated between parentheses. CC=corpus callosum;

CCGT=genu thickness; CCBT=body thickness; CCST=splenium thickness; BV=brain volume; BD=biparietal diameter;

APD=anteroposterior diameter; HC=head circumference; Z-HC=head circumference for age Z score. W=weight; H=height.

* Pb.05.

*** Pb.001.

**** Pb.0001.

Table 3

Absolute brain parameters, anthropometric measurements, IQ, and age of Chilean high school graduates by sex and SESa

Males (47) Student’s t test Females (49) Student’s t test

High SES (24) Low SES (23) High SES (24) Low SES (25)


CC Length (mm) 72.2F4.7 70.8F4.8 0.990, NS 70.2F4.7 71.3F5.1 0.769, NS

CCGT (mm) 11.5F1.3 11.2F2.0 0.566, NS 10.6F1.5 11.2F1.6 1.462, NS

CCBT (mm) 6.5F0.7 5.8F0.9 2.926** 6.5F0.8 6.4F0.9 0.254, NS

CCST (mm) 11.7F1.4 11.0 F1.6 1.585, NS 11.3F1.8 11.3F1.4 0.029, NS

BV (cm3) 1486.2F116.6 1474.0F136.3 0.328, NS 1407.7F93.9 1381.6F83.7 1.027, NS

BD (mm) 130.9F5.6 134.1F7.3 1.659, NS 127.4F4.9 131.8F6.7 2.656*

APD (mm) 165.5F6.4 163.7F6.9 0.882, NS 162.3F6.3 161.2F5.1 0.694, NS


HC (cm) 55.8F1.6 55.5F1.8 0.658, NS 54.8F1.2 54.1F1.2 2.074*

Z-HC �0.01F1.24 �0.23F1.41 0.564, NS �0.08F0.97 �0.56F0.87 1.829 (t)

Body W (k) 66.6F9.5 63.7F7.8 1.155, NS 56.8F6.1 57.1F10.8 0.140, NS

Body H (cm) 173.3F5.8 168.5F5.9 2.851** 160.8F6.5 158.0F5.4 1.646, NS

IQ

Total 111.3F16.1 104.5F21.1 1.235, NS 110.4F16.2 105.9F19.1 0.890, NS

Verbal 111.6F17.0 104.2F21.6 1.303, NS 109.5F16.3 105.8F19.7 0.710, NS

Nonverbal 109.5F14.0 104.4F18.3 1.061, NS 110.4F16.2 105.5F17.1 1.020, NS

Age (years) 18.0F0.9 18.0F0.9 0.206, NS 17.9F0.6 18.0F0.9 0.576, NS

t=Tendency (PN.05 and b.10) (Pb.074); NS=not significantly different.a Results are expressed as meanFS.D. The number of cases is indicated between parentheses. CC=corpus callosum;


APD=anteroposterior diameter; HC=head circumference; Z-HC=head circumference for age Z score; W=weight; H=height.

* Pb.05.

** Pb.01.


by SES in both sexes. Independently of SES, absolute BVand APD did not differ significantly by SES in

both males and females, but BD values were significantly higher in females of the low SES compared

with those from the high SES (Pb.05). In both sexes, cortical thickness in the frontal, parietal, temporal,

and occipital lobules was near 4 mm, without significant differences when compared by sex and SES. As

regards to anthropometric measurements, males HC and Z-HC values did not differ significantly by SES

but in females, HC values were slight but significantly higher in those from the high SES than their peers

of the low SES (Pb.05). However, when expressed as Z-HC, differences were not significant in both

sexes. H values were significantly higher in males of the high SES than their peers of the low SES

(Pb.01); no significant differences were observed in the females. Total, verbal, and nonverbal IQ and

age did not differ significantly when analyzed by sex and SES.

Table 4 shows the absolute brain parameters, anthropometric measurements, IQ, and age by sex and

total IQ group. Independently of sex, school-age children with high total IQ exhibited an absolute BV

significantly higher than those of the low total IQ group. This means that males with high total IQ had an

absolute BV that was 133 cm3 greater than their peers of the low SES (Pb.0001), while in the females

this difference was 47.9 cm3 (Pb.05). Males with high total IQ presented an APD significantly higher

than their peers of the low total IQ group (Pb.01), and in the females only a tendency was observed

Table 4

Absolute brain parameters, anthropometric measurements, IQ, and age of Chilean high school graduates by sex and total IQ

groupa

Males (47) Student’s t test Females (49) Student’s t test

High total IQ

(23)

Low total IQ

(24)

High total IQ

(24)

Low total IQ

(25)


CC length (mm) 72.3F4.6 70.7F5.0 1.149, NS 71.6F5.6 69.9F4.0 1.226, NS

CCGT (mm) 11.7F1.9 11.0F1.5 1.323, NS 10.8F1.7 11.0F1.5 0.540, NS

CCBT (mm) 6.3F0.8 6.0F1.0 1.174, NS 6.4F0.8 6.5F0.9 0.439, NS

CCST (mm) 11.7F1.7 11.1F1.3 1.256, NS 11.2F1.8 11.5F1.4 0.679, NS

BV (cm3) 1548.2F86.7 1415.2F123.4 4.289**** 1418.8F92.4 1370.9F80.3 2.022*

BD (mm) 132.9F6.8 132.0F6.6 0.446, NS 129.4F6.1 129.8F6.6 0.211, NS

APD (mm) 167.2F5.6 162.1F6.6 2.824** 163.2F6.2 160.4F4.6 1.792 (t)


HC (cm) 56.5F1.4 54.8F1.6 3.917*** 54.8F1.2 54.0F1.2 2.208*

Z-HC 0.57F1.06 �0.78F1.22 4.053*** �0.01F0.84 �0.63F0.95 2.418*

Body W (k) 66.3F6.4 64.2F10.5 0.832, NS 56.4F6.1 57.4F10.8 0.390, NS

Body H (cm) 171.4F4.6 170.5F7.6 0.524, NS 161.2F4.9 157.6F6.7 2.175*

IQ

Total 125.7F5.7 91.0F7.6 17.884**** 125.0F5.4 91.9F6.1 20.090****

Verbal 126.5F5.9 90.2F7.6 18.273**** 124.6F5.6 91.4F7.5 17.656****

Nonverbal 121.5F7.5 93.2F8.2 12.325**** 122.3F9.7 94.1F7.7 11.200****

Age (years) 17.6F0.4 18.4F1.1 3.388** 17.6F0.4 18.4F0.9 3.720***

t=tendency (PN.05b.10 years) (Pb.081); NS=not significantly different.a Results are expressed as meanFS.D. The number of cases is indicated between parentheses. CC=corpus callosum;


APD=anteroposterior diameter; HC=head circumference; Z-HC=head circumference for age Z score. W=weight; H=height.

* Pb.05.

** Pb.01.

*** Pb.01.

**** Pb.0001.


(Pb.081). In both sexes, cortex thickness in the frontal, parietal, temporal, and occipital lobules was near

4 mm without significant differences when compared by sex and total IQ group. In the low SES, two

males who had low total IQs had abnormal amounts of white matter, five school-age children (four males

and one female) had abnormal basal subarachnoid spaces and ventricular system size, and one case had

slight, nonspecific diffuse brain atrophy. Despite the fact that these abnormalities affected mainly males,

no association was found both SES and total IQ. Independently of sex, school-age children with total

high IQ registered an absolute HC and Z-HC values significantly higher compared with their peers with

low total IQ. Males with high total IQ presented an absolute HC 1.7 cm greater than the low total IQ

group (Pb.001) while in females this difference was 0.8 cm (Pb.05). When expressing as Z-HC, males

with high total IQ had values 1.35 S.D. greater than the low total IQ group (Pb.001), and in females this

difference was 0.62 S.D. (Pb.05). According to body H, only females with high total IQ had values

significantly higher compared with the low total IQ group (Pb.05); in males, no significant difference

was observed. Significant differences in total, verbal, and nonverbal IQ between total IQ groups are


observed in both males and females (Pb.0001). School-age children with low total IQ were significantly

older than their peers from the high total IQ group both in males (Pb.01) and in females (Pb.001). This

can be explained since the repetition rate was significantly higher in school-age children with low total

IQ group (0.67F0.72 years; n=49) compared with those of the high total IQ group (0.07F0.25 years;

n=47) (Student’s t test=5.441; df=94; Pb.0001), and this was observed both in males (Pb.01) and in

females (Pb.0001).

Figs. 1 and 2 are examples of T1-weighted midsagittal MRIs of the brains of males and females with

high (left) and low (right) IQs, respectively. In the T1-weighted midsagittal MRI, it is evident that the

brain size of school-age children is greater when IQ is higher compared with those with low IQ. Despite

the significant differences in brain size, midsagittal MRI projections did not show greater changes in the

CC length, cerebral convolutions, and basal subarachnoid space as indicated in Table 4.

Table 5 summarizes the Pearson correlation coefficients between total, verbal and nonverbal IQ, brain

parameters, HC, age, and SES by sex. A positive and significant correlation was observed between total,

verbal, and nonverbal IQ with absolute BV, HC, and APD in both males and females, although in

females, only a tendency was observed between verbal IQ and APD. Total IQ–BV correlation was .551

(Pb.0001) in males and .370 (Pb.01) in females, and total IQ–HC correlation was .499 (Pb.001) and

.397 (Pb.01) in males and females, respectively. In males, a positive and significant low correlation was

observed between total, verbal, and nonverbal IQ with CCBT and nonverbal IQ correlated also with

CCST. In both sexes, absolute BV positively and significantly correlated with HC, BD, and APD. A high

correlation was observed between absolute HC and BV (r=.867, Pb.0001; and r=.720, Pb.0001, for

males and females, respectively) and between adjusted values (r=.978, Pb.0001; and r=.969, Pb.0001,

for males and females, respectively). In males, absolute BV positively and significantly correlated also

with CC length while only a tendency was observed in females.

Fig. 1. Example of T1-weighted midsagittal MRI showing the brain of males with high IQ (left; total IQ=134, HC=57.4 cm, Z-

HC=1.64, absolute BV=1592.53 cm3, and age=17 years 8 months) and low IQ (right; total IQ=80, HC=50.8 cm, Z-HC=�2.88,

absolute BV=1119.53 cm3, and age=19 years). IQ=intellectual quotient; HC=head circumference; Z-HC=head circumference

for age Z score; BV=brain volume.

Fig. 2. Example of T1-weighted midsagittal MRI showing the brain of females with high IQ (left; total IQ=136, HC=57.0 cm,

Z-HC=2.39, absolute BV=1574.29 cm3, and age=17 years 1 month) and low IQ (right; total IQ=88, HC=51.6 cm, Z-

HC=�2.34, absolute BV=1322.74 cm3, and age=18 years 7 months). IQ=intellectual quotient; HC=head circumference; Z-

HC=head circumference for age Z score; BV=brain volume.


Multiple regression analysis between BV (dependent variable) and CC, CCGT, CCBT, CCST, BD,

and APD (independent variables) (Table 6) revealed that APD and BD were the brain parameters with

the greatest explanatory power for children’s BV variance both in males (r2=.650) and in females

(r2=.519). In both sexes, APD accounts for a significant proportion of the variance in BV, 87.2% and

76.7% in males and females, respectively. BD accounted for a significant but lower proportion of the

variance, greater in females (23.3%) than in males (12.8%).

Table 7 shows the multiple regression analysis between IQ (dependent variable) and BV, CC, APD,

and sex (independent variables). Independently of sex, BV was the only brain parameter that contributed

to explain total IQ (r2=.248), verbal IQ (r2=.227), and nonverbal IQ variances (r2=.237).

4. Discussion

The results of this study show that in this sample of Chilean high school graduates, absolute and

adjusted values for brain parameters did not differ significantly both males and females, with the only

exception of CCBT in females. This means that the effects of sex and body size (height and weight) for

both BV and HC were not significant. Similar results were observed for absolute CC length adjusted for

sex and BV and for effects of sex and CC length for absolute CCGT and CCST.

In our study, when we evaluated sexual dimorphism in brain structures absolute BV, BD, APD, and

the anthropometric measurements such as absolute HC, body W and body H were significantly higher in

males than in females. With the exception of H in males and BD and HC but not Z-HC in females, no

significant differences were observed related to SES. MRI has been used to evaluate sex differences in

Table 5

Pearson correlation coefficients between IQ, absolute brain parameters, Z-HC, age, and SESa

IQ VIQ N-VIQ BV HC CC CCGT CCBT CCST BD APD AGE SES

Males (47)

IQ –

VIQ .986**** –

N-VIQ .963**** .906**** –

BV .551**** .552**** .515*** –

HC .499*** .522*** .425** .867**** –

CC .157, NS .177, NS .124, NS .421** .440** –

CCGT .209, NS .205, NS .207, NS .215, NS .202, NS .061, NS –

CCBT .322* .291* .352* .136, NS .015, NS .013, NS .394** –

CCST .261 (t) .203, NS .343* .127, NS .179, NS .450** .106, NS .447** –

BD �.058, NS �.041, NS �.090, NS .413** .320* .126, NS .175, NS �.004, NS .025, NS –

APD .470*** .486*** .411** .745**** .658**** .575**** .289* .125, NS .062, NS .179, NS –

AGE �.446** �.478*** �.375**** �.361**** �.337* �.118, NS �.210, NS �.066, NS .152, NS .270 (t) �.387**** –

SES .182, NS .192, NS .157, NS .049, NS .097, NS .146, NS .084, NS .402**** .231, NS .241, NS .131, NS .031, NS –

Females (49)

IQ –

VIQ .968**** –

N-VIQ .930**** .812**** –

BV .370** .331* .383** –

HC .397** .383** .364* .720**** –

CC .175, NS .113, NS .244 (t) .270 (t) .270 (t) –

CCGT �.015, NS �.045, NS .019, NS .148, NS .141, NS .272 (t) –

CCBT �.016, NS �.037, NS .002, NS .146, NS .086, NS .375** .238, NS –

CCST �.042, NS �.037, NS �.058, NS .050, NS .210, NS .584**** .338* .596**** –

BD �.034, NS �.017, NS �.075, NS .385** .224, NS �.147, NS .249 (t) .036, NS �.123, NS –

APD .334* .249 (t) .423** .622**** .605**** .610**** .243 (t) .259 (t) .306* .069, NS –

AGE �.553**** �.591**** �.421** �.191, NS �.222, NS .054, NS .215, NS .200, NS .097, NS .023, NS �.043, NS –

SES .128, NS .103, NS .147, NS .149, NS .272(t) .111, NS .208, NS .037, NS .004, NS �.359* .101, NS .153, NS –

t=tendency (PN.05b.10 years).a The number of cases is indicated between parentheses. IQ=total intellectual quotient; VIQ=verbal intellectual quotient; N-VIQ=nonverbal intellectual

quotient; BV=brain volume; HC=head circumference; CC=corpus callosum length; CCGT=genu thickness; CCBT=body thickness; CCST=splenium thickness;

BD=biparietal diameter; APD=anteroposterior diameter; SES=socioeconomic strata.

* Pb.05.

** Pb.01.

*** Pb.001.

**** Pb.0001.

D.M

.Iva

novic

etal./Intellig

ence

32(2004)461–479

471

Table 6

Multiple regression analysis table (Statistical Analysis System: PROC GLM Error type III) between school-age children’s BV

(dependent variable) and most relevant brain parameters (independent variables) by sexa

Parameter Estimate T for HO:

parameter = 0

PrN[T] Standard error

of estimate

Partial r2 Percentage of the

explained variance

Males

Intercept �1504.425909 �4.23 0.0001 355.8123257 – –

CC �2.734262 �0.72 0.4730 3.7743326 – –

CCGT �5.299503 �0.67 0.5081 7.9352897 – –

CCBT 2.592629 0.15 0.8785 16.8479638 – –

CCST 9.581160 0.90 0.3710 10.5885857 – –

BD 5.652066 3.11 0.0035 1.8187651 .083 12.8

APD 14.377398 5.85 0.0001 2.4558151 .567 87.2

Model r2=.650; root MSE (standard deviation of the dependent variable)=79.498565; model F value=12.40; Pb.0001

Females

Intercept �774.2356894 �2.35 0.0236 329.5865560

CC �0.1639400 �0.06 0.9561 2.9636962

CCGT �3.7165585 �0.55 0.5850 6.7528346

CCBT 5.4907364 0.37 0.7098 14.6560267

CCST �5.8922408 �0.67 0.5062 8.7884390

BD 4.8369945 2.92 0.0056 1.6571488 .121 23.3

APD 10.0453106 4.61 0.0001 2.1813053 .398 76.7


a CC=corpus callosum; CCGT=genu thickness; CCBT=body thickness; CCST=splenium thickness; BD=biparietal

diameter; APD=anteroposterior diameter.


brain morphology and a significant gender effect on BV, males being larger than females (Blatter et al.,

1995; Nopoulos et al., 2000; Raz et al., 1997; Skullerud, 1985). In brain MRI of healthy children and

adolescents, males had a 9% larger cerebral volume than females (Giedd et al., 1999; Giedd, Castellanos,

Rajapakse, Vaituzis, & Rapoport, 1997). Our findings are comparable since males had an absolute BV

approximately 6% larger than females.

Along the same lines, males in our study had absolute HCs significantly higher (2.3%) than females,

and this difference is in agreement with our previous results and with those of other authors (Ivanovic et

al., 1995; Nellhaus, 1968; Roche et al. 1987; Tanner, 1984; Weaver & Cristian, 1980). However, when

expressed as Z-HC according to sex and age, differences by sex were not significant. Recent findings

pointed out that male newborns had significantly larger head/chest proportions, suggesting that they may

have a greater metabolic demand related to brain size (Nagy, Loveland, Orvos, & Molnar, 2001).

In this study, with the exception of CCBT, males showed higher absolute values for CC length,

CCGT, and CCST compared with the females, but differences were not significant. Our results are in

agreement with those of Pozzilli et al. (1994), who did not find significant differences related to sex in

absolute CC area or the callosal subregions. Significant Sex�Age interactions were seen for CC area,

specifically, males had more prominent age-related CC area increases compared with females (DeBellis

et al., 2001).

During the morphologic development of the CC during childhood and adolescence, the character-

ization of the normal developmental pattern of the CC is hindered by the enormous variability of its size

(Giedd et al., 1999). Other investigators had informed that in the adult age range (22–71 years), men had

Table 7

Multiple regression analysis table (statistical analysis system: PROC GLM error type III) between school-age children’s IQ

(dependent variable) and most relevant brain parameters and sex (independent variables)a

Parameter Estimate T for HO: parameter=0 PrN[T] Standard error

of estimate

Total IQ

Intercept �58.36111844 �1.27 0.2072 45.93705359

Sex

Males �6.12249571 �1.69 0.0954 3.63319307

Females 0.00000000 – – –

BV 0.05933763 2.76 0.0071 0.02153680

CC �0.35544460 �0.82 0.4131 0.43231088

CCBT 1.99888701 1.01 0.3166 1.98500980

APD 0.59325661 1.35 0.1800 0.43905797


Verbal IQ

Intercept �47.88759811 �1.00 0.3203 47.91645981

Sex

Males �5.84917872 �1.54 0.1262 3.78974567

Females 0.00000000 – – –

BV 0.06307471 2.81 0.0061 0.02246482

CC �0.37440675 �0.83 0.4086 0.45093896

CCBT 1.61525190 0.78 0.4374 2.07054295

APD 0.51690249 1.13 0.2620 0.45797677


Nonverbal IQ

Intercept �50.82673967 �1.21 0.2276 41.83564886

Sex

Males �5.81887998 �1.76 0.0820 3.30881016

Females 0.00000000 – – –

BV 0.04612230 2.35 0.0209 0.01961393

CC �0.25505446 �0.65 0.5188 0.39371281

CCBT 2.09599848 1.16 0.2493 1.80778188

APD 0.61141342 1.53 0.1298 0.39985749


a BV=brain volume; CC=corpus callosum; CCBT=body thickness; APD=anteroposterior diameter.


larger brains and CC than women, such as in our study (Matano & Nakano, 1998; Sullivan,

Rosenbloom, Desmond, & Pfefferbaum, 2001). On the other hand, the size of the CC and the body of the

CC consistently decrease in size with age, and the cross-sectional areas of the genu, splenium, and CC,

overall, do not vary significantly with respect to sex such as in our study (Hopper, Patel, Cann, Wilcox,

& Schaeffer, 1994). With the exception of the absolute CCBT that was significantly lower in males from

the low SES, CC parameters did not differ by SES. A recent cross-sectional study of pregnant women

demonstrated that female fetuses had statistically significantly thicker CC than males for each gestational

age. However, the length and width of the CC during gestation did not differ significantly between the

sexes suggesting sex dimorphism of human CC and raising the possibility that prenatal sex hormones

may play later a role in determining callosal development (Achiron, Lipitz, & Achiron, 2001).


Studies carried out in animals provided controversial evidence about sexual dimorphism of brain

structures. The whole BV and the size of the entire CC of young adult female rhesus monkeys are

approximately 20% smaller than those of young adult males and the area of the splenium of the CC is

larger in female monkeys (Franklin et al., 2000). Other findings in dogs showed that the anterior half, the

posterior half, the posterior fifth, and the total CC were significantly greater in absolute area in males

than in females (Aydinlgoglu et al., 2000). However, another study performed in rats, rabbits, cats, dogs,

horses, cows, and humans revealed no sex differences in callosal size in any of the species (Olivares,

Michalland, & Aboitiz, 2000).

The high correlation observed in the present study between HC and BV both absolute and adjusted

values is in agreement with findings from other authors and confirms that HC is the anthropometric

indicator both brain development and nutritional background (Bartholomeusz, Courchesne, & Karns,

2002; Vernon et al., 2000). As it turns out, the assumption that external head size can serve as a proxy for

BV is not unreasonable (Vernon et al., 2000), correlations between the two being approximately .60 in

adults (Hoadley, 1929; Tan et al., 1999; Wickett et al., 1994, 2000) and above .90 in infants and children

(Bray, Shields, Wolcott, & Madsen, 1969; Dobbing & Sands, 1978; Lemons, Schreiner, & Gresham,

1981). Our previous results demonstrated that BV accounted for 78.1% of HC variance (Ivanovic et al.,

in press) but in the present study APD was the brain parameter that explained most part of BV variance

and this is in agreement with the findings of other investigators (Willerman et al., 1991).

In our study, school-age children with high IQ had a significantly higher BV and HC, despite the fact

that these were younger than those with low IQ. School-age children of both IQ groups belonged to the

same grade; however, low total IQ group presented school delay due to a significantly higher repetition

rate compared with their peers with high total IQ. We described previously that in this sample,

independently of SES, high school graduates with similar IQ had similar nutritional brain development

and educational parameters and this was observed for both sexes. Maternal IQ, BV, and severe

undernutrition during the first year of life were the independent variables with the greatest explanatory

power for child IQ variance (r2=.707) without interaction with age, sex, or SES. Child IQ (Pb.0001) was

the only independent variable that explained scholastic achievement variance (r2=.848) and Academic

Aptitude Test (the baccalaureate examination for university admission of national covering in Chile)

variance (r2=.876) without interaction with age, sex, or SES, and this was observed both males and

females (Ivanovic, Almagia et al., 2000; Ivanovic et al., 2002).

As already stated, several authors have found a positive and significant association between BVor HC

and intelligence, and these findings are in agreement with our results since BV is the only brain

parameter that contributed to explain IQ variance; in this respect, genetic and environmental factors had

been involved in these interrelationships (Andreasen et al. 1993; Biondi et al., 1998; Botting et al. 1998;

Desch et al. 1990; Diamond & Hopson, 1998; Eliot, 1999; Fisch et al. 1976; Gibson, 2002; Gignac et al.

2002; Hack & Breslau, 1986; Hack et al. 1991; Ivanovic, Almagia et al., 2000; Ivanovic et al., 2002;

Ivanovic, Leiva et al., 2000; Ivanovic, Forno et al., 2000; Jensen & Johnson, 1994; Johnson, 1991;

McGue & Bouchard, 1998; MacLullich et al. 2002; Mohr et al. 2001; Nelson & Deutschberger, 1970;

Ounsted et al. 1988; Reiss et al. 1996; Reynolds et al., 1999; Rushton, 2000; Rushton & Ankney, 1996,

2000; Strauss & Dietz, 1998; Susanne, 1979; Van Valen, 1974; Vernon et al., 2000; Wickett et al., 2000;

Willerman et al., 1991). However, some studies, many of them in twins, have reported significant and

nonsignificant associations between these variables (Anderson, 1999; Pennington et al., 2000;

Schoenemann et al., 2000; Teasdale & Pakkenberg, 1988; Tramo et al., 1998; Yeo et al., 1987). Jensen

and Sinha (1993) predicted that there is no question that BV and IQ are significantly and positively


correlated, with the best estimate being a correlation of approximately .40. However, males of the present

study showed a correlation above .50. BV and HC were highly correlated and so a similar correlation

was observed between BV and IQ and HC and IQ, total, verbal, and nonverbal. IQ also correlated with

APD probably because this is the most relevant brain parameter correlated with BV and that explains

most part of BV variance. The correlation between BVand IQ does not appear limited to adults, and this

should come as no surprise because 92% of adult brain weight is achieved by age 6 (Ho, Roessmann,

Straumfjord, & Monroe, 1980).

In this study no significant correlations were found between SES with IQ, BV, and HC since children

were paired by IQ in each socioeconomic strata and in both sexes. In consequence, the present study

reveals that differences in BV and HC can be more properly attributed to differences in IQ and not to

SES. This means that independently of SES, high school graduates with similar IQ have similar brain

development parameters both in males and in females. Many factors contribute to the size of the brain,

and at least one of them, the number of neurons, is the most obvious factor affecting the overall size and

directly related to intelligence. In fact, Pakkenberg and Gundersen (1997) have shown that larger brains

have more neurons, and it is possible that this increase in neuronal number benefits both cognitive

capacity and complexity through a greater number of synaptic connections (Wickett et al., 2000).

In summary, the results of the present study confirm our hypothesis that independently of sex, BVand

HC are positively and significantly associated with IQ. However, these interrelationships do not have a

direct cause–effect relationship since complex interactions are established during the lifetime of the

individuals. Some authors have underlined that there will no doubt be many exciting attempts over the

next several years to determine what it is about a larger brain that is beneficial to cognitive processing.

Attention will turn to what it is about intelligence that is predicted by BV since this aspect has been

almost completely ignored in the literature (Wickett et al., 2000). Thus, further research is needed to

provide new evidence to this complex interactions.

Acknowledgements

Authors are very gratefully to the Ministry of Education of Chile for all the facilities given to carry out

this research; to Dr. Oscar Brunser MD for helpful comments and suggestions; to Ms. Nora Dıaz and Ms.

Barbara Leyton for their statistical assistance; to Messrs. Ivan Soza, Ricardo Castillo, and Claudio

Canete for the operation of the MRI equipment at the German Clinic of Santiago, Chile; and to Mr.

Leopoldo Salgado for photographic work. Supported in part by Grant 1961032 from the National Fund

for Scientific and Technologic Development (FONDECYT), Grant 024/1997 from the University of

Chile, Postgradest Department, and Grant SOC 01/13-2 from the Research and Development

Department (DID), University of Chile.

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Brain development parameters and intelligence in Chilean high school graduates

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