close

Вход

Забыли?

вход по аккаунту

?

Fetal and infant head circumference sexual dimorphism in primates.

код для вставкиСкачать
AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 126:97–110 (2005)
Fetal and Infant Head Circumference Sexual
Dimorphism in Primates
Tracey H. Joffe,1* Alice F. Tarantal,2 Karen Rice,3 Michelle Leland,3 Ann-Kathrin Oerke,4
Charles Rodeck,5 Michael Geary,5 Peter Hindmarsh,6 Jonathan C.K. Wells,1 and Leslie C. Aiello7
1
Institute of Child Health, MRC Childhood Nutrition Research Center, University College London, London WC1N
1EH, UK
2
California National Primate Research Center and Department of Pediatrics, University of California,
Davis, California 95616-8542
3
Southwest Foundation for Biomedical Research, San Antonia, Texas 78227-5301
4
Department of Reproductive Biology, German Primate Center, 37077 Göttingen, Germany
5
Department of Obstetrics and Gynaecology, University College London, London WC1E 6 BT, UK
6
London Center for Paediatric Endocrinology, University College London, London WC1E 6 BT, UK
7
Department of Anthropology, University College London, London WC1E 6 BT, UK
KEY WORDS
human; rhesus monkey; baboon; marmoset; encephalization
ABSTRACT
Studies have shown that after controlling
for the effects of body size on brain size, the brains of adult
humans, rhesus monkeys, and chimpanzees differ in relative size, where males have a greater volume of cerebral
tissue than females. We assess whether head circumference sexual dimorphism is present during early development by evaluating sex differences in relative head circumference in living fetuses and infants within the first
year of life. Head circumference is used as a proxy for
brain size in the fetus and infant. Femur length is used as
a proxy for body length in the fetus. Ultrasonography was
used to obtain fetal measures, and anthropometry was
used to obtain postnatal measures in humans, rhesus
monkeys, baboons, and common marmosets. We show that
statistically significant but low levels of head circumference sexual dimorphism are present in humans, rhesus
monkeys, and baboons in early life. On average, males
have head circumferences about 2% larger than females of
comparable femur/body length in humans, rhesus monkeys, and baboons. No evidence for head circumference
sexual dimorphism in the common marmoset was found.
Dimorphism was present across all body size ranges. We
suggest that head circumference sexual dimorphism
emerges largely postnatally and increases throughout
maturation, particularly in humans who reach adult dimorphism values greater than the monkeys. We suggest
that brain dimorphism is not likely to impose an additional energetic burden to the gestating or lactating
mother. Finally, some of the problems with ascribing functional significance to brain size sexual dimorphism are
discussed, and the energetic implications for brain size
sexual dimorphism in infancy are assessed. Am J Phys
Anthropol 126:97–110, 2005. © 2004 Wiley-Liss, Inc.
An absolute difference in brain size between human males and females has been documented by
several researchers. Ankney (1992), using autopsy
data on adults (Ho et al., 1980a,b), showed that sex
differences persist in brain size after controlling for
the effects of body size. Sex differences in relative
brain size in the living individual were also found
using MRI (Andreasen, 1993; Filipek et al., 1994;
Pfefferbaum et al., 1994; Gur et al., 1991; Harvey et
al., 1994; Resnick, 1995; Willerman et al., 1991;
Blatter et al., 1995). In addition, Falk et al. (1999)
demonstrated that relative brain size is subject to
sexual dimorphism in adult rhesus macaques and
humans. Based on postmortem data, both species
display similar levels of sexual dimorphism in relative brain size, with males having brains about 8%
(in rhesus monkeys) to 10% (in humans) larger than
females. Herndon et al. (1999) also documented
brain size sexual dimorphism in chimpanzees from
necropsy records of individuals between birth and
59.4 years of age. However, these authors show that
brain weight declines with age in chimpanzees. This
is also the case for humans.
Dekaban and Sadowsky (1978) and Hartmann et
al. (1994) reported a trend toward lower brain
weight with increasing age in humans, with an increase in the rate of decline at about 50 years. In
general, brains of 70 – 80-year-olds weigh about 7%
less than those of 20-year-olds of comparable body
weight (Dekaban and Sadowsky, 1978; Hartmann et
©
2004 WILEY-LISS, INC.
*Correspondence to: Tracey H. Joffe, Department of Family Medicine
and Community Health, Tufts University School of Medicine, 136 Harrison Ave., Posner 4, Boston, MA 02111. E-mail: tracey.joffe@tufts.edu
Received 2 October 2002; accepted 19 January 2004.
DOI 10.1002/ajpa.20035
Published online 7 October 2004 in Wiley InterScience (www.
interscience.wiley.com).
98
TRACEY H. JOFFE ET AL.
al., 1994; Pakkenberg and Voigt, 1964; Chrzanowska and Beben, 1973). From ages 26 – 80, brain
weight declines by about 2 g per year (Ho et al.,
1980a,b). This loss in brain weight is largely due to
the loss of neuronal somata, neurophil, or white
matter (Herndon et al., 1999) and water (Dobbing
and Sands, 1970). MRI studies show that an overall
decrease in brain volume following the late teens is
associated with the replacement of gray matter with
cerebrospinal fluid (CSF) (Gur et al., 1991; Jernigan
et al., 1991; Resnick, 1995). As a result, variations in
the rates of brain weight loss and age make accurate
assessment of adult brain weight sexual dimorphism problematic. This is particularly true for
women, since levels of brain weight loss may be
higher in association with estrogen depletion during
menopause (Namba and Sokoloff, 1984; Nehlig et
al., 1985; Maki and Resnick, 2001).
In addition to adults, brain size sexual dimorphism was also found in infants, where autopsy
brain weights, matched by stature, are greater in
males (Dekaban and Sadowsky, 1978; Pakkenberg
and Voigt, 1964; Voigt and Pakkenberg, 1983). Autopsy materials are, however, subject to a number of
influences that may alter brain/body weight relationships in the individual. Many people presented
for autopsy were ill or had died as a result of trauma.
Body wasting is common in subjects following longterm illness. In addition, dehydration or edema may
be marked in individuals as a function of illness or
the time elapsed between death and autopsy. Moreover, the time delay between death and autopsy may
influence the degree of brain autolysis, impacting
brain weight. Hypoxia also has an effect on brain
weight, as it often leads to brain hematoma and
engorgement, while blood loss may influence brain
weight. Ideally, brain and body size relationships
should be assessed in the young living subject, and
relative brain size should be calculated as a function
of body length, rather than body weight, as length
tends to be influenced less by environmental insult
(Tanner, 1978).
Deacon (1989) argued that relative brain size (encephalization) in the adult is the product of brain/
body growth patterns throughout ontogeny. Adult
brain size dimorphism may relate either to dimorphism throughout ontogeny or to dimorphism onset
in later life. Equally, it may vary as brain and body
growth rates vary across development. Here we
evaluate whether head circumference/body size relationships in fetal and young infant human and
nonhuman primates exhibit sexual dimorphism.
Head circumference is strongly correlated with
brain weight in early life (Cooke et al., 1977), and is
therefore used here as a proxy for brain size. Femur
length in early life is strongly correlated with body
length (Fazekas and Kósa, 1978), and is used here as
a proxy for prenatal body size. The species assessed
here include humans, rhesus monkeys (Macaca mulatta), baboons (Papio sp.), and marmosets (Callithrix jacchus).
MATERIALS AND METHODS
Head circumference is considered a good and reliable indicator of brain weight (Cooke et al., 1977;
Epstein and Epstein, 1978; Fujimura and Seryu,
1977; McLennan et al., 1983) and intracranial volume (Bray et al., 1969; Buda et al., 1975) during the
prenatal period and first year of life (Bray et al.,
1969; Dobbing, 1970), where about 96% of the variation in postmortem brain weight is explained by
head circumference (Cooke et al., 1977). The linear
relationship between postmortem brain weight and
head circumference in infants (ranging in age from
18 – 43 weeks of gestation) is described by the relationship:
log10 BW ⫽ 3.003 * log10 HC ⫺ 2.0306
(1)
where BW is brain weight in grams, and HC is head
circumference in centimeters (R ⫽ 0.981, SE ⫽
0.097, N ⫽ 422) (Cooke et al., 1977).
Because head circumference is closely correlated
with brain weight, it is routinely measured antenatally using ultrasound. Previous work showed this
measurement to be reproducible throughout pregnancy (Nicolini et al., 1986). The same ultrasound
techniques are used for measuring head circumference in humans and nonhuman primates. Ultrasound head circumference in humans and nonhuman primates is generally measured along the
occipito-bregmatic plane in order to reflect head size
independently of head shape (Doubilet and Greenes,
1984). After ultrasound measures of occipito-frontal
diameter and biparietal diameter are taken, measures of head circumference are estimated using the
formula for an ellipse:
HC ⫽ 3.14 √(BPD2 ⫹ OFD2)/2
(2)
where HC is head circumference in mm, BPD is
biparietal diameter in mm, and OFD is occipitofrontal diameter in mm. The same methods for humans and nonhuman primates are used.
Both head circumference and femur length can be
measured after 12 postconceptional weeks within an
error margin of 1 mm (Guihard-Costa and Larroche,
1995). Antenatal femur length is measured routinely with ultrasound in humans and nonhuman
primates in order to assess longitudinal growth in
utero (Campbell and Thoms, 1977; Sabbagha, 1978;
Little and Campbell, 1982; De Vore and Platt, 1987;
Meire, 1981). Previous work showed this measurement to be reproducible throughout pregnancy
(Nicolini et al., 1986). It should be noted, however,
that only ossified bone is detected ultrasonically,
and femoral epiphyses are therefore excluded from
femur length measures in humans and nonhuman
primates. Even though both femur length and body
length are subject to sexual dimorphism in humans
in early life, femur length is a good proxy for body
length in utero, and can be used to estimate body
length effectively. According to Fazekas and Kósa
(1978), the underlying relationship between fetal
99
HEAD CIRCUMFERENCE SEXUAL DIMORPHISM
TABLE 1. Means, standard deviations, and sample sizes for males and females in human sample1
Males
Mean
Variable
Head circumference (mm)
Ultrasound 2 (16–28 GW)
Ultrasound 3 (28–37 GW)
Birth (34–43 GW)
6 months (21–33 weeks)
12 months (49–58 weeks)
Femur/body length (mm)
Ultrasound 2 (16–28 GW)
Ultrasound 3 (28–37 GW)
Birth (34–43 GW)
6 months (21–33 weeks)
12 months (49–58 weeks)
Age (weeks)
Ultrasound 2 (16–28 GW)
Ultrasound 3 (28–37 GW)
Birth (34–43 GW)
6 months (21–33 weeks)
12 months (49–58 weeks)
SD
Females
n
Mean
SD
n
%
difference
180.0
362.0
348.0
441.0
471.0
12.1
13.5
15.4
11.9
12.1
749
604
743
485
170
176
298
342
430
460
11.5
14.5
14.8
11.7
12.4
704
568
701
430
460
2.18*
1.3*
1.85*
2.59*
2.44*
32.7
61.9
504.0
682.0
766.0
2.92
3.08
25.7
23.5
27.3
739
681
737
485
169
32.6
62.2
495
663
748
2.73
3.31
24.3
29.1
27.4
690
652
698
440
181
0.25
⫺0.39
1.7*
2.83*
2.4*
0.99
1.21
1.55
1.44
1.02
749
604
743
485
160
0.98
1.29
1.60
1.55
0.72
704
568
701
430
181
0.15
⫺0.53
0.3
⫺0.08
0.15
20.27
32.15
39.55
25.58
52.10
20.24
32.32
39.43
25.60
52.02
1
Femur lengths at ultrasound examinations 2 and 3. GW, gestation weeks. Some individuals did not have both head circumference
and femur length measures.
%difference, mean difference as a percent of female mean.
* P ⱕ 0.0001, based on independent-samples t-tests comparing mean size between sexes.
body length and fetal femur length does not differ
significantly between the sexes, and in both sexes
body length can be estimated from the following
equation, where
Total body length (cm) ⫽ femur length (cm) * 6.44
⫹ 4.51 (3)
(R ⫽ 0.999, N ⫽ 138)
The measures of Fazekas and Kósa (1978) are
based on skeletal materials and include only the
femoral diaphyses, and can therefore be reliably
used to estimate body length from ultrasound femur
measures that also include only the ossified diaphyseal portion of the femur.
In the human and nonhuman primate neonate
and infant, postnatal head circumference measures
are taken with a tape measure, at the maximum
perimeter of the head (Meredith, 1971). Head circumference measurement error is usually no greater
than about 1 mm. Unlike ultrasound, this measure
includes the thickness of the scalp, which at term is
about 8 –10 mm in human neonates (Fescina and
Ucieda, 1980; Fescina and Martell, 1983). It is also
influenced by edema and hair thickness. Therefore,
fetal and infant measures are analyzed separately
here.
Data
Human data. The human data analyzed here
were collected by Dr. Michael Geary, Dr. Peter Hindmarsh, and Prof. Charles Rodeck as part of a longitudinal study of fetal and infant growth carried out
at University College London Hospitals between
1996 –1999 (see Hindmarsh et al., 2002 for further
details). Biometric measures were taken longitudinally at different intervals, ranging between 16 –37
weeks of gestation, at birth, at 6 postnatal months,
and at 1 year. A total of 1,427 individuals had both
femur or body length and head circumference measures taken prenatally and postnatally, with males
comprising 52% of the sample. All postnatal measures were taken three times, and the mean was
reported. Measurement error in both ultrasound
and anthropometric measures was very low. The
coefficient of variation for ultrasound measures was
no greater than 1% for head circumference and femur length. The maximum coefficient of variation
for body length was 0.15% of the mean, based on 10
infants measured five times by three observers. It is
no higher than 0.75% of the mean for the head
circumference (P. Hindmarsh, personal communication). Table 1 lists the means, standard deviations,
and sample sizes for human variables at each measurement period and for age. In addition, the difference in head circumference and femur length/body
length between males and females and the difference in age for each measurement period are represented as the percent difference in size. The number
of individuals measured at each measurement period differed, but the sexes were well-matched for
age at each period.
Rhesus macaque data. The rhesus macaque
(Macaca mulatta) data analyzed here were collected
by Dr. Alice Tarantal at the California National
Primate Research Center at the University of California, Davis. See Tarantal and Gargosky (1995) and
Tarantal and Hendrickx (1988) for a detailed description of these data. A total of 482 individuals had
both fetal head circumference and femur length
measures taken ultrasonically, of which 52% were
male. Measures were taken longitudinally between
60 days and term (165 ⫾ 10 days). Femur lengths
were obtained by measuring the longest view of the
ossified portion of the femur and positioning the
100
TRACEY H. JOFFE ET AL.
TABLE 2. Means, standard deviations, and sample sizes for males and females in rhesus monkey sample1
Males
Variable
Head circumference (mm)
Prenatal:
Second trimester (⬃55–110 days)
Third trimester (⬃111–165 days)
Postnatal:
Birth–1 month
1–2 months
2–3 months
3–6 months
Femur length (mm)
Prenatal:
Second trimester (55–110 days)
Third trimester (111–165 days)
Postnatal:
Birth–1 month
1–2 months
2–3 months
3–6 months
Age (days)
Prenatal:
Second trimester (⬃55–110 days)
Third trimester (⬃111–165 days)
Postnatal:
Birth–1 month
1–2 months
2–3 months
3–6 months
Females
%
difference
Mean
SD
N
Mean
SD
N
113.8
177.1
28.8
13.4
135
142
109.0
175.2
28.3
14.9
124
135
4.37
1.1
203.1
217.4
222.6
230.4
8.4
4.2
6.0
7.3
76
16
12
12
200.4
215.1
219.8
227.3
7.5
3.4
4.2
4.7
86
13
10
11
1.1
1.1
1.27
1.38
17.7
42.1
7.9
8.0
173
169
17.4
42.9
8.1
8.6
164
173
2.43
⫺1.92
62.6
73.9
80.1
90.8
4.3
2.4
2.9
5.4
76
16
12
12
63.2
73.4
80.0
87.6
4.9
3.8
3.9
4.7
87
13
10
11
⫺1.26
0.8
0.24
3.72
86.96
137.09
17.50
12.87
135
142
86.21
136.67
17.42
12.53
124
135
0.87
0.31
173.83
216.63
250.0
305.0
12.53
7.26
0.0
25.05
76
16
12
12
173.56
214.46
250.0
307.0
12.98
8.65
0.0
24.94
86
13
10
11
0.16
1.01
0.0
⫺0.65
1
Average gestation length is 165 ⫾ 10 days. Some individuals did not have both head circumference and femur length measures.
Postnatal ages presented as days from age at conception (i.e., gestation age ⫹ postnatal days).
%difference, mean difference as a percent of female mean. Nonsignificant based on independent-samples t-tests.
cursors at each end. Head circumference was measured by tracing the outer limits of the skull with
the cursor. Measurement error for both head circumference and femur length was within 1 mm. In
addition, anthropometric measures of head circumference and femur length at birth and during infancy were taken for 242 individuals, of which 49%
were male. Not all individuals were measured in
each measurement period. Postnatal femur length
measures were taken using calipers from the
greater trochanter to the patella. Measurement error was no greater than 1 mm, and was associated
with 0.7% measurement error of fetal head circumference and 3.6% of femur length in the fetus. Measurement error in the infant rhesus monkey is estimated to be no greater than 0.6% of the head
circumference mean, and 1.4% of the femur length
mean. Table 2 lists the means, standard deviations,
and sample sizes for the rhesus monkey data. In
addition, the difference in head circumference, femur length, and age between males and females is
represented as the percent difference in size. Sexes
were well-matched for age in each measurement
period.
Baboon data. Ultrasound head circumference
and femur length measures were collected for baboon species by Drs. Karen Rice and Michelle Leland at the Southwest Foundation for Biomedical
Research (San Antonio, TX). A total number of 2,677
individuals had both head circumference and femur
length measures taken prenatally between 30 –180
gestational days. Of these, only 569 had head circumference and femur length measured and were
sexed with males, comprising 53% of the sample.
Ultrasound measures for all baboon species were
taken with a precision within 1 mm. Measurement
error is estimated to be within 0.8% of the head
circumference mean, and 3.4% of the femur length
mean in the fetus. Although a number of species are
represented in this database, size or dimorphism
differences between species were not present (Michelle Lehland, personal communication). Therefore,
the combined dataset of baboon species was analyzed here. Table 3 lists the means, standard deviations, and sample sizes for the fetal baboon data
from the second trimester on. In addition, the difference in head circumference, femur length, and age
between males and females is represented as the
percent difference in size. In each measurement period, the sexes were well-matched for age.
Marmoset data. Neonatal anthropometric measures for the common marmoset (Callithrix jacchus)
were taken by Dr. Ann-Kathrin Oerke at the Deutsches Primatenzentrum (Göttingen, Germany). In
total, 69 neonates, produced in 30 pregnancies, were
measured for both head circumference and body
weight. Femur lengths could not be measured accurately at birth due to the very small size of the
neonate. Head circumference was measured at the
widest diameter of the head, with a measurement
error of about 1% of the mean. Measurement error in
weight was minimal.
101
HEAD CIRCUMFERENCE SEXUAL DIMORPHISM
TABLE 3. Means, standard deviations, and sample sizes for males and females in fetal baboon sample1
Males
Head circumference (mm)
Second trimester (63–124 days)
Third trimester (125–185 days)
Femur length (mm)
Second trimester (63–124 days)
Third trimester (125–185 days)
Age (days)
Second trimester (63–124 days)
Third trimester (125–185 days)
Females
%
difference
Mean
SD
N
Mean
SD
N
119.1
201.8
36.6
17.0
233
71
116.9
198.1
35.5
16.1
200
65
4.37
1.1
23.4
54.3
10.6
9.0
233
72
23.4
54.8
10.7
8.6
200
67
2.43
⫺1.92
94.06
141.81
20.15
13.68
233
72
93.7
141.22
20.08
13.74
200
67
0.38
0.42
Variable
1
Average gestation length is 185 days. Some individuals did not have both head circumference and femur length measures. Although
2,665 baboons in dataset had ultrasound data, only 567 were sexed. % difference, mean difference as a percent of female mean.
Nonsignificant based on independent-samples t-tests.
TABLE 4. Means, standard deviations, and sample sizes for male and female marmoset neonates1
Males
Females
Variable
Mean
SD
N
Mean
SD
N
%
difference
Birth weight (g)
Head circumference (mm)
29.0
85.0
4.03
4.56
27
25
30.5
86.4
4.4
5.41
45
44
⫺4.74
⫺1.56
1
Average gestation length is 145 days. All measures taken at birth. % difference, mean difference as a percent of female mean.
Nonsignificant based on independent-samples t-tests.
There is no evidence for neonatal body size sexual
dimorphism in the common marmoset, and Oerke
(1995) showed that there are no significant differences in head measurements between singleton,
twin, and triplet fetuses. Differences in head circumference were therefore evaluated between male and
female neonates from multiparous pregnancies as a
function of birth weight. Table 4 lists the means,
standard deviations, and samples sizes for the neonatal marmoset data. In addition, the difference in
head circumference and body weight between males
and females is represented as the percent difference
in size.
Statistics
First we determined whether sexual dimorphism
was present in both absolute head circumference
and absolute body size (femur length, body length,
or body weight, depending on the species). We used
independent samples t-tests to compare the means
in absolute values between the sexes at specific measurement periods. These included, for humans: ultrasounds 2 and 3, birth, 6 months, and 1 year; for
baboons: second and third trimester measures; for
rhesus monkeys: second and third trimester measures, measures taken between birth and 1 month,
1–2 months, 2–3 months, and 3– 6 months; marmosets: measures at birth.
Sex differences in relative head circumference
were analyzed using reduced major axis (RMA) regression analysis. First for each species separately,
head circumference measures were plotted against
femur length (fetus) or body length (infant) measures and evaluated for linearity. Then RMA regression models were fitted through the combined sex
data. RMA residuals were then calculated from the
predictive equations as the difference between observed and predicted head circumference. Sex differences in residuals were then determined using independent-samples t-tests with confidence limits set at
95% where age ranges for the sexes were wellmatched. Sex-specific box plots were produced to
show the mean ⫾2 SD in derived head circumference residuals between the sexes at specific measurement periods. In addition, we assessed these
findings in comparison to those found when fitting
least squares regressions through the data, in order
to ensure that the results were not a function of the
line-fitting technique used.
We evaluated whether significant findings of sexual dimorphism in relative head circumference may
be influenced by differing relationships in the sexes
in body/femur length. We used multiple regression
analysis, where the variance in head circumference
was determined as a function of femur/body length,
sex, and the interaction between femur/body length
and sex (Sokal and Rohlf, 1997). Sex was included as
an interaction variable with femur/body length in
the model, in order to determine whether the sex
effect on head circumference may vary over the
range of body size. A dummy variable was established, whereby values of 0 and 1 were assigned to
males and females, respectively. The dummy variable was then multiplied by femur or body length
values, representing the interaction between sex
and length. Length, sex, and interaction variables
were then entered into a multiple regression model
as independent variables, with head circumference
entered as the dependent variable. A significant difference in the resulting R2 values with and without
the interaction variable entered into the model rep-
102
TRACEY H. JOFFE ET AL.
resents the influence of sex on body length in explaining the variance in head circumference.
Statistical analyses were carried out using SPSS
(SPSS, Inc., Chicago, IL). Reduced major-axis regressions were carried out using PAST, developed by
O. Hammer (University of Oslo, Oslo, Norway).
Hammer utilized the methods of Miller and Kahn
(1962) to calculate the error of the slope and intercept and the 95% confidence intervals for RMA directly.
RESULTS
Sexual dimorphism
Statistically significant but small differences between human males and females were present in
absolute head circumference and in absolute postnatal body length, where males were generally
larger than females (Table 1). No statistically significant differences in absolute head circumference or
absolute femur length (body weight in marmosets)
were present in the baboons, rhesus monkeys, or
marmosets in this study (Tables 2– 4). During fetal
life, human male femur length did not differ significantly from female femur length. Male head circumference was 2.2% larger than female at ultrasound 2, and 1.3% larger at ultrasound 3. From birth
through 12 months of age, significant and comparable differences in both head circumference and body
length were present, where males had larger heads
and greater body lengths. At birth, the male head
circumference was 1.9% larger and the male body
length was 1.7% larger. At 6 postnatal months, the
male head circumference was 2.6% larger and the
male body length was 2.8% larger than the female.
At 12 postnatal months, both the head circumference and body length were 2.4% greater in the male.
Fig. 1. Head circumference in relation to femur length in
prenatal humans with reduced major axis regression line.
RMA analysis: human
Head circumference measures in relation to femur
length (in the fetus) or body length (in the infant)
measures yielded linear relationships at ultrasounds 2 and 3. The clustering of data points when
the two measurement periods were combined prevented the assessment of this relationship across
the entire fetal period for which we have measurements (Fig. 1). Linear relationships were also
present at birth, 6 months, and 12 months; however,
they were nonlinear in the combined postnatal dataset (Fig. 2). The nonlinear relationship at this time
is consistent with the slowing down of head circumference growth in relation to body length growth.
Combined data for ultrasounds 2 and 3 are included
in the results, while a combined postnatal RMA
analysis was not possible.
Between 23% and 61% of the variance in head
circumference was explained by femur or body
length at specific measurement periods, with the
statistical relationship generally weakening with increasing age. The results of the reduced major-axis
regression analysis for humans are listed in Table 5,
Fig. 2. Head circumference in relation to body length in postnatal humans with measurement period-specific RMA lines.
Combined postnatal regression is nonlinear.
where the slopes, intercepts, and 95% confidence
intervals for the predictive equations are also given.
Least squares slopes and intercepts are also given
for comparative purposes. Statistics for sex-specific
regressions are listed in Table 6. These reveal that
although the slopes for both sexes are similar, intercepts are consistently but not significantly higher in
males. The least squares regression provided the
same results, although the intercepts were higher
and slopes lower than those derived using RMA.
Figures 3–7 show the sex-specific RMA regressions
at each measurement period.
Independent-samples t-tests associated with the
derived RMA residuals (from the pooled sex equations in Table 5) are listed in Table 7. T-tests were
carried out where ages were well-matched between
the sexes. Statistically significant levels of relative
103
HEAD CIRCUMFERENCE SEXUAL DIMORPHISM
TABLE 5. Reduced major-axis regression for relationship between head circumference and femur length (prenatal) or body length
(postnatal) in humans, with least squares slopes and intercepts given for comparison1
Scan 22
Scan 32
Birth3
6 months3
1 year3
Scans 2 ⫹ 3
combined2
R2
SEE
P
n
Intercept
Slope
Error
intercept
Error
slope
CI intercept
0.607
0.311
0.323
0.296
0.232
0.972
8.04
13.08
14.28
12.47
13.65
10.56
0.000
0.000
0.000
0.000
0.000
0.000
1542
1215
1434
926
350
2757
40.74
32.52
42.23
92.68
111.76
42.67
4.21
4.31
0.61
0.51
0.47
4.15
2.20
6.37
6.59
9.48
16.56
0.633
0.07
0.10
0.013
0.01
0.022
0.013
35.09, 46.62
19.15, 45.58
27.1, 56.16
73.59, 111
74.83, 144.5
41.5, 43.76
CI slope
4.02,
4.10,
0.58,
0.48,
0.42,
4.12,
4.39
4.52
0.64
0.54
0.52
4.18
LS
slope
LS
intercept
3.28
2.41
0.35
0.28
0.23
4.09
71.0
150.70
172.97
249.33
294.78
45.33
1
SEE, standard error of estimate; CI, 95% confidence interval; LS, least squares regression. RMA (reduced major axis) statistics
calculated using PAST software.
2
Head circumference (mm) in relation to femur length (mm).
3
Head circumference (mm) in relation to body length (mm).
TABLE 6. R2 values, sex-specific slopes, and intercepts with 95% confidence intervals for head circumference in relation to femur
length (fetus) or body length (infant) in humans, with least squares slopes and intercepts given for comparison1
Males
Measurement
period
R
Slope
Ultrasound 22
Ultrasound 32
Birth3
6 months3
12 months2
Ultrasounds 2
⫹ 32
0.610
0.302
0.290
0.220
0.138
0.973
4.16 (3.25)
4.34 (2.39)
0.60 (0.32)
0.50 (0.24)
0.43 (0.16)
4.17 (4.11)
2
Females
Intercept
95% CI
slope
95% CI
intercept
R
Slope
Intercept
95% CI
slope
95% CI
intercept
43.92 (73.7)
32.84 (154.09)
48.31 (186.82)
97.55 (280.21)
138.15 (347.44)
43.47 (46.11)
3.92, 4.39
4.04, 4.64
0.56, 0.64
0.46, 0.55
0.37, 0.51
4.135, 4.209
36.49, 51.38
13.97, 51.12
27.41, 68.63
68.16, 125.8
81.94, 184
41.689, 45.254
0.612
0.331
0.327
0.216
0.190
0.973
4.21 (3.29)
4.30 (2.48)
0.61 (0.35)
0.47 (0.22)
0.45 (0.20)
4.13 (4.07)
38.82 (68.71)
30.37 (144.04)
40.66 (169.77)
114.84 (283.43)
119.95 (311.42)
41.34 (43.92)
3.92, 4.49
4.10, 4.64
0.57, 0.65
0.44, 0.52
0.40, 0.51
4.092, 4.167
29.63, 48
9.8, 49.48
17.81, 60.79
87.5, 139.4
75.33, 161.3
39.529, 43.158
2
1
Least squares slopes and intercepts given in parentheses beside; LS, least squares regression. RMA values. SEE, standard error of
estimate; CI, 95% confidence interval. RMA statistics calculated using PAST software.
2
Head circumference (mm) in relation to femur length (mm).
3
Head circumference (mm) in relation to body length (mm).
Fig. 3. Head circumference in relation to femur length in
human fetuses at ultrasound 2 with sex-specific RMA lines.
head circumference dimorphism were found at all
measurement periods, with the exception of birth.
Residual head circumference was consistently
greater in males across measurement periods, with
the mean difference in residuals being 3.5 mm at
ultrasound 2, 4.9 mm at ultrasound 3, 1.3 mm at
birth, 2.1 mm at 6 months, and 3.0 mm at 12
months. Figure 8 shows a box plot comparing the
mean ⫾ 2 SD for RMA residuals in males and females at each measurement.
Fig. 4. Head circumference in relation to femur length in
human fetuses at ultrasound 3 with sex-specific RMA lines.
RMA analysis: nonhuman primates
Head circumference measures in relation to femur
length measures in fetal baboons and fetal and infant rhesus monkeys are shown in Figures 9 –11,
where the coefficients of determination (R2) between
head circumference and femur length were high (Table 8). In baboons, 96% of the variation in head
circumference was explained by femur length. Similarly, in fetal rhesus monkeys, 96% of the variation
in head circumference was explained by femur
104
TRACEY H. JOFFE ET AL.
Fig. 5. Head circumference in relation to body length in neonatal humans with sex-specific RMA lines.
Fig. 7. Head circumference in relation to body length in postnatal humans at 12 months with sex-specific RMA lines.
TABLE 7. T-test results comparing RMA residuals calculated
from head circumference in relation to femur (prenatal) or body
length (postnatal): humans1
Measurement
period
Scan 2
Scan 3
Birth
6 months
12 months
Prenatal combined
Male Female
Mean
SE of
mean mean difference difference
⫹1.57
⫹2.35
⫹0.65
⫹0.97
⫹1.54
⫹1.92
⫺1.92
⫺2.51
⫺0.67
⫺1.17
⫺1.49
⫺2.19
3.49*
4.87*
1.31
2.14**
3.03**
4.11*
0.42
0.75
0.75
0.82
1.45
0.41
df
1,425
1,169
1,432
919
348
2,596
1
See Table 5 for RMA regression statistics. Sample sizes vary
where sex was not reported.
* P ⱕ 0.0001. ** P ⱕ 0.05.
Fig. 6. Head circumference in relation to body length in postnatal humans at 6 months with sex-specific RMA lines.
length. During early infancy, rhesus monkey femur
length explained 83% of the variation in head circumference. Head circumference measures plotted
against body weight in neonatal marmosets also
produced a linear relationship, although body
weight did not explain a statistically significant
amount of the variation in marmoset head circumference at birth (Table 8).
The results of the reduced major-axis regression
analysis for nonhuman primates are listed in Table
8, with sex-specific regression statistics listed in Table 9. These include the slopes and intercepts as well
as 95% confidence intervals. Least squares slopes
and intercepts are given for comparative purposes.
In rhesus monkeys, intercepts were higher in males
in both the prenatal and postnatal periods, although
not at a statistically significant level. Male and female intercepts in fetal baboons were not signifi-
cantly different. Statistically nonsignificant relationships between the head and birth weight were
present in the marmosets. Although the male intercept was higher than the female, the difference was
nonsignificant, but reflected a general trend toward
higher relative head circumference in males. Sexspecific slopes in the marmosets, however, differed
markedly. In contrast, in the baboons and rhesus
monkeys, the slopes and intercepts for males and
females were very similar. However, Figure 9 demonstrates that the difference in slope between sexes
in baboons increases with femur length, where the
male slope is higher than the female. Least squares
regressions provided the same results, with the exception that intercepts were generally higher and
slopes lower than those derived using RMA.
Independent-samples t-tests associated with the
RMA residuals derived from combined male and
female regressions are listed in Table 10. Figures
12–14 show box plots comparing the mean ⫾ 2 SD
for RMA residuals in males and female fetal baboons, rhesus monkeys (fetus and infant separately), and neonatal marmosets.
No statistically significant difference in residual
head circumference was found in neonatal marmo-
HEAD CIRCUMFERENCE SEXUAL DIMORPHISM
Fig. 8. Box plot comparing human RMA residual mean (⫾2
SD) calculated from head circumference in relation to femur
length (fetus) or body length (infant). Calculated from predictive
equations derived from Table 5.
Fig. 9. Head circumference in relation to femur length in
prenatal baboons with sex-specific RMA lines.
sets. However, statistically significant differences in
relative head circumference were present in fetal
baboons, fetal rhesus monkeys, and infant rhesus
monkeys. Similar levels of relative head circumference dimorphism were present in the baboons and
rhesus monkeys, where the mean difference ranged
between 2.9 mm in the fetal baboon and 2.7 mm in
the fetal rhesus monkey. The mean difference in
residuals between the sexes in infant rhesus monkeys was comparable, at 2.6 mm.
Multiple regression analysis for humans and
nonhuman primates
Table 11 lists the results of the multiple regression analysis (with sex as an interaction variable) in
humans, and Table 12 in nonhuman primates. Re-
105
Fig. 10. Head circumference in relation to femur length in
prenatal rhesus monkeys with sex-specific RMA lines.
Fig. 11. Head circumference in relation to femur length in
postnatal rhesus monkeys with sex-specific RMA lines.
sults of the multiple regression analysis in human
fetuses and infants suggest that the inclusion of sex
as an interaction variable in the model, along with
femur/body length and sex, does not contribute significantly to explaining the variance in head circumference. At ultrasounds 2 and 3 and birth, 0% of the
variance in head circumference was explained by
the interaction of sex and femur/body length specifically. The interaction variable explained 0% of head
circumference variance at 6 months, and 0.6% at 12
months. In baboon and rhesus monkey fetuses, 0%
of the variance in head circumference was explained
by the interaction of sex and femur length. In rhesus
monkey infants, only 0.12% of the variance was explained. In marmosets, the model did not reach significance. The interaction variable therefore did not
contribute significantly to the models in any of the
monkey species or humans. These findings suggest
106
TRACEY H. JOFFE ET AL.
TABLE 8. Reduced major-axis regression for relationship between head circumference and femur length in nonhuman primates,
with least squares slopes and intercepts given for comparison1
Species
R2
SEE
P
n
Intercept
Slope
Error
intercept
Error
Slope
95% CI
intercept
Fetal baboon2
Fetal rhesus monkey2
Infant rhesus monkey2
Neonatal marmoset3
0.963
0.957
0.827
0.023
9.32
7.77
5.41
6.69
0.000
0.000
0.000
0.221
2,665
481
242
69
48.86
53.32
127.31
50.9
2.88
3.11
1.18
1.17
0.366
0.885
2.20
4.21
0.011
0.029
0.031
0.14
48.2, 49.54
51.54, 54.8
122.2, 131.40
36.98, 126.0
95% CI slope
LS
slope
LS
intercept
2.82
3.04
1.07
0.18
50.46
55.18
134.66
80.67
2.85, 2.91
3.05, 3.17
1.12, 1.24
⫺1.34, 1.60
1
SEE, standard error of the estimate; CI, 95% confidence interval; LS, least squares regression. RMA (reduced major axis) statistics
calculated using PAST software.
2
Head circumference (mm) in relation to femur length (mm).
3
Head circumference (mm) in relation to body weight (g).
TABLE 9. R2 values, sex-specific slopes, and intercepts with 95% confidence intervals for head circumference in relation to femur
length in nonhuman primates, with least squares slopes and intercepts given for comparison1
Males
Baboon fetus
Rhesus monkey
fetus
Rhesus monkey
infant
Common
marmoset
neonate
Females
95% CI
slope
95% CI
intercept
R2
Slope
Intercept
95% CI
slope
95% CI
intercept
49.46 (51.19)
52.41 (54.09)
2.74, 2.90
3.01, 3.17
47.24, 51.5
50.4, 54.64
1.20 (1.09)
124.79 (132.03)
1.12, 1.29
118.3, 130.1
1.22 (0.77)
49.30 (84.04)
⫺1.66, 1.77
31.2, 137.5
R2
Slope
Intercept
0.961
0.956
2.90 (2.85)
3.12 (3.05)
49.59 (51.30)
54.36 (56.29)
2.82, 2.99
3.04, 3.19
47.36, 51.69
52.41, 56.58
0.960
0.961
2.81 (2.76)
3.09 (3.03)
0.839
1.14 (1.04)
131.23 (137.89)
1.05, 1.25
124, 137.8
0.831
0.080
1.10 (0.31)
53.38 (76.06)
⫺1.35, 1.54
39.51, 124
0.004
1
Least squares slopes and intercepts given in parentheses beside RMA values. HC, head circumference in mm; FL, femur length in
mm; CI, 95% confidence interval. Nonsignificant in common marmoset. RMA statistics calculated using PAST software.
TABLE 10. T-test results comparing RMA residuals calculated from head circumference
in relation to femur length: nonhuman primates1
Fetal baboon
Fetal rhesus monkey
Infant rhesus monkey
Neonatal marmoset
Male
mean
Female
mean
Mean
difference
SE of
difference
df
⫹1.38
⫹1.28
⫹0.975
⫹0.308
⫺1.51
⫺1.44
⫺1.603
⫹0.167
2.9*
2.72*
2.58*
0.48
0.802
0.699
0.678
1.69
5672
479
240
67
1
See Table 8 for RMA regression statistics. Sample sizes vary where sex was not reported.
Reduction in sample size due to large number of unsexed data utilized for RMA equation calculation.
* P ⱕ 0.0001.
2
that head circumference dimorphism persists across
femur/body length ranges in humans and monkeys.
DISCUSSION
Despite using somewhat different data and approaches in different species, each sample was internally robust for evaluating sex differences. Low
but statistically significant differences between the
sexes were found in the humans, baboons, and rhesus monkeys in this study, where comparable levels
of dimorphism were found between humans, rhesus
monkeys, and baboons (⬃2%). No significant dimorphism was found in marmosets or humans at birth.
It is unclear why statistically significant levels of
relative head circumference dimorphism in humans
were not found at birth. One possibility for this may
be head molding or swelling, which often occurs with
natural birth and may mask the relatively low levels
of dimorphism found in young humans.
Multivariate analysis revealed that when the interaction between sex and body length was included
in the model, it did not explain a significant proportion of the variance in head circumference in hu-
mans and monkeys. This suggests that the findings
of the RMA analysis are not driven by the relationship between sex and body length specifically, nor is
dimorphism influenced by extremes in body size.
The fact that such low levels of relative head circumference dimorphism were found here suggests
that it emerges largely postnatally, reaching adulthood values in humans of about 10% based on autopsy brain weights (Ho et al., 1980a,b; Dekaban
and Sadowsky, 1978; Filipek et al., 1994; Pfefferbaum et al., 1994; Blatter et al., 1995). In rhesus
monkeys, dimorphism also develops largely in later
life, when adult brain (independent of body size)
dimorphism is on the order of 8% (Falk et al., 1999).
Direct comparisons between the fetal and infant
relative head circumference dimorphism values
found here should, however, be applied to adult
brain dimorphism values with caution, as head circumference in the adult is not a good indicator of
brain weight due to increased skull thickness and
changes in shape. Nevertheless, marked relative
brain dimorphism appears to be primarily a postnatal phenomenon.
107
HEAD CIRCUMFERENCE SEXUAL DIMORPHISM
Fig. 12. Box plot comparing baboon mean (⫾2 SD) RMA residuals calculated from head circumference in relation to femur length.
Calculated from predictive equations derived from Table 8.
Fig. 14. Box plot comparing mean (⫾2 SD) RMA residuals for
male and female neonatal marmosets. Calculated from predictive
equations derived from Table 8.
TABLE 11. Results of multiple regression analysis:
human sample1
Measurement
Fetal scan 2
Fetal scan 3
Birth
6 months
1 year
Body length
⫹ sex R2
Sex
interaction R2
%
influence
N
0.621
0.345
0.337
0.361
0.316
0.621
0.345
0.337
0.361
0.318
0.0
0.0
0.0
0.0
0.63
1,427
1,172
1,434
921
350
1
Head circumference in relation to femur/body length, sex, and
sex interaction with femur/body length. R2 values derived from
multiple regression analysis, where head circumference is independent variable. % influence, difference between R2 values for
models including body length ⫹ sex with and without interaction
between body length and sex.
TABLE 12. Results of multiple regression analysis:
rhesus monkey sample1
Fig. 13. Box plot comparing mean rhesus monkey (⫾2 SD)
RMA residuals calculated from head circumference in relation to
femur length. Calculated from predictive equations derived from
Table 8.
It is interesting that no evidence for relative head
circumference dimorphism was found in the common marmoset here. Unlike in humans, baboons,
and rhesus monkeys, we relied on marmoset birth
weights rather than femur lengths in our analysis.
Unfortunately, because of the difficulty in accurately measuring femur length in such small animals, we do not know whether the relationship between femur length and head circumference differs
from that of birth weight and head circumference.
Also, little is known of the timing of brain development in this species, but it is a rapidly growing
species, reaching adulthood significantly sooner
than the other monkeys. It is therefore possible that
delayed growth is a prerequisite for early brain di-
Measurement
Rhesus monkey
Fetus
Infant
Baboon
Fetus
Femur length
⫹ sex R2
Sex
interaction
R2
%
influence
N
0.958
0.839
0.958
0.838
0.0
0.12
481
123
0.961
0.961
0.0
265
1
Head circumference in relation to femur length, sex, and sex
interaction with femur length. R2 values derived from multiple
regression analysis, where head circumference is independent
variable. % influence, difference between R2 values for models
including femur length ⫹ sex with and without interaction between femur length and sex. Model did not reach significance in
common marmosets.
morphism, particularly given that advances in dimorphism appear to take place following early infancy. Humans, for example, undergo a marked
prolongation of growth (Watts, 1985, 1986; Leigh
and Park, 1998).
In addition to differences in duration of growth,
differences in growth rate between the sexes may
108
TRACEY H. JOFFE ET AL.
play a role in relative head circumference dimorphism. Vančata et al. (1995) found in a group of
captive-born rhesus monkeys that body parameters
displayed different growth rates accompanied by differences between the sexes. Notably, females displayed growth acceleration in body height and mass
in the prepuberty and early puberty periods, while
male height and mass increased more rapidly in the
first 5 years of life. In contrast, head circumference
growth increased rapidly until 40 weeks of life, and
then slowed markedly.
The differing growth trajectories in body length
between the sexes found by Vančata et al. (1995)
may relate to increased differences in relative head
circumference over time. Fluctuations between the
sexes in femur/body length during growth, accompanied by more consistent differences in head circumference between the sexes, may therefore comprise
the relative head circumference dimorphism found
in this species. As shown here, from the third trimester to the first month of life, female rhesus monkey femur lengths were significantly greater than
male, while male head circumferences were consistently greater than female. Baboons were similar in
that female femur lengths in the third trimester
were larger than male, but head circumference in
males was consistently larger than female. Humans,
on the other hand, differed from the monkeys in that
they appeared to retain similar levels of head and
body dimorphism after birth in this analysis, with
males consistently larger in both parameters.
Caution should be taken before ascribing functional significance to the relative head circumference dimorphism found here and in the adults.
Brain size alone cannot be viewed as a cognitive
constraint, as females, who have relatively smaller
brains than males, have proportionately more gray
matter than males. The greater volume of gray matter in female brains is associated with increased
efficiency of computational processing of the brain in
response to the associated increased nerve cell bodies and dendritic expansion, and greater number of
neural connections associated with increased gray
matter (Andreasen et al., 1993), that could compensate for decreased intracranial space in women (Gur
et al., 1999). For this reason, investigators should be
cautious before ascribing functional significance to
brain size sexual dimorphism, particularly since we
do not yet fully understand what comprises overall
brain size differences between the sexes.
One possibility, yet to be explored, is that male
brains may be associated with higher levels of hydration than female brains. Adult males have about
50% more lean body tissue than females (Norgan,
1999), and may well be generally more hydrated as
a result. About 74% of lean tissue in human adults is
comprised of water (Wang et al., 1999). Accordingly,
increased male hydration may be generalized
throughout the body. We know that over three quarters of the adult brain is comprised of water, and
that brain hydration values are not constant but
change with age (Widdowson and Dickerson, 1960).
It is certainly not clear from existing longitudinal
MRI studies whether temporary changes in brain
size are associated with changes in water, lipid, or
protein, for example (Holdcroft et al., 1997). Alternatively, increased cerebrospinal fluid in males (Gur
et al., 1999) may explain overall gender differences
in relative brain size. It may be that larger individuals (males) require relatively more cerebrospinal
fluid.
The implications of the relatively larger head circumference of the human male are interesting to
consider in light of the high energetic costs of the
brain. In early life, the brain utilizes up to 85% of
total energy requirements. Using the values of Elia
(1992) for weight-specific brain metabolic rate (computed in the adult), the estimated daily metabolic
cost of 1 g of brain tissue in a 6-month-old infant is
⬃0.24 kcal/day. The male head circumference at this
time is 441 mm, and the female is 430 mm (Table 1).
Using Equation 1 to estimate brain weight from
head circumference, the additional 11 mm of head
circumference in the male is equivalent to 13 g of
brain tissue and an additional cost of 3 kcal/day in
an infant with a daily metabolic requirement of
about 390 kcal/day at about 6 months of age. The
metabolic cost of the increase in brain size would
therefore be associated with a ⬃0.8% increase in
total daily energy requirements compared to those of
a female of comparable body size.
According to Butte (1996), total energy requirements for males in the first 6 months of life are 5.8%
greater than females, when taking into account the
costs of growth and total energy expenditure. Of the
additional energy requirements in males at this
time, brain dimorphism accounts for only 0.8% of the
difference, with the remaining 5% explained by bone
mineral content/density, lean tissue, and activity
differences between the sexes. In light of the parentoffspring conflict theory and the Trivers-Willard hypothesis (Trivers, 1972, 1974; Trivers and Willard,
1973), it is important to consider the possibility that
this may pose an increased energetic burden to the
lactating mother.
The energy content of breast milk is estimated at
58 kcal/100 ml (Lucas and Davies, 1990), while the
increased caloric demand of male brain dimorphism
at 6 months was estimated at 3 kcal/d. This level of
energy demand is associated with an additional 5 ml
of milk production per day. The efficiency of converting dietary energy to milk energy is thought to be
80%, and is therefore associated with a cost to the
mother of 3.6 kcal/day. This represents a very low
cost to the woman, and suggests that increasing
dimorphism with age may be supported in part by
the increasing dietary independence of the male.
Marked increases in brain dimorphism in later life,
when male brain weight is as much as 10% larger
than the female, are likely to impact male energy
balance, and the additional energetic burden would
HEAD CIRCUMFERENCE SEXUAL DIMORPHISM
be interesting to consider in terms of growth and
life-history differences between the sexes.
CONCLUSIONS
Using ultrasound and anthropometric measures
in fetal and infant human and nonhuman primates,
we showed that statistically significant but negligible levels (within 2%) of dimorphism in relative head
circumference were found in humans, rhesus monkeys, and baboons. We cannot discount that some of
the dimorphism found may be attributable to measurement errors in the head circumference or femur/
body length. However, measurement error was
slightly greater in femur length rather than head
circumference, and would thus be associated with a
decrease rather than an increase in head circumference dimorphism. In the common marmoset, we
found no evidence for relative head circumference
sexual dimorphism. Furthermore, multivariate
analysis, controlling for the interaction of sex and
body length, revealed that sex per se did not influence the underlying relationship between the head
and body within this context, but that dimorphism
existed in head circumference across the full range
of body sizes.
The head circumference dimorphism levels found
here are significantly lower than brain dimorphism
values reported in adults. Head circumference in
early life is shown to be a good estimator of brain
weight. We suggest that increases in head circumference sexual dimorphism with age may point to an
early onset of brain dimorphism, perhaps during
hyperplasic brain growth, followed by increases in
size resulting from hypertrophic growth as well as
differences between the sexes in head and body
growth. It will be informative to evaluate dimorphism in head circumference relative to body length
in juveniles to assess whether adulthood values of
dimorphism are attained at or prior to sexual maturity, since dimorphism levels may impact energy
requirements and growth rates.
While dimorphism values in fetal humans do not
differ significantly from those of baboons and rhesus
monkeys, during later development, humans undergo a greater increase in dimorphism, resulting in
adulthood dimorphism values 2% greater than those
for adult rhesus monkeys. It is during this period
that the study of brain dimorphism will be particularly informative.
We caution investigators in ascribing functional
significance to brain size sexual dimorphism until a
better understanding of the nature of the relative
brain size difference between the sexes is established. It is still not clear whether differences in
specific component volumes, neuronal density, cerebrospinal fluid, or hydration in the brain account for
brain size sexual dimorphism. Although the clear
functional significance of this dimorphism is not yet
known, it may have important effects on energy
metabolism, with possible implications for growth
and life history.
109
ACKNOWLEDGMENTS
We are grateful to Prof. Timothy Cole for his help
with statistics and to Dr. Elisabeth Isaacs for her
insights into sex differences in brain size. T.H.J. also
thanks the Overseas Research Studentship Program and the UCL Graduate School for support with
this work, carried out as part of a Ph.D. dissertation
project.
LITERATURE CITED
Andreasen NC. 1993. Sex differences in the brain: perspectives
from neuroimaging. Society for Neuroscience. Washington, DC.
Andreasen NC, Flaum M, Swayze V II, O’Leary DS, Alliger R,
Cohen G, Ehrhardt J, Yuh WTC. 1993. Intelligence and brain
structure in normal individuals. Am J Psychiatry 150:130 –134.
Ankney CD. 1992. Sex differences in relative brain size: the
mismeasure of woman too? Intelligence 16:329 –336.
Blatter DD, Bigler ED, Gale SD, Johnson SC, Anderson CV,
Burnett BM. 1995. Quantitative volumetric analysis of brain
MR: normative database spanning 5 decades of life. Am J
Neuroradiol 16:241–251.
Bray PF, Shields WD, Wolcott GJ, Madsen JA. 1969. Occipitofrontal head circumference, an accurate measure of intracranial volume. J Pediatr 75:303–305.
Buda BF, Rabe EF, Reed JC. 1975. Skull volume in infants,
methodology, normal values and application. Am J Dis Child
129:1171–1176.
Butte NF. 1996. Energy requirements of infants. Eur J Clin Nutr
50:24 –36.
Campbell S, Thoms A. 1977. Ultrasound measurement of the fetal
head to abdominal circumference ratio in the assessment of
growth retardation. Br J Obstet Gynaecol 84:165–174.
Chrzanowska G, Beben A. 1973. Weight of brain and body height
in man between the ages of 20 and 89 years. Folia Morphol
(Warsz) 32:391– 406.
Cooke RWI, Lucas A, Yudkin PLN, Pryse-Davies J. 1977. Head
circumference as an index of brain weight in the fetus and
newborn. Early Hum Dev 1:145–149.
Deacon TW. 1989. Problems of ontogeny and phylogeny in brainsize evolution. Int J Primatol 11:237–282.
Dekaban AS, Sadowsky D. 1978. Changes in brain weight during
the span of human life: relation of brain weights to body heights
and body weights. Ann Neurol 4:345–356.
De Vore GR, Platt LD. 1987. Diagnosis of intrauterine growth
retardation: the use of sequential measurements of fetal
growth parameters. Clin Obstet Gynecol 30:968 –984.
Dobbing J. 1970. Undernutrition and the developing brain: the
relevance of animal models to the human problem. Am J Dis
Child 120:411.
Dobbing J, Sands J. 1970. Timing of neuroblast multiplication in
developing human brain. Nature 226:639.
Doubilet PM, Greenes RA. 1984. Improved prediction of gestational age from fetal head measurements. Am J Radiol 142:
797– 800.
Elia M. 1992. Organ and tissue contribution to metabolic rate. In:
Kinney JM, Tucker HN, editors. Tissue determinants and cellular corollaries. New York: Raven Press. p 61–79.
Epstein HT, Epstein EB. 1978. The relationship between brain
weight and head circumference from birth to age 18 years.
Am J Phys Anthropol 48:471– 474.
Falk D, Froese N, Sade DS, Dudek BC. 1999. Sex differences in
brain/body relationships of rhesus monkeys and humans. J
Hum Evol 36:233–238.
Fazekas IG, Kósa I. 1978. Forensic fetal osteology. Budapest:
Akadémiai Kiadó.
Fescina RH, Martell M. 1983. Intrauterine and extrauterine
growth of cranial perimeter in term and preterm infants. Am J
Obstet Gynecol 147:928 –931.
Fescina RH, Ucieda FJ. 1980. Reliability of fetal anthropometry
by ultrasound. J Perinat Med 8:93.
110
TRACEY H. JOFFE ET AL.
Filipek PA, Richelme C, Kennedy DN, Caviness VS. 1994. The
young adult human brain: an MRI-based morphometric analysis. Cereb Cortex 4:344 –360.
Fujimura M, Seryu JI. 1977. Velocity of head growth during the
perinatal period. Arch Dis Child 52:105–112.
Guihard-Costa AM, Larroche JC. 1995. Fetal biometry. Fetal
Diagn Ther 10:212–278.
Gur RC, Mozley PD, Resnick SM, Gottlieb GL, Koh M, Zimmerman R, Herman G, Atlas S, Grossman R, Berretta D, Erwin R,
Gur RE. 1991. Gender differences in age effect on brain atrophy
measured by magnetic resonance imaging. Proc Natl Acad Sci
USA 88:2845–2849.
Gur RC, Turetsky BI, Matsui M, Yan M, Bilker W, Hughett P,
Gur RE. 1999. Sex differences in brain gray and white matter
in healthy young adults: correlations with cognitive performance. J Neurosci 19:4065– 4072.
Hartmann P, Ramseier A, Gudat F, Mihatsch MJ, Polasek W,
Geisenhoff C. 1994. Das Normegewicht des Gehirns beim Erwachsonen in Abhängigkeit von Alter. Geschlecht, Korpergröße
und Gewicht. Pathologe 15:165–170.
Harvey I, Persaud R, Ron MA, Baker G, Murray RM. 1994.
Volumetric MRI measurements in bipolars compared with
schizophrenics and healthy controls. Psychol Med 24:689 –
699.
Herndon JG, Tigges J, Anderson DC, Klumpp SA, McClure HM.
1999. Brain weight throughout the life span of the chimpanzee.
J Comp Neurol 409:567–572.
Hindmarsh PC, Geary MP, Rodeck CH, Kingdom JC, Cole TJ.
2002. Intrauterine growth and its relationship to size and
shape at birth. Pediatr Res 52:263–268.
Ho KC, Roessmann U, Straumfjord JV, Monroe G. 1980a. Analysis of brain weight: I. Adult brain weight in relation to sex,
race and age. Arch Pathol Lab Med 104:635– 639.
Ho KC, Roessmann U, Straumfjord JV, Monroe G. 1980b. Analysis of brain weight: II. Adult brain weight in relation to body
height, weight, and surface area. Arch Pathol Lab Med 104:
640 – 645.
Holdcroft A, Oatridge A, Hajnal JV, Bydder GM. 1997. Changes
in brain size in normal human pregnancy. J Physiol (Paris)
49:79 – 80.
Jernigan TL, Archibald SL, Berhow MT, Sowell ER, Foster DS,
Hesselink JR. 1991. Cerebral structure on MRI, part 1: localization of age-related chaanges. Biol Psychiatry 29:55– 67.
Leigh SR, Park PB. 1998. Evolution of human growth prolongation. Am J Phys Anthropol 107:331–350.
Little D, Campbell S. 1982. Ultrasound evaluation of intrauterine
growth retardation. Radiol Clin North Am 20:335–351.
Lucas A, Davies PSW. 1990. Physiologic energy content of human
milk. In: Atkinson SA, Hanson LA, Chandra RK, editors.
Breastfeeding, nutrition, infection and infant growth in developed and emerging countries. St. John’s, Newfoundland, Canada: ARTS Biomedical Publishers and Distributors.
Maki PM, Resnick SM. 2001. Effects of estrogen on patterns of
brain activity at rest and during cognitive activity: a review of
neuroimaging studies. Neuroimage 14:789 – 801.
McLennan JE, Gilles FH, Neff RK. 1983. A model of growth of the
human fetal brain. In: Gilles FH, Leviton A, Dooling EC, editors. The developing human brain. Boston: John Wright PSG. p
43–58.
Meire HB. 1981. Ultrasound assessment of fetal growth patterns.
Br Med Bull 37:253–258.
Meredith HV. 1971. Human head circumference from birth to
early adulthood: racial, regional, and sex comparisons. Growth
35:233–251.
Miller RL, Kahn JS. 1962. Statistical analysis in the geological
sciences. New York: John Wiley & Sons. 483 p.
Namba H, Sokoloff L. 1984. Acute administration of high doses of
estrogen increases glucose utilization throughout brain. Brain
Res 291:391–394.
Nehlig A, Porrino LJ, Crane AM, Sokoloff L. 1985. Local cerebral
glucose ultilization in normal female rats: variations during the
estrous cycle and comparison with males. J Cereb Blood Flow
Metab 5:393– 400.
Nicolini U, Ferrazzi E, Molla R, Massa E, Cicognani G, Santarone
M, Bellotti M, Pardi G. 1986. Accuracy of an average ultrasonic
laboratory in measurements of fetal biparietal diameter, head
circumference, and abdominal circumference. J Perinat Med
14:101–107.
Norgan NG. 1998. Body composition. In: Ulijaszek SJ, Johnston
FE, Preece MA, editors. The Cambridge encyclopedia of human
growth and development. Cambridge: Cambridge University
Press. p 212–215.
Oerke AK. 1995. Detection of pregnancy and monitoring patterns of uterine and fetal growth in the marmoset monkey
(Callithrix jacchus) by real-time ultrasonography. Am J Primatol 36:1–13.
Pakkenberg H, Voigt J. 1964. Brain weight of the Danes: a forensic material. Acta Anat (Basel) 56:297–307.
Pfefferbaum A, Mathalon DH, Sullivan EV, Rawles JM, Zipursky
RB, Lim FO. 1994. A quantitative resonance imaging study of
the changes in brain morphology from infancy to late adulthood. Arch Neurol 51:874 – 887.
Resnick SM. 1995. Gender differences in brain structure and
function in the elderly. International Development Symposium:
biological basis for sexual orientation and sex-typical behavior.
Minot State University, ND.
Sabbagha RE. 1978. Intrauterine growth retardation. Antenatal
diagnosis by ultrasound. Obstet Gynecol 52:252–256.
Sokal RR, Rohlf FJ. 1997. Biometry. New York: W.H. Freeman &
Co.
Tanner JM. 1978. Foetus into man: physical growth from conception to maturity. 2nd ed. London: Open Books.
Tarantal AF, Gargosky SE. 1995. Characterization of the insulinlike growth factor (IGF) axis in the serum of maternal and fetal
macaques (Macaca mulatta and Macaca fascicularis). Growth
Regul 5:190 –198.
Tarantal AF, Hendrickx AG. 1988. Prenatal growth in the cynomolgus and rhesus macaque (Macaca fascicularis and Macaca
mulatta): a comparison by ultrasonography. Am J Primatol
15:309 –323.
Trivers RL. 1972. Parental investment and sexual selection. In:
Campbell B, editor. Sexual selection and the descent of man.
Chicago: Aldine. p 139 –179.
Trivers RL. 1974. Parent offspring conflict. Am Zool 14: 247–
262.
Trivers RL, Willard DE. 1973. Natural selection of parental ability to vary the sex ratio of offspring. Science 179:90 –92.
Vančata V, Zlámalová H, Vančatová M, Jebavy L. 1995. Mode
and rate of postnatal growth of Macaca mulatta— basic
adaptive trends and sexual dimorphism. Anthropologie 1–2:
29 –38.
Voigt J, Pakkenberg H. 1983. Brain weight of Danish children.
Acta Anat (Basel) 116:290 –301.
Wang Z, Deurenberg P, Wang W, Pietrobelli A, Baumgartner RN,
Haymsfield SB. 1999. Hydration of fat-free body mass: review
and critique of a classic body-composition constant. Am J Clin
Nutr 69:833– 841.
Watts ES. 1985. Adolescent growth and development of monkeys,
apes and humans. In: Watts ES, editor. Non-human primate
models for human growth and development. New York: Alan
Liss. p 41– 65.
Watts ES. 1986. Evolution of the human growth curve. In:
Falkner F, Tanner JM, editors. Human growth, volume 3. New
York: Plenum Press. p 153–166.
Widdowson EM, Dickerson JWT. 1960. The effect of growth and
function on the chemical composition of soft tissues. Biochem J
77:30.
Willerman L, Schultz R, Rutledge JN, Bigler BD. 1991. In vivo
brain size and intelligence. Intelligence 15:223–228.
Документ
Категория
Без категории
Просмотров
2
Размер файла
203 Кб
Теги
infant, dimorphic, circumference, head, primate, sexual, fetal
1/--страниц
Пожаловаться на содержимое документа