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: email@example.com 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. 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