This study is, to our knowledge, the first pediatric MRI study to implement a population-based sampling strategy to generate unbiased estimates of global and regional brain volumes in a large sample of healthy children and adolescents, ages 4–18 years. It is also the first to examine comprehensively the effects of key socioeconomic indicators on healthy brain volumetric development and the first to report the effects of BMI on brain volumes in healthy children. We describe and quantify associations with age and sex for global brain volumes, regional brain volumes, and hemispheric asymmetries, as measured by multispectral MRI in conjunction with an automated processing pipeline, strict quality control, and a well-established biostatistical model.
There were minimal cross-sectional age-related differences in TBV within the 4- to 18-year-old age range, larger TBVs in males, age-related decreases in cerebral GM, concomitant increases in WM, and more prominent age-related differences in cortical structures and the cerebellum relative to subcortical structures. Salient leftward asymmetries (>1% of TBV) were seen in occipital GM, occipital WM, temporal WM, caudate, and globus pallidus, whereas a prominent rightward asymmetry was seen in temporal lobe GM. Neither of the 2 socioeconomic indicators examined here, AFI or parental education, was significantly related to the volumetric brain measures examined in this healthy pediatric sample. BMI index was inversely related to cerebral GM volumes and positively related to cerebral WM volumes, with no net effect on overall brain volume. We now discuss these findings in more detail.
TBV showed a very small, curvilinear pattern of association across the age range, first increasing and then decreasing very slightly, consistent with some previous reports (e.g., Giedd et al. 1996
; Sporn et al. 2003
; Lenroot et al. 2007
). Thus, most of the increase in global brain volume has already occurred by approximately age 5, or early school age. TBV was approximately 10% greater in males than in females across the age range, also consistent with both the pediatric (Caviness et al. 1996
; Giedd et al. 1996
; Reiss et al. 1996
; Lange et al. 1997
; Kennedy et al. 1998
) and adult (Cosgrove et al. 2007
) literature. There is evidence that males, at birth, have approximately 9% larger intracranial volumes (including 10% more cortical GM and 6% more cortical WM) than do females (Gilmore et al. 2007
), thus extending this sexual dimorphism to younger age ranges.
All regional volumes were significantly correlated with TBV, necessitating adjustment for overall brain size when making regional, and particularly male–female, comparisons. After such adjustment, considerable variability among regional volumes remained. Associations with TBV were generally larger for lobar GM and WM than for subcortical GM structures. Thus, linear stereotaxic normalization may obscure true, though subtle, relationships between regional, particularly cortical, measures and brain size, particularly during development.
Following adjustments for TBV, there were few sex differences, consistent with some, but not all (Sowell et al. 2002
), earlier reports in children (Caviness et al. 1996
; Giedd et al. 1996
; Lange et al. 1997
; Kennedy et al. 1998
) and with data in adults (Luders et al. 2002
). Thus, many reported sex differences may actually reflect differences in brain size. Only the relative volumes of occipital GM, putamen, and cerebellum differed significantly by sex, all larger in males. Some of these effects are consistent with prior reports (e.g., Giedd et al. 1996
reported larger putamen in males), but other previously reported sex differences were not detected. Among these nonreplicated findings are reports of proportionally larger GM volumes in females involving the frontal lobe (Lenroot et al. 2007
) and the caudate (Giedd et al. 1996
; Wilke et al. 2007
). Inconsistencies likely arise from the high interindividual and interstudy variability seen across similar efforts, differences in the specific regional measures examined, sampling design, biostatistical models applied, and other methodological issues. The determinants and implications of any sex-related differences in brain volumes are unclear. Few studies have examined hormonal, genetic, or experiential influences on global brain size. Neither have the functional correlates of such differences been elucidated, and indeed our cognitive data revealed few sex differences (Waber et al. 2007
Controlling for brain size may be critical when assessing variations in regional brain volumes and other cerebral measures, particularly when examining sex differences and/or disorders associated with deviations in brain size, such as autism spectrum disorders, which are associated with early brain overgrowth (Lainhart et al. 1997
; Schumann et al. 2010
), and ADHD, which is associated with smaller brain volumes (Valera et al. 2007
). Few studies have controlled specifically and stringently for whole-brain volumes when examining regional structural variations. Sowell et al. (2007)
is a notable exception, which matched a subset of subjects for brain size to confirm that sex differences identified in cortical thickness were independent of brain volume. Further allometric study of brain development in both health and neurodevelopmental disorders is warranted.
In contrast to the relative stability of TBVs, cortical GM and cerebral WM volumes showed dynamic relations with age. Global and regional GM volumes decreased and WM increased across the age range for nearly all regions reported here, in keeping with prior findings (Caviness et al. 1996
; Reiss et al. 1996
; Lange et al. 1997
; Giedd et al. 1999
). Only the putamen and lateral ventricles failed to show a significant relationship to age. The absence of a relation of age with the lateral ventricular volumes is most likely attributable to high between-subject variability, noted elsewhere in an independent sample (Lange et al. 1997
When both sexes are analyzed together, most age-related associations (consisting of decreases in GM and increases in WM in most regions) were best described by linear functions, with curvilinear functions observed for TBV, parietal WM, thalamus, and cerebellum only. In the context of the more complex multiple regression model employed here, nonlinear relationships were less prominent than in earlier reports (Giedd et al. 1996
). Within our sample, the numbers of subjects available were more sparse at the youngest and oldest ages, potentially limiting our ability to detect nonlinear relationships, as the identification of more complex functions requires more data points and parameters than those needed to fit simple linear functions (Van Belle and Fisher 2004
). The observed trajectories did vary to some extent by sex; females tended to show curvilinear functions more often than did males. These sex differences merit further investigation using forthcoming longitudinal data from this sample. If confirmed, these sex differences should be explored in relationship to genetic, pubertal, and hormonal variables.
After adjusting for TBV, lobar GM declined across cross-sectional age by an estimated 1.11% per year of age, whereas lobar WM increased linearly by 1.54% per year. Age-related associations with GM were more variable across regions than those for WM. Declines in GM volumes were more prominent in parietal and occipital cortex than in frontal and temporal cortex, in keeping with a posterior-to-anterior sequence of maturation. In contrast, lobar WM showed a relatively consistent increase across lobar regions, except for the parietal lobe, ranging from 1.37% (frontal) to 2.14% (occipital) increase per year. These associations are generally consistent with previous reports (Giedd et al. 1996
; Reiss et al. 1996
; Sowell et al. 2002
; Wilke et al. 2007
The increases in WM and concurrent decreases in GM are consistent with progressive myelination and thinning of the cortical mantle reported from postmortem studies (Huttenlocher and Dabholkar 1997
). The concomitant decreases in GM may reflect synaptic pruning. Although subcortical GM taken as a whole was not significantly associated with age, a substantial age-related increase was seen for the thalamus, along with smaller but statistically significant decreases for the caudate and globus pallidus. Overall, the relationship of age to volumes of the subcortical GM structures was more attenuated relative to the lobar volumes, reflecting a more protracted developmental course of cortical regions, despite the involvement of the basal ganglia in higher-order cognitive functions (Middleton and Strick 2000
). In contrast with a previous report (Giedd et al. 1996
), the cerebellum showed large volumetric increases through approximately age 11 years. Whether these various age-related differences in volumes also reflect varying capacities for experience-driven plasticity is unknown.
Hemispheric asymmetries were present in nearly every regional volume. Most reflected a larger volume on the left. Particularly salient were the leftward asymmetries of the occipital lobe, especially its GM, and temporal lobe WM, consistent with torque (the opposing tendency of the left posterior/right anterior brain to protrude further than its contralateral counterpart; LeMay 1976
; Lancaster et al. 2003
). Additional prominent leftward asymmetries were seen in the caudate and globus pallidus. Some leftward hemispheric asymmetries reported here contrast with an earlier report (Giedd et al. 1996
) of rightward hemispheric asymmetries for the 4- to 18-year-old age range. Few studies have related global asymmetries to more local asymmetries or investigated their functional significance. However, a recent study reported a positive relationship of torque to asymmetries of the planum temporale (Barrick et al. 2005
), shown to be related to handedness and language lateralization (Preis et al. 1999
In contrast to these leftward asymmetries, temporal lobe GM showed a prominent rightward asymmetry, consistent with findings in adults (Jack et al. 1989
) and the tendency of the Sylvian fissure to course upward posteriorly at a steeper angle on the right than on the left, although this asymmetry may be less pronounced in children than in adults (Sowell et al. 2001
). Although such studies have primarily involved adults, alterations in cerebral asymmetries have been reported in neurodevelopmental disorders such as dyslexia (Zadina et al. 2006
), schizophrenia (Sharma et al. 1999
), and autism (Lange et al. 2010a
) and thus may hold clinical significance.
There were no significant interactions between asymmetry and age, suggesting that these volumetric asymmetries are relatively stable across the age range. The only interactions of these asymmetries with sex involved parietal GM, which showed a more pronounced leftward asymmetry in males than in females, and the putamen, which showed a more pronounced rightward asymmetry. Although speculative, the enhanced parietal asymmetry in males may be related to sex differences in certain visuospatial skills (Wolbers and Hegarty 2010
Socioeconomic indicators (family income and parental education) were not associated with variations in brain volumes in our analysis, consistent with a prior analysis indicating that total and regional brain volumes do not mediate the association between parental education and IQ in this sample (Lange et al. 2010b
). Although there are scattered reports in which associations between socioeconomic variables and structural brain development have been examined, these have generally been in the context of studies designed to address specific circumscribed brain structures in small samples of limited age range (Eckert et al. 2001
; Raizada et al. 2008
). To our knowledge, the present study is the first to conduct a comprehensive examination of regional and whole-brain volumes in relation to socioeconomic indicators in a large normative pediatric sample.
Socioeconomic status is a complex construct that has been associated with variation in life stress, social status, and neighborhood quality, as well as in child health and development (Evans and Kantrowitz 2002
; Hackman and Farah 2009
). Such associations likely reflect the combined and interactive influences of numerous environmental and biological influences, including genetic and epigenetic factors, whose effects may vary across the course of development.
Our stringent inclusion and exclusion criteria may also have contributed to the absence of association between socioeconomic indicators and volumetric MRI measures because the rate of health-based exclusions was significantly higher for lower-income participants in our study (Waber et al. 2007
). This pattern is consistent with the higher rates of morbidity, including psychiatric morbidity, typically observed in lower-income populations (Kessler et al. 1994
; Muntaner et al. 1998
; Mackenbach et al. 2008
). Indeed, a large proportion of low-income children who did not meet criteria for the study were excluded on the basis of elevated levels of behavioral symptoms, attention problems (as measured by the CBCL) being frequent. Certain family factors that were exclusionary criteria for our study, such as smoking and psychopathology in first-degree relatives, are also more prevalent in less well-educated individuals (Giovino 2002
A novel finding was a relatively small but consistent association between BMI and tissue-specific lobar brain volumes, adjusted for all other covariates, including family income and parental education. Twelve percent of the sample was classified as obese by recent childhood norms, but none had diabetes or other diseases associated with obesity. An additional 14% were classified as overweight. Both of these percentages are lower than those observed by Singh et al. (2010)
for US children in 2007, who reported a 16% obesity and 32% overweight rate for children from birth through 17 years in a large survey. Higher BMI was associated with decreased whole-brain and lobar GM and increased whole-brain and lobar WM volumes, with no net effect on TBV and no effect on subcortical GM structures, cerebellum, or brainstem. BMI findings here are similar to those reported in healthy adults, including elderly adults, which document negative associations between BMI and GM volumes in various cortical regions (Pannacciulli et al. 2006
; Gunstad et al. 2008
; Taki et al. 2008
). Obesity has also been associated with increases in WM volume in some studies (Walther et al. 2010
), an effect reported to be at least partially reversible with dieting (Haltia et al. 2007
), suggesting that some such effects are malleable. The present findings, derived from a very well-documented population-based sample, indicating that associations between BMI and brain structure are present in childhood and adolescence, are provocative. The significance of these associations, in particular their functional significance, warrants further investigation.
The relationships of brain volumes to age and sex described here are based on cross-sectional data and await refinement in future analyses of the complete, longitudinal data set. With respect to socioeconomic status, our recruitment relied on family income alone as a proxy and recruited from largely urban areas surrounding major medical centers, thereby excluding rural participants. Despite our rigorous geocoding recruitment strategy, the resulting parental educational levels were higher than expected, perhaps limiting extrapolation to less well-educated low-income populations.