Parental Education and Childhood Brain and Behavioral Development
Sean Deoni1,2, Holly Dirks2, Jonathan O'Muircheartaigh3, and Douglas C Dean4

1CHILD Lab, Children's Hospital, Colorado, Aurora, CO, United States, 2Advanced Baby Imaging Lab, Brown University, Providence, RI, United States, 3Neuroimaging, King's College, London, London, United Kingdom, 4Waisman Lab for Brain Imaging and Behavior, University of Wisconsin Madison, Madison, WI, United States


It is well established that family socioeconomic status (SES), related to parental education level, occupation, and income, is associated with differences in offspring educational outcomes and cognitive abilities. However, while brain imaging studies in older children have revealed altered brain structure associated with SES, the influence of SES on infant and childhood brain development remain unclear. Here we investigated longitudinal trajectories of brain and cognitive development in a large cohort of typically-developing children from 2 months to 6 years of age. Results reveal diverging developmental trends associated with parental education (PE) level even when controlling for common confounds.


Infancy and early childhood are sensitive periods of brain development, during which the structural and functional networks subserving nearly all cognitive and behavioral functioning are established. Refinement of these networks through genetic and environmental influences help to set the foundation for later skill acquisition and outcomes, including academic achievement. Of the various influences, disparities in socioeconomic status (SES), including parental education level (PE), family income, and social standing are associated with differences in child education outcome and cognitive ability (e.g., IQ). Brain imaging studies of older children have revealed links between SES, brain structure, and cognitive function. However, the relationships between SES and brain and cognitive development remain unclear, particularly throughout early childhood when brain development is most rapid and sensitive to external factors. In this work, we sought to examine the relationship between PE and early childhood brain and cognitive development, controlling for factors such as family size, ethnicity, marital status, and infant feeding.


598 longitudinal MRI and neurocognitive datasets were obtained from 179 (98 female) healthy and typically-developing infants and young children, 2 months through 6 years of age. Mean interval between follow-up scans was 300 days. To assess brain growth and white matter myelination, mcDESPOT [1] imaging was performed during non-sedated sleep. The Early Learning Composite (ELC) from the Mullen Scales of Early Learning [2] was used as a measure of general cognitive ability, with each child assessed within 7 days of successful scanning. The ELC is an age-normalised measure, with a mean of 100 and standard deviation of 15. SES and PE were measured using the 4-factor Hollingshead scale, with PE denoted by a 7-level scale (ranging from 1=less than 7th grade to 7=graduate degree). In addition, child and family history information, including ethnicity, marital status, gestation duration, birth weight, family size, child parity, languages spoken in home, infant feeding practice, and length of exclusive breastfeeding.

Following routine mcDESPOT processing [3] and calculation of their myelin water fraction (MWF) maps, data from each child was aligned to a common template [4]. From our large study population, 33 (18 female) were selected who's mother had low PE (high school graduate or below); and 53 matched children whose mother had high PE (university degree and higher). Mean trajectories of MWF and cognitive (ELC) development we calculated using a mixed effects approach assuming a modified gompertz model for MWF and linear model of ELC [3]. Groups were matched in terms of mean age, gender and ethnicity ratio, gestation duration, birth weight, family size, parity, spoken languages, and breastfeeding practice.

In addition to group comparisons, the temporal influence of PE on brain and cognitive development was examined using sliding window correlation across a fixed age window of 6 months.


From our longitudinal analysis, we found that children stratified by maternal education level (up to high school graduate vs. those with a graduate degree) displayed marked differences in cognitive development (Fig. 1a) and brain myelination (Fig. 1b) even when controlling for common confounds. In the case of ELC, the difference in ability between the high and low PE children at 5 years of age is approx. 2 standard deviations, with the high PE children 1 standard deviation above the norm, and the low PE children 1 standard deviation below. Exploring the temporal relationship between PE on cognitive ability and brain myelination across all children, we found an evolving relationship (Fig. 2) with an increasing influence with age that reaches significance at approx. 2 years of age. For cognitive ability, this influence remains significant for the duration of childhood; however, after the peak at 2 years, its influence on brain myelin diminishes with age.

Presented results provide the first insight into the influence of SES and maternal education on longitudinal brain development throughout infancy and early childhood, and its association with evolving cognitive function and ability. Results are in line with prior investigations [e.g., 5], however are surprising given they are seen in children raised in a resource-rich community (Providence, RI, USA). While they suggest PE has a significant influence on brain and cognitive development throughout early childhood, they may also suggest an early window of opportunity, prior to 1.5-2 years of age, when interventions may be most effective in lessening this influence. Further research is required to delve further into aspects of SES (e.g., words spoken in home, nutrition, mother-child bonding) to determine exactly what aspects of SES are principally driving this influence.


The authors acknowledge the financial support of the Bill & Melinda Gates Foundation for this research.


[1] Deoni SCL, et al. Magn Reson Med. 2008 :1372–87. [2] Mullen EM. Mullen scales of early learning. 1995. [3] Dean DC, et al. Brain Struct Funct. 2014. [4] Deoni SCL, et al. Neuroimage. 2012, [5] Noble KG et al. Nature Neuroscience. 2015.


Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)