Age-Related Differences in Cortical Thickness Vary by Socioeconomic Status

Abstract

Recent findings indicate robust associations between socioeconomic status (SES) and brain structure in children, raising questions about the ways in which SES may modify structural brain development. In general, cortical thickness and surface area develop in nonlinear patterns across childhood and adolescence, with developmental patterns varying to some degree by cortical region. Here, we examined whether age-related nonlinear changes in cortical thickness and surface area varied by SES, as indexed by family income and parental education. We hypothesized that SES disparities in age-related change may be particularly evident for language- and literacy-supporting cortical regions. Participants were 1148 typically-developing individuals between 3 and 20 years of age. Results indicated that SES factors moderate patterns of age-associated change in cortical thickness but not surface area. Specifically, at lower levels of SES, associations between age and cortical thickness were curvilinear, with relatively steep age-related decreases in cortical thickness earlier in childhood, and subsequent leveling off during adolescence. In contrast, at high levels of SES, associations between age and cortical thickness were linear, with consistent reductions across the age range studied. Notably, this interaction was prominent in the left fusiform gyrus, a region that is critical for reading development. In a similar pattern, SES factors significantly moderated linear age-related change in left superior temporal gyrus, such that higher SES was linked with steeper age-related decreases in cortical thickness in this region. These findings suggest that SES may moderate patterns of age-related cortical thinning, especially in language- and literacy-supporting cortical regions.

The independent and interacting effects of socioeconomic status and dual‐language use on brain structure and cognition

“…Because brain structure varies dramatically across childhood and adolescence (Brito et al, 2017; Piccolo et al, 2016), we next divided the sample into two age groups: children (ages 3–11.9, M = 8.4, SD = 2.1, N = 237) and adolescents (ages 12 – 20.9, M = 17.2, SD = 2.5, N = 325). Controlling for covariates (sex, GAF, and scanner type), group analysis for the younger children indicated no significant main effects of income ( p = .20), or dual-language use ( p = .40), and no significant income x dual-language interaction ( p = .71) for cortical SA.…”

“…A propensity score was calculated via logistic regression model with age, sex, family income, parental educational attainment, and oral reading score as the covariates, as these variables have been reported to be related to differences in brain structure and cognitive skills during childhood within this dataset (Brito, Piccolo, & Noble, 2017; Noble et al, 2015; Piccolo et al, 2016). Reading score was included to rule out the possibility of any structural brain differences being attributed to reading ability (He et al, 2013).…”

“…However, SES differences in brain structure may differ by age. For example, Piccolo and colleagues (2016) reported that among children from more disadvantaged families, cortical thickness (CT) of the cerebral cortex shows steep age-related differences earlier in childhood, and then levels off during adolescence, with children from more advantaged families showing a more gradual decline in thickness with age. Hanson et al (2013) reported slower trajectories of cortical volume growth for low-income children, particularly in the frontal and parietal lobes, compared to higher-income children.…”

All Wrapped Up: Environmental Effects on Myelination

“…Environmental resources like healthcare, education, and housing have a cause and effect relationship on the brain throughout life, and individual differences in cognition, emotion, and psychological well-being can be attributed to deviations in these social parameters [155,156]. …”

Lower total and regional grey matter brain volumes in youth with perinatally-acquired HIV infection: Associations with HIV disease severity, substance use, and cognition

“…Previous studies have demonstrated that altered grey matter measures such as volume, cortical thickness, and surface area in distributed cortical and subcortical regions are associated with socioeconomic status (Hair et al, 2015; Jednoróg et al, 2012; Noble et al, 2015; Piccolo et al, 2016). Despite differences in socioeconomic status between our HIV-unexposed and uninfected youth and PHIV youth cohorts, regional and total grey matter volume differences persisted after controlling for socioeconomic status.…”