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Family income, parental education and brain structure in children and adolescents

Abstract

Socioeconomic disparities are associated with differences in cognitive development. The extent to which this translates to disparities in brain structure is unclear. We investigated relationships between socioeconomic factors and brain morphometry, independently of genetic ancestry, among a cohort of 1,099 typically developing individuals between 3 and 20 years of age. Income was logarithmically associated with brain surface area. Among children from lower income families, small differences in income were associated with relatively large differences in surface area, whereas, among children from higher income families, similar income increments were associated with smaller differences in surface area. These relationships were most prominent in regions supporting language, reading, executive functions and spatial skills; surface area mediated socioeconomic differences in certain neurocognitive abilities. These data imply that income relates most strongly to brain structure among the most disadvantaged children.

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Figure 1: Parent education is linearly associated with cortical surface area (N = 1,099).
Figure 2: Family income is logarithmically related to cortical surface area (N = 1,099).
Figure 3: Parental education is quadratically associated with left hippocampal volume (N = 1,099).

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Acknowledgements

This work was funded by the Annie E. Casey Foundation and the GH Sergievsky Center (K.G.N.) and by the following grants: RC2 DA029475 to T.L.J., L.C., T.M.E., A.M.D. and S.S.M. R01 HD053893 to E.R.S., R01 MH087563 to E.R.S. and R01 HD061414 to T.L.J.

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Authors and Affiliations

Authors

Contributions

K.G.N. developed the theory, conducted analyses, wrote the introduction, results, discussion and methods. S.M.H. compiled/collected data, compiled methods, and created tables and figures. N.H.B. conducted analyses, wrote a portion of the results and edited the manuscript. A.M.D., H.B. and J.M.K. developed the portal in which most analyses were conducted and assisted with interpretation of results and images. E.K. compiled and lent expertise regarding the imaging data and created figures. O.L., N.J.S., C.S.B. and S.S.M. performed analysis of genetic data. D.G.A., P.V.Z., D.N.K., L.C., B.J.C., N.A., T.K., J.A.F., J.R.G., W.E.K. and S.M. oversaw participant accrual, behavioral assessment and imaging at data collection sites. T.M.E. developed and maintained MRI sequences and protocols, and ensured quality of MRI data across sites and time. E.R.S. and T.L.J. contributed to theory development and interpretation of results, oversaw participant accrual, behavioral assessment and imaging at one site, and edited the manuscript. L.C. was involved in designing the research protocol and supervised the data collection at one site.All of the authors approved the final version of the manuscript.

Corresponding authors

Correspondence to Kimberly G Noble or Elizabeth R Sowell.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Family Income is Related to Cortical Surface Area at Stringent FDR Thresholds (N=1099).

When adjusting for age, age2, scanner, sex, and genetic ancestry, ln(family income) was significantly associated with surface area in widespread regions of children’s bilateral frontal, temporal, and parietal cortices as well as right occipital cortex. Relationships were strongest in bilateral inferior temporal, insula and inferior frontal gyrus, and in the right occipital and medial prefrontal cortex Results are shown thresholded at A. the traditional p < 0.05 threshold (FDR-corrected); B. at p <.01 (FDR-corrected); and C. at the stringent threshold of p < 0.001 (FDR-corrected), where results remained significant bilaterally in the insula, temporal pole, and anterior and posterior cingulate, and in the right dorsal frontal region extending onto the medial surface.

Source data

Supplementary Figure 2 Surface Area Partially Mediates the Association between Family Income and Cognitive Control (N=1074).

Multiple regression analyses revealed that, when adjusting for age, age2, scanner, sex, and GAF, the direct effect of income on flanker scores (β=0.050, t(1074)= 2.68, p =.007) was reduced when controlling for surface area (β=0.043, t(1074) = 2.27, p =.023). A Sobel test indicated that this reduction was significant, suggesting partial mediation (Sobel z = 2.4, p =. 02).

Source data

Supplementary Figure 3 Surface Area Partially Mediates the Association between Family Income and Working Memory (N=1084).

Multiple regression analyses revealed that, when adjusting for age, age2, scanner, sex, and GAF, the direct effect of income on working memory scores (β= 0.069, t(1084) =3.77, p = 0.0002) was reduced when controlling for surface area (β= 0.061, t(1084) = 3.31, p = 0.001). The Sobel test was significant, suggesting partial mediation (Sobel z = 2.6, p =. 009).

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Supplementary Figures 1–3 and Supplementary Tables 1–4 (PDF 335 kb)

Supplementary Methods Checklist (PDF 398 kb)

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Noble, K., Houston, S., Brito, N. et al. Family income, parental education and brain structure in children and adolescents. Nat Neurosci 18, 773–778 (2015). https://doi.org/10.1038/nn.3983

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