Robust studies of human brain development require large, diverse pediatric samples1 to inform personalized medicine in pediatrics. Historically, neuroimaging research has overrepresented non-Hispanic White (hereinafter, White), wealthier populations, omitting both participants and researchers from marginalized racial, ethnic, and socioeconomic groups.2 Diversity and inclusion in pediatric research populations is vital, as is careful consideration of how social determinants of health contribute to downstream individual differences in neurodevelopmental trajectories. Despite progress describing normative (ie, average) adolescent neurodevelopment, individual variability remains poorly characterized. We investigated individual variability across sociodemographic factors in key facets of white and gray matter development, estimated from annual rates of change across early adolescence in the nationwide Adolescent Brain Cognitive Development (ABCD) Study.
This cohort study used neuroimaging and demographic data from ABCD Study release 4.0, collected between 2016 and 2020 from 4131 to 7115 children (at ages 9-10 and 11-13 years) (eTable in Supplement 1). Brain change variance was compared across caregiver-reported sociodemographic factors, including child race and ethnicity, household income, and caregiver education.3 Caregivers and youths gave written consent and assent in accordance with institutional review board policy at each site. We calculated variance in annualized percent changes in cortical thickness, functional (blood oxygenation level–dependent) fluctuations, and white matter fractional anisotropy (FA) over 2 years (eMethods in Supplement 1). The Fligner-Killeen test was used to assess unequal variance in change scores across sociodemographic factors, with heteroscedasticity at α < .01 (family-wise error-rate corrected).4 The study followed the STROBE reporting guideline. Data analysis was performed from December 2021 to September 2022 using SciPy, version 1.9.1, in Python, version 3.8.9 (Python Software Foundation).
This study included 7115 youths (3300 [46%] girls and 3815 [54%] boys; mean [SD] age, 9.9 [0.62] years at baseline data collection). Youths were Hispanic (1383 [19%]), non-Hispanic Black (924 [13%]), White (3938 [55%]), or other race or ethnicity (870 [12%]). We identified heteroscedasticity of annualized brain change across social strata from youths aged 8.9 to 13.0 years. Significant differences in variance were observed between racial and ethnic groups in rates of change in cortical thickness (81% of brain regions), functional fluctuations (63%), and white matter tract FA (63% of tracts) (Figure 1A). Household income (Figure 1B) and caregiver educational attainment also exhibited significant albeit less widespread heterogeneous variance, with heteroscedasticity of changes in cortical thickness (65% and 46%), white matter FA (49% and 23%), and functional fluctuations (55% and 58%), respectively. Differences in brain change variance were neuroanatomically similar across sociodemographic factors.
Across sociodemographic factors, the greatest variance in annual rates of brain development was observed between structurally disadvantaged individuals (eg, racial and ethnic minority children from low-income households with fewer years of caregiver education). The least variance in annual percent change was seen between structurally advantaged individuals (eg, White children from high-income households with greater caregiver education) (Figure 2).
We observed substantially different magnitudes of variance in annual rates of neurodevelopmental change across sociodemographic groups during early adolescence, which were greater than previously reported differences in variance regarding age, sex, and puberty in this same pediatric cohort.5 These findings suggest greater interindividual differences in neurodevelopment within marginalized and structurally disadvantaged groups compared with their more advantaged peers, potentially extending the previously identified variance-reducing effect of income6 to brain development.
Overlooking differences in neurodevelopmental variance across social and economic backgrounds may obscure determinants of brain health. Thus, population-level developmental neuroscience must clarify how individuals differ on key outcomes, both between and within socially stratified groups, especially in this dynamic and variable phase of early adolescence. Although this cohort study includes thousands of participants from across the US, it is limited by relying on coarse delineations of sociodemographic strata, with fewer participants from lower-income and racial and ethnic minority backgrounds compared with the general population. Future investigations are needed to develop and test theoretical models that elucidate how structural forces unfolding across generations shape individual children’s patterns of brain maturation.
Accepted for Publication: March 8, 2024.
Published: May 8, 2024. doi:10.1001/jamanetworkopen.2024.10441
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2024 Bottenhorn KL et al. JAMA Network Open.
Corresponding Author: Katherine L. Bottenhorn, PhD, or Megan M. Herting PhD, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, 1845 N Soto St, Los Angeles, CA 90032 (bottenho@usc.edu or herting@usc.edu).
Author Contributions: Drs Bottenhorn and Herting had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Bottenhorn, Laird, Herting.
Acquisition, analysis, or interpretation of data: Bottenhorn, Cardenas-Iniguez, Schachner, Rosario, Mills, Herting.
Drafting of the manuscript: Bottenhorn, Schachner, Herting.
Critical review of the manuscript for important intellectual content: All authors.
Statistical analysis: Bottenhorn, Cardenas-Iniguez.
Obtained funding: Laird, Herting.
Administrative, technical, or material support: Bottenhorn.
Supervision: Laird, Herting.
Conflict of Interest Disclosures: Dr Herting reported receiving grants from the National Institutes of Health (NIH) and the Health Effects Institute during the conduct of the study. No other disclosures were reported.
Funding/Support: This study was supported by NIH grants R01ES032295 and R01ES031074. Dr Cardenas-Iniguez was supported by NIH grant T32ES013678.
Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Disclaimer: This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or Adolescent Brain Cognitive Development (ABCD) Study investigators.
Data Sharing Statement: See Supplement 2.
Additional Contributions: We extend special thanks to all of the children and families for their participation in the ABCD Study. We gratefully acknowledge Jade Li, University of Southern California, for her help with creating the white matter tract visualizations. No financial compensation was provided for this contribution.
Additional Information: Data used in the preparation of this article were obtained from the ABCD Study (https://abcdstudy.org), held in the National Institute of Mental Health (NIMH) Data Archive. A listing of participating sites and a complete listing of ABCD Study investigators can be found at https://abcdstudy.org/consortium_members/. Dr Cardenas-Iniguez acknowledges scholars involved in the NIH-funded Neuroscience Scholars program (grant R25NS089462), the Broadening the Representation of Academic Investigators in NeuroScience program (grant R25NS094094), and the Diversifying CNS program (grant R25NS117356) as well as the NIMH-funded workshops (grants R25MH125545 and R25MH120869) for creating a supportive network of ABCD Study users. The ABCD Study is supported by the NIH and additional federal partners under award numbers U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123, and U24DA041147. A full list of ABCD Study supporters is available at https://abcdstudy.org/federal-partners.html.