Assessment of Parent Income and Education, Neighborhood Disadvantage, and Child Brain Structure

Rakesh, Divyangana; Zalesky, Andrew; Whittle, Sarah

doi:10.1001/jamanetworkopen.2022.26208

Cited by 44 publications

(41 citation statements)

References 84 publications

(175 reference statements)

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“…Cognitive performance also likely has both social (i.e., school, family) and neurobiological (i.e., brain-supported functioning) foundations that would position cognition as either a contributor to or consequence of brain development [26][27][28] , and future research may dissociate these effects using more specific measurements. Additionally, because morphometry in certain regions connected to the SLF (e.g., superior frontal-parietal cortices), CST (e.g., precentral gyrus), and Fmaj (e.g., occipital lobes) has similarly exhibited associations with SES and cognition in children [12][13][14]28,30,32,33 , our findings in white matter might reflect developmental interactions with gray matter instead of an isolated process 71 .…”

Section: Discussion (1167 Words)mentioning

confidence: 84%

“…These studies used obesity measures as a proxy for diet and exercise 13 , and cognitive performance as a proxy for the social, sensory, and cognitive influence the brain, potentially through different pathways. Recent findings suggest that SES indicators at both neighborhood-level (e.g., area deprivation index) and household-level (e.g., income, parental education), though correlated, do independently relate to children's brain morphology and functional networks 12,13,[29][30][31][32][33] . In terms of SES, families having the same income level may have access to different neighborhoods due to differences in local cost of living and/or structural racism barriers 8 .…”

Section: Introduction (737 Words)mentioning

confidence: 99%

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Associations between socioeconomic status and white matter microstructure in children: indirect effects via obesity and cognition

Cai

Taylor

et al. 2023

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Importance Both neighborhood and household socioeconomic disadvantage relate to negative health outcomes and altered brain structure in children. It is unclear whether such findings extend to white matter development, and via what mechanisms socioeconomic status (SES) influences the brain. Objective To test independent associations between neighborhood and household SES indicators and white matter microstructure in children, and examine whether body mass index and cognitive function (a proxy of environmental cognitive/sensory stimulation) may plausibly mediate these associations. Design This cross-sectional study used baseline data from the Adolescent Brain Cognitive Development (ABCD) Study, an ongoing 10-year cohort study tracking child health. Setting School-based recruitment at 21 U.S. sites. Participants Children aged 9 to 11 years and their parents/caregivers completed baseline assessments between October 1st, 2016 and October 31st, 2018. Data analysis was conducted from July to December 2022. Exposures Neighborhood disadvantage was derived from area deprivation indices at primary residence. Household SES indicators were total income and the highest parental education attainment. Main Outcomes and Measures Thirty-one major white matter tracts were segmented from diffusion-weighted images. The Restriction Spectrum Imaging (RSI) model was implemented to measure restricted normalized directional (RND; reflecting oriented myelin organization) and isotropic (RNI; reflecting glial/neuronal cell bodies) diffusion in each tract. Obesity-related measures were body mass index (BMI), BMI z-scores, and waist circumference, and cognitive performance was assessed using the NIH Toolbox Cognition Battery. Linear mixed-effects models tested the associations between SES indicators and scanner-harmonized RSI metrics. Structural equation models examined indirect effects of obesity and cognitive performance in the significant associations between SES and white mater microstructure summary principal components. Analyses were adjusted for age, sex, pubertal development stage, intracranial volume, and head motion. Results The analytical sample included 8842 children (4299 [48.6%] girls; mean age [SD], 9.9 [0.7] years). Greater neighborhood disadvantage and lower parental education were independently associated with lower RSI-RND in forceps major and corticospinal/pyramidal tracts, and had overlapping associations in the superior longitudinal fasciculus. Lower cognition scores and greater obesity-related measures partially accounted for these SES associations with RSI-RND. Lower household income was related to higher RSI-RNI in almost every tract, and greater neighborhood disadvantage had similar effects in primarily frontolimbic tracts. Lower parental education was uniquely linked to higher RSI-RNI in forceps major. Greater obesity-related measures partially accounted for these SES associations with RSI-RNI. Findings were robust in sensitivity analyses and mostly corroborated using traditional diffusion tensor imaging (DTI). Conclusions and Relevance These cross-sectional results demonstrate that both neighborhood and household contexts are relevant to white matter development in children, and suggest cognitive performance and obesity as possible pathways of influence. Interventions targeting obesity reduction and improving cognition from multiple socioeconomic angles may ameliorate brain health in low-SES children.

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Section: Discussion (1167 Words)mentioning

confidence: 84%

Section: Introduction (737 Words)mentioning

confidence: 99%

Associations between socioeconomic status and white matter microstructure in children: indirect effects via obesity and cognition

Cai

Taylor

et al. 2023

Preprint

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“…This could indicate that cortical thinning across childhood and adolescence might be affected more by genetic factors, while surface area (Strike et al, 2019) and GWC could be more sensitive to environmental impact. However, a recent paper by Rakesh et al (2022) reported associations between neighborhood disadvantage and local cortical thickness.…”

Section: Discussionmentioning

confidence: 96%

Parental education and income are linked to offspring cortical brain structure and psychopathology at 9-11 years

Norbom

Rokicki

Eilertsen

et al. 2023

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A childs socioeconomic environment can shape central aspects of their life, including vulnerability to mental disorders. Negative environmental influences in youth may interfere with the extensive and dynamic brain development occurring at this time. Indeed, there are numerous yet diverging reports of associations between parental socioeconomic status (SES) and child cortical brain morphometry. Most of these studies have used single metric- or unimodal analyses that downplay the probable scenario that separate sources of variability, from numerous independent biological pathways, are the basis for SES-related cortical differences in youth. To comprehensively capture such variability, using data from 9758 children aged 8.9-11.1 years from the ABCD Study, we employed linked independent component analysis (LICA) and fused vertex-wise cortical thickness, surface area, curvature and grey-/white-matter contrast (GWC). LICA revealed 70 uni- and multimodal components. We then assessed the linear relationships between parental education, parental income and each of the cortical components, controlling for age, sex, genetic ancestry, and family relatedness. We also assessed whether cortical structure moderated the negative relationships between parental SES and child general psychopathology. Parental education and income were both associated with larger surface area and higher GWC globally, in addition to local increases in surface area and to a lesser extent bidirectional GWC and cortical thickness patterns. The negative relation between parental income and child psychopathology were attenuated in children with a multimodal pattern of larger frontal- and smaller occipital surface area, and lower medial occipital thickness and GWC. In conclusion, structural brain MRI is sensitive to SES-related variability in childhood, and in low-income families, having a more developed cortex across MRI metrics, is beneficial for mental health.

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“…Prior studies have linked specific measures of household SES to differences in youth behavior (Lahelma et al, 2006; Lorant et al, 2003; McLaughlin et al, 2011) and brain structure (Lawson et al, 2013; Noble et al, 2015, 2012; Rakesh et al, 2022), but little is known about household-level SES-related effects on brain predicted aging. Herein, we show that our previously derived SES and psychopathology-blind brain age metrics (Zhao et al, 2019) are in fact associated with specific components of household SES and anxiety/depression symptoms.…”

Section: Discussionmentioning

confidence: 99%

“…Lower SES has also been shown to associate with lower global white matter volumes in one study (McDermott et al, 2019) but not in others (Jednoróg et al, 2012; Mackey et al, 2015). In line with differing associations between SES components and mental health outcomes, parent education and income differ in their ability to predict cortical thickness across the brain (Lawson et al, 2013; Noble et al, 2015, 2012; Rakesh et al, 2022) as well as hippocampal volume (Noble et al, 2015). These findings suggest different SES components may be biologically distinct and could help explain how SES components result in divergent mental health outcomes.…”

Section: Introductionmentioning

confidence: 99%

Relative Brain Age Is Associated with Socioeconomic Status and Anxiety/Depression Problems in Youth

Cohen

Ramphal

DeSerisy

et al. 2022

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Socioeconomic status (SES) has been linked to differences in brain structure and psychiatric risk across the lifespan. Despite many neuropsychiatric disorders emerging in childhood, few studies have examined the influence of SES on brain aging and psychopathology in youth. We re-analyzed relative brain age (RBA) data from the Healthy Brain Network to examine the influence of SES components (parent education, occupation, household income-to-needs ratio (INR), public assistance enrollment) on RBA. RBA was previously determined using covariation patterns for cortical morphology, white, and subcortical gray matter volumes without SES in predictive models. We also examined associations between RBA and psychiatric symptoms (child behavior checklist). Full case analysis included 470 youth (5-17 years; 61.3% male), self-identifying as White (55%), African American (15%), Hispanic (9%), or multiracial (17.2%). Mean household income was 3.95+/-2.33 (Mean+/-SD) times the federal poverty threshold. Multiple linear regression examined if 1) SES components associated with RBA, and 2) RBA associated with psychiatric symptoms. Models covaried for sex, scan location, and parent psychiatric diagnoses. RBA associated with public assistance (p = 0.03), parent occupation (p = 0.01), and parent psychiatric diagnosis (p = 0.01), but not with INR and parent education. Parent occupation (p = 0.02) and RBA (p = 0.04) associated with CBCL anxiety/depression scores. Components of SES associated with brain aging, underscoring the risk of omitting these factors in developmental brain research. Further, delayed brain aging was associated with low parental occupational prestige and child anxiety/depression scores, suggesting a possible biological pathway from SES to mental health risk.

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Assessment of Parent Income and Education, Neighborhood Disadvantage, and Child Brain Structure

Cited by 44 publications

References 84 publications

Associations between socioeconomic status and white matter microstructure in children: indirect effects via obesity and cognition

Associations between socioeconomic status and white matter microstructure in children: indirect effects via obesity and cognition

Parental education and income are linked to offspring cortical brain structure and psychopathology at 9-11 years

Relative Brain Age Is Associated with Socioeconomic Status and Anxiety/Depression Problems in Youth

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