Distinct influence of parental occupation on cortical thickness and surface area in children and adolescents: Relation to self‐esteem

Khundrakpam, Budhachandra; Choudhury, Subhashree; Vainik, Uku; Al‐Sharif, Noor; Bhutani, Neha; Jeon, Seun; Gold, Ian; Evans, Alan C.

doi:10.1002/hbm.25169

Cited by 15 publications

(16 citation statements)

References 67 publications

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“…For example, it was found in a previous study that those from families with higher levels of parental occupation (titles falling into the category of "higher executives of large concerns, proprietors, and major professionals") were shown to have larger cortical surface areas than those from families with lower levels of parental occupation (titles falling into the category of unskilled laborers). 38 Likewise, one of our previous studies found that a higher level of parental education is positively associated with increased cortical surface areas and higher reading levels among children. 24 This occurrence is due to the distal effects that SES has on environments surrounding a child.…”

Section: Discussionmentioning

confidence: 76%

Developmental Cost of Being Asian but Living in the United States: Diminished Returns of Household Income on Cortical Surface Area in 9-10 Year Old Children

Assari

Lee

2022

Int J Travel Med Glob Health

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Introduction: While socioeconomic status (SES) indicators such as household income are known to be associated with larger cortical surface area, recent research on Marginalization-related Diminished Returns (MDRs) suggests that family SES indicators such as household income may have weaker effects on brain function and structure for non-White (marginalized) than White (privileged) families: a pattern that reflects structural and societal inequalities deeply intertwined into the United States social fabric. Methods: This is a cross-sectional study that used baseline data from the Adolescent Brain Cognitive Development (ABCD) study. Data was collected between 2016 and 2018. Overall, 6039 9–10-year-old children entered our analysis. The independent variable was household income. The moderator was race. The primary outcome was the overall cortical surface area. Age, sex, and family structure were the covariates. We used mixed effects regression models that adjusted for data analysis because ABCD data is nested into families, centers, and US states. Results: While high household income was associated with larger cortical surface area, this effect was weaker for Asian than non-Hispanic White children. This racial heterogeneity in the effects of household income on cortical surface area was documented by a statistically significant interaction between race and household income on cortical surface area. Conclusion: For American children, household income does not similarly correlate with cortical surface area of diverse racial groups. Brain development in the US is not solely a function of SES (availability of resources) but also how social groups are racialized and treated in the society. In the US, race, as a proxy of racism, limits how much SES can affect brain structures such as cerebral cortex. Due to racialization, segregation, discrimination, and marginalization, racial minority children may experience weaker effects of SES. Structural inequalities should be addressed to equalize the return of SES resources across racially diverse families.

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Section: Discussionmentioning

confidence: 76%

Developmental Cost of Being Asian but Living in the United States: Diminished Returns of Household Income on Cortical Surface Area in 9-10 Year Old Children

Assari

Lee

2022

Int J Travel Med Glob Health

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“…In recent years, several studies focussed on the role that parents play in children's development of numerical competencies [16][17][18]. Here, studies differ in their usage of various SES measures [10,19], and the most common aspects (i.e., parental occupation, education, and income) seem to be highly correlated [20,21].…”

Section: Parental Occupation and Other Aspects Of Socioeconomic Statusmentioning

confidence: 99%

“…Here, the SES can be conceptualized as a multidimensional construct that acts as an indicator of a family's economic and social resources. SES is mostly measured with three objective parental factors: income, occupation, and education [10]. In addition, neighbourhood, social standing, and prestige are often considered as SES estimates as well [1,10].…”

Section: Introduction 1family's Socioeconomic Status and Children's Early Numerical Competenciesmentioning

confidence: 99%

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Parental (STEM) Occupations, the Home Numeracy Environment, and Kindergarten Children’s Numerical Competencies

et al. 2021

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Children’s early numerical competencies are of great importance for later academic achievement. Young children gain these competencies in the context of the home numeracy environment (HNE). Additionally, child characteristics and families’ socioeconomic status (SES) are associated with children’s competencies. In this study, we investigated parents’ occupations (i.e., STEM or non-STEM occupation) as a specific aspect of the SES to understand whether parental occupations are associated with children’s numerical competencies and whether such an association may depend on the HNE. We analysed data from a sample of N = 190 children (Mage = 63.58 months; SD = 4.41) at two measurement points. Correlational analyses and crossed-lagged models were conducted to predict children’s numerical competencies by a global measure of the HNE and parental STEM vs. non-STEM occupations. We found significant associations between parents’ learned and current occupations and the HNE. Further, significant associations between parents’ learned occupations and children’s numerical competencies were observed. However, parents’ current occupations were not significantly associated with children’s numerical competencies. Consequently, more specific facets of the SES instead of a global measure seem to be associated with children’s numerical competencies. A greater focus on specific differences between family characteristics and their potential impact on children’s HNE and the development of their numerical competencies seems expedient.

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“…The raw T1-weighted imaging data for the PING study are publicly shared (https://nda.nih.gov/) for a subset of the sample (n = 934). The only difference between the full PING sample and the subsample with raw T1-weighted imaging data was that the full PING sample was older on average than the subsample (Khundrakpam, Choudhury, et al, 2020). We used the CIVET processing pipeline (https://mcin.ca/technology/civet/) developed at the Montreal Neurological Institute to compute CT measurements at 81,924 regions covering the entire cortex.…”

Section: Image Acquisition and Preprocessingmentioning

confidence: 99%

Educational Attainment Polygenic Scores, Socioeconomic Factors, and Cortical Structure in Children and Adolescents

Merz

Strack

Hurtado

et al. 2021

Preprint

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Background: Genome-wide polygenic scores for educational attainment (PGS-EA) and socioeconomic factors, which are correlated with each other, have been consistently associated with academic achievement and general cognitive ability in children and adolescents. Yet, the independent associations of PGS-EA and socioeconomic factors with specific underlying factors at the neural and neurocognitive levels are not well understood. The goal of this study was to examine the unique contributions of PGS-EA and parental education to cortical thickness (CT), cortical surface area (SA), and neurocognitive skills in children and adolescents. Methods: Participants were typically developing children and adolescents (3-21 years of age; 53% male; N = 391). High-resolution, T1-weighted magnetic resonance imaging data were acquired. PGS-EA were computed based on the most recent genome-wide association study of educational attainment. Sustained attention, inhibitory control, working memory, vocabulary, and episodic memory were measured. Results: PGS-EA and parental education were independently and significantly associated with SA, vocabulary, and attention outcomes but were not associated with CT. Vertex-wise analyses indicated that higher PGS-EA was significantly associated with greater SA in the left medial orbitofrontal gyrus and inferior frontal gyrus after accounting for parental education. Higher parental education was significantly associated with greater SA in the left parahippocampal gyrus after accounting for PGS-EA. Conclusions: These findings suggest that education-linked genetics may influence SA, particularly in certain frontal regions, leading to variability in academic achievement. Results suggested genetic confounding in associations between parental education and SA in children and adolescents, with these associations remaining significant after controlling for PGS-EA.

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Distinct influence of parental occupation on cortical thickness and surface area in children and adolescents: Relation to self‐esteem

Cited by 15 publications

References 67 publications

Developmental Cost of Being Asian but Living in the United States: Diminished Returns of Household Income on Cortical Surface Area in 9-10 Year Old Children

Developmental Cost of Being Asian but Living in the United States: Diminished Returns of Household Income on Cortical Surface Area in 9-10 Year Old Children

Parental (STEM) Occupations, the Home Numeracy Environment, and Kindergarten Children’s Numerical Competencies

Educational Attainment Polygenic Scores, Socioeconomic Factors, and Cortical Structure in Children and Adolescents

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