Socioeconomic Status and the Brain: Mechanistic Insights from Human and Animal Research

Center for Cognitive Neuroscience, Center for Neuroscience and Society, Department of Psychology, University of Pennsylvania, 3720 Walnut Street, Room B51, Philadelphia, Pennsylvania 19104-6241, USA.
Nature Reviews Neuroscience (Impact Factor: 31.43). 09/2010; 11(9):651-9. DOI: 10.1038/nrn2897
Source: PubMed


Human brain development occurs within a socioeconomic context and childhood socioeconomic status (SES) influences neural development--particularly of the systems that subserve language and executive function. Research in humans and in animal models has implicated prenatal factors, parent-child interactions and cognitive stimulation in the home environment in the effects of SES on neural development. These findings provide a unique opportunity for understanding how environmental factors can lead to individual differences in brain development, and for improving the programmes and policies that are designed to alleviate SES-related disparities in mental health and academic achievement.

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    • "Another direct mechanism is environmental impoverishment, which may include less stimulation, less exposure to language, poorer nutrition, and decreased access to educational inputs (Evans, 2004;Noble et al., 2005). Stress in the family context also affects children's developing executive control via its effects on parenting (Conger et al., 2002;Hackman, Farah, & Meaney, 2010;). However, the emerging literature has not fully addressed whether differential recruitment or activation of the neural circuitry underlying executive control accounts for the income differences often observed in performance on executive control measures. "
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    ABSTRACT: This study aimed to specify the neural mechanisms underlying the link between low household income and diminished executive control in the preschool period. Specifically, we examined whether individual differences in the neural processes associated with executive attention and inhibitory control accounted for income differences observed in performance on a neuropsychological battery of executive control tasks. The study utilized a sample of preschool-aged children ( N = 118) whose families represented the full range of income, with 32% of families at/near poverty, 32% lower income, and 36% middle to upper income. Children completed a neuropsychological battery of executive control tasks and then completed two computerized executive control tasks while EEG data were collected. We predicted that differences in the event-related potential (ERP) correlates of executive attention and inhibitory control would account for income differences observed on the executive control battery. Income and ERP measures were related to performance on the executive control battery. However, income was unrelated to ERP measures. The findings suggest that income differences observed in executive control during the preschool period might relate to processes other than executive attention and inhibitory control.
    Full-text · Article · Jan 2016 · Development and Psychopathology
    • "Children growing up in low SES families are more likely to be exposed to risks to physical health, such as inadequate nutrition, poor housing conditions, and exposure to toxins, which are all factors impairing brain and cognitive development (Brooks- Gunn & Duncan, 1997; Evans & Kantrowitz, 2002). In addition, lack of cognitively stimulating resources and poor parenting quality are observed more often in low SES households which may also contribute to delayed or impaired intellectual development (Blair & Raver, 2012; Hackman, Farah & Meaney, 2010; Hoff, 2003; Raviv, Kessenich & Morrison, 2004). Finally, disparities among different SES backgrounds may also extend beyond the household boundaries. "
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    ABSTRACT: Socioeconomic risks (SES risks) are robust risk factors influencing children's academic development. However, it is unclear whether the effects of SES on academic development operate universally in all children equally or whether they vary differentially in children with particular characteristics. The current study aimed to explore children's temperament as protective or risk factors that potentially moderate the associations between SES risks and academic development. Specifically, latent growth modeling (LGM) was used in two longitudinal datasets with a total of 2236 children to examine how family SES risks and children's temperament interactively predicted the development of reading and math from middle childhood to early adolescence. Results showed that low negative affect, high effortful control, and low surgency mitigated the negative associations between SES risks and both reading and math development in this developmental period. These findings underline the heterogeneous nature of the negative associations between SES risks and academic development and highlight the importance of the interplay between biological and social factors on individual differences in development.
    No preview · Article · Dec 2015 · Developmental Science
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    • "race and gender) of our youth participants, and aspects of their familial social capital (e.g. parental education) have statistical relationships with their neurocognitive performance (Hackman & Farah, 2009; Hackman et al. 2010). The importance of neighborhood-level demography and crime, to further characterize the environment around these youth at the time of entry into the cohort, has also been noted (Noble et al. 2007; McEwen & Gianaros, 2010). "
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    ABSTRACT: Background: The contribution of 'environment' has been investigated across diverse and multiple domains related to health. However, in the context of large-scale genomic studies the focus has been on obtaining individual-level endophenotypes with environment left for future decomposition. Geo-social research has indicated that environment-level variables can be reduced, and these composites can then be used with other variables as intuitive, precise representations of environment in research. Method: Using a large community sample (N = 9498) from the Philadelphia area, participant addresses were linked to 2010 census and crime data. These were then factor analyzed (exploratory factor analysis; EFA) to arrive at social and criminal dimensions of participants' environments. These were used to calculate environment-level scores, which were merged with individual-level variables. We estimated an exploratory multilevel structural equation model (MSEM) exploring associations among environment- and individual-level variables in diverse communities. Results: The EFAs revealed that census data was best represented by two factors, one socioeconomic status and one household/language. Crime data was best represented by a single crime factor. The MSEM variables had good fit (e.g. comparative fit index = 0.98), and revealed that environment had the largest association with neurocognitive performance (β = 0.41, p < 0.0005), followed by parent education (β = 0.23, p < 0.0005). Conclusions: Environment-level variables can be combined to create factor scores or composites for use in larger statistical models. Our results are consistent with literature indicating that individual-level socio-demographic characteristics (e.g. race and gender) and aspects of familial social capital (e.g. parental education) have statistical relationships with neurocognitive performance.
    Full-text · Article · Oct 2015 · Psychological Medicine
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