A research agenda for understanding how social inequality is linked to brain structure and function

Abstract

Consistent evidence documents powerful effects of social inequality on health, well-being and academic achievement. Yet research on whether social inequality may also be linked to brain structure and function has, until recently, been rare. Here we describe three methodological approaches that can be used to study this question-single site, single study; multi-site, single study; and spatial meta-analysis. We review empirical work that, using these approaches, has observed associations between neural outcomes and structural measures of social inequality-including structural stigma, community-level prejudice, gender inequality, neighbourhood disadvantage and the generosity of the social safety net for low-income families. We evaluate the relative strengths and limitations of these approaches, discuss ethical considerations and outline directions for future research. In doing so, we advocate for a paradigm shift in cognitive neuroscience that explicitly incorporates upstream structural and contextual factors, which we argue holds promise for uncovering the neural correlates of social inequality.

Figure 1.. Childhood Neighborhood Disadvantage is Associated with Greater Amygdala Reactivity

Figure adapted from Gard et al. (2021). Greater neighborhood disadvantage in early childhood was associated with elevated amygdala response to neutral faces in early adulthood, after adjusting for family-level SES and other forms of adversity including maternal depression and harsh parenting. These findings were replicated in 2 studies of boys from low-income family backgrounds, (a) at the University of Pittsburgh with participants from Pittsburgh (n=167) and (b) at the University of Michigan with participants from Chicago, Toledo, and Detroit.

Figure 2.. Association between Family Income and Hippocampal Volume is Stronger in States with Higher Costs of Living, But Weaker in U.S. States with More Generous Anti-Poverty Policies

Figure adapted from Weissman et al. (2023). 3-way interactions between state-level cost of living and generosity of anti-poverty programs and individual family income-to-needs ratio (log-transformed). Cash assistance was based on both monthly Temporary Assistance for Needy Families (TANF) benefits in that state and the average monthly Earned Income Tax Credit (EITC) in that state. Higher cost of living was associated with smaller hippocampal volume among low-income participants, but this was attenuated when states also offered more generous cash benefits. Postal abbreviations for the 17 states in the ABCD study (CA: California; CO: Colorado; CT: Connecticut; FL: Florida; MD: Maryland: MI: Michigan; MN: Minnesota; MO: Missouri; NY: New York; OK: Oklahoma; OR: Oregon; PA: Pennsylvania; SC: South Carolina; UT: Utah; VT: Vermont; VA: Virginia; WI: Wisconsin) are placed along the X-axis in the location corresponding most closely to their cost of living and cash assistance relative to the other states. Hippocampal volume estimates are equivalent to the random intercept of the relation between income and hippocampal volume for that state when family income is 1 SD above (high income) or below (low income) the mean.

Figure 3.. Spatial Meta-analysis of the Association between Gender Inequality in 29 Countries and Cortical Structure

Figure adapted from Zugman et al. (2023). (a) The authors identified 139 studies conducted in 29 countries. (b) Using nation-level data from the United Nations and the World Economic Forum, the authors examined the association between gender inequality and sex differences in cortical thickness and surface area. They found that in studies conducted in countries with greater gender inequality, men tended to have greater right hemisphere cortical thickness. Associations between gender inequality and sex differences in cortical thickness in specific regions were also observed.