Population variation in social brain morphology: Links to socioeconomic status and health disparity

ABSTRACT

Health disparity across layers of society involves reasons beyond the healthcare system. Socioeconomic status (SES) shapes people’s daily interaction with their social environment and is known to impact various health outcomes. Using generative probabilistic modeling, we investigate health satisfaction and complementary indicators of socioeconomic lifestyle in the human social brain. In a population cohort of ~10,000 UK Biobank participants, our first analysis probed the relationship between health status and subjective social standing (i.e., financial satisfaction). We identified volume effects in participants unhappy with their health in regions of the higher associative cortex, especially the dorsomedial prefrontal cortex (dmPFC) and bilateral temporo-parietal junction (TPJ). Specifically, participants in poor subjective health showed deviations in dmPFC and TPJ volume as a function of financial satisfaction. The second analysis on health status and objective social standing (i.e., household income) revealed volume deviations in regions of the limbic system for individuals feeling unhealthy. In particular, low-SES participants dissatisfied with their health showed deviations in volume distributions in the amygdala and hippocampus bilaterally. Thus, our population-level evidence speaks to the possibility that health status and socioeconomic position have characteristic imprints in social brain differentiation.

KEYWORDS:

• Bayesian hierarchical modeling
• big biomedical data
• population neuroscience
• probabilistic inference

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

D.B. designed the study and the quantitative analysis approach. N.S., H.K., and D.B. interpreted the results, drafted and revised the manuscript.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/17470919.2022.2083230

Additional information

Funding

This work was supported by the Canadian Institute of Health Research [CIHR 438531]; Brain Canada Foundation, through the Canada Brain Research Fund, with the financial support of Health Canada, National Institutes of Health [NIH R01 AG068563A];Healthy Brains Healthy Lives initiative (Canada First Research Excellence fund); Google (Research Award, Teaching Award); and CIFAR Artificial Intelligence Chairs program (Canada Institute for Advanced Research).