Summary:
A large clinical MRI study of 2,826 patients shows that living in socioeconomically disadvantaged neighborhoods is linked to measurable signs of accelerated brain aging, lower overall brain volume, and increased markers of vascular injury in the white matter. The findings demonstrate that structural inequities leave biological imprints on brain structure and vascular health detectable with routine neuroimaging.
Key Facts:
- Accelerated brain aging and reduced volume: People living in the most disadvantaged neighborhoods had a larger brain age gap—their brains appeared older than their chronological age—and showed reduced total brain volume.
- Evidence of vascular injury: MRI scans revealed higher white matter hyperintensity volume among residents of highly deprived areas, a radiologic sign of chronic microvascular damage.
- Real-world clinical sample: This retrospective analysis evaluated 2,826 clinical brain MRI scans from adults aged 18 to 96, linking imaging biomarkers to neighborhood-level disadvantage measured by the Area Deprivation Index (ADI).
Source: RSNA
Decades of research have suggested that the places where people live, work, and grow older shape their health. Translating these social determinants into quantifiable neurobiological changes across broad clinical populations, however, has been challenging.
A study published in Radiology by investigators at the University of Wisconsin School of Medicine and Public Health provides robust clinical evidence that neighborhood-level socioeconomic disadvantage is associated with specific, measurable changes on brain MRI.
Analyzing nearly 3,000 clinical MRI scans, the researchers report that individuals living in areas with the highest deprivation scores exhibit signs of accelerated brain aging, global brain volume loss, and higher volumes of white matter hyperintensities compared with residents of less disadvantaged neighborhoods.
“We’ve long suspected that your living environment affects your brain, but until now it hasn’t been proven at scale in a real-world clinical population,” said senior author John-Paul J. Yu, M.D., Ph.D. “These results provide clear, quantitative evidence that neighborhood conditions have an outsized impact on the brain at cellular and molecular levels.”
Measuring the Imprint of Structural Inequity
This retrospective imaging study evaluated 2,826 patients (1,094 men and 1,732 women) aged 18 to 96, with MRIs collected from January to June 2024 across University of Wisconsin Hospitals and affiliated community partners. To focus on environmental influences, the team excluded scans with visible neurologic disease, normalized volumetric measures to total intracranial volume, and adjusted all models for age and sex.
Neighborhood disadvantage was quantified using the Area Deprivation Index (ADI), a census block–level composite metric derived from the 2023 American Community Survey. ADI integrates 17 indicators including income, housing quality, employment, and education, and was assigned using patient ZIP codes.
Correlating ADI with imaging measures revealed two primary morphometric changes associated with higher deprivation:
- Increased brain age gap (BAG): A larger difference between predicted biological brain age and chronological age, indicating accelerated structural aging in those from deprived neighborhoods.
- Decreased total brain volume (TBV): Global tissue loss relative to intracranial volume, reflecting overall atrophy.
Residents of the most disadvantaged neighborhoods showed higher BAG and lower TBV, consistent with prior work linking elevated brain age to greater risk for cardiovascular disease, cognitive impairment, and psychiatric conditions.
The Vascular Footprints of Chronic Stress
Beyond volume changes, the study found higher white matter hyperintensity volume (WMHV) among patients from high-deprivation neighborhoods. White matter hyperintensities are bright focal lesions on MRI that reflect chronic ischemic injury and small-vessel disease.
“White matter hyperintensities are essentially the footprints of cardiovascular damage in the brain,” Dr. Yu explained. “Chronic stressors such as hypertension, sleep disruption, and persistent psychosocial stress can constrict small vessels and reduce blood flow, producing these MRI-visible lesions over time.”
Accumulation of white matter hyperintensities is strongly associated with memory decline, executive dysfunction, and an elevated risk of dementia.
Implications for Public Health and Clinical Care
The authors propose that neuroimaging markers like BAG, TBV, and WMHV can serve as objective intermediate biomarkers linking structural inequity to brain health. Incorporating neighborhood-level measures such as ADI into clinical risk assessment may help identify individuals at elevated neurologic risk before symptoms appear.
“This is the first time a real-world clinical population has shown clear, quantifiable links between an individual’s environment and brain morphometry,” Dr. Yu said. “Where people are born, live, work, and age shapes long-term neurological outcomes and should inform prevention and resource allocation.”
Because indices like the ADI capture cumulative environmental and economic disparities that extend beyond individual behavior, the researchers urge health systems and policymakers to consider neighborhood-level data in preventive strategies and health equity initiatives.
Editorial Notes:
- Article edited by a Neuroscience News editor.
- Journal paper reviewed in full; additional context added by staff.
About this Neurodevelopment Research:
- Media Contact: Linda Brooks
- Source: RSNA
- Image Credit: Image generated for Neuroscience News
- Original Research (Open Access): Radiology (September 15, 2026). “Evaluating the Effect of Neighborhood-level Disadvantage on Brain Health: An Imaging Epidemiology Study.” Authors: Ethan H. Willbrand, Elizabeth M. Stoeckl, Daryn Belden, Sheena Y. Chu, Eleanna M. Melcher, Daniil Zhitnitskii, Elena Bonke, Jussi Mattila, Usman Iftikhar, Juha Koikkalainen, Antti Tolonen, Jyrki Lötjönen, Richard Bruce, and John-Paul J. Yur.
- DOI: 10.1148/radiol.260693
Abstract
Evaluating the Effect of Neighborhood-level Disadvantage on Brain Health: An Imaging Epidemiology Study
Background
Neighborhood-level socioeconomic disadvantage and its relationship to brain health is a growing research focus with important implications for public health and clinical practice. The specific association between community disadvantage and brain structure, however, has remained incompletely defined.
Purpose
To examine the epidemiologic link between neighborhood-level socioeconomic disadvantage (measured by ADI) and morphometric neuroimaging measures in a real-world clinical cohort.
Materials and Methods
In this retrospective study at an academic medical center and community partners, consecutive cross-sectional brain MRI scans from patients without radiologic evidence of neurologic disease were analyzed. ADI was assigned per patient using geospatial census-block measures. Linear regression models tested associations between ADI and morphometric outcomes: brain age gap (BAG), total brain volume (TBV), total white matter hyperintensity volume (WMHV), volumes of five subcortical regions (hippocampus, thalamus, caudate, putamen, nucleus accumbens), and four cortical regions (anterior and posterior cingulate cortices, medial frontal cortex, dorsolateral prefrontal cortex). Volumes were normalized to intracranial volume; models adjusted for age and sex.
Results
The study included 2,826 patients (mean age 53 ± 18.8 years; 1,732 female). Residence in the most disadvantaged neighborhoods was associated with higher BAG (adjusted differences: national β = 2.72 years, P < .001; state β = 3.02 years, P < .001) and lower TBV (national β = −6.33 normalized mL, P = .01; state β = −7.46, P = .002). WMHV was greater among those in the most disadvantaged areas (national β = 0.31 log-transformed normalized mL, P < .001; state β = 0.32, P < .001). Interaction analyses revealed stronger negative associations between WMHV and striatal (β = −0.02; P = .01) and dorsolateral prefrontal cortex volumes (β = −0.40; P = .008) in the most disadvantaged neighborhoods.
Conclusion
Living in the most socioeconomically disadvantaged neighborhoods was associated with adverse brain morphometry on MRI, including higher brain age gap, lower total brain volume, and greater white matter hyperintensity burden. These findings support the use of neuroimaging biomarkers to quantify the neurologic consequences of structural inequity and to inform prevention and public health strategies.