MRI reveals differences in people’s brains by where they live, a study published September 15 in Radiology found.
MRI scans of people living in highly disadvantaged neighborhoods showed more ties to adverse brain health, wrote a research group led by John-Paul Yu, MD, PhD from the University of Wisconsin in Madison and colleagues.
“The practical point for clinicians is that neighborhood context appears to be a measurable correlate of brain structure in ordinary clinical care, not just in curated research cohorts, and that some of the variation we see in clinical scans may be environmentally driven rather than representative of a named pathological change,” Yu told AuntMinnie.
Researchers in recent years have studied potential relationships between neighborhood-level socioeconomic disadvantage and brain health. This research may have implications toward public health and clinical practice, as well as how studies take such information into account. For example, higher brain age is tied to cardiovascular risk factors, psychiatric illness, and cognitive impairment.
Yu and colleagues noted that most neuroimaging studies focused on socioeconomic disparities rely on enriched research cohorts or disease-specific samples.
The Yu team studied whether living in the most socioeconomically disadvantaged neighborhoods is linked to a higher brain age gap and decreased total brain volume. Based on MRI estimates, brain age gap measures the difference between a person’s actual age and how much younger or older the brain appears.
National and state neighborhood-level disadvantage rankings of the study patients. (A) National disadvantage rankings are
shown. Left: area deprivation scores mapped onto the state of Wisconsin, where the study sample resides, with national ranking deciles shown. Blue indicates less disadvantaged neighborhoods, whereas red indicates more disadvantaged neighborhoods. Right: histogram quantifying the number of patients in each Area Deprivation Index (ADI) decile. (B) Same as A, but state ranking deciles are shown. The distributions of both the national and state-level ADI rankings of the patients were skewed toward less disadvantaged neighborhoods. Maps were obtained from reference 36.RSNA
The researchers analyzed brain MRIs from 2,826 patients ranging in age from 18 to 96 years. Of the total patients, 1,732 were women and 1,094 were men. They used neuroimaging data from consecutive inpatient and outpatient clinical MRI exams performed in 2024. The study did not include patients with imaging evidence of disease.
The team calculated an Area Deprivation Index (ADI) score for each patient. ADI is a measure of neighborhood-level socioeconomic disadvantage based on a resident’s zip code. It incorporates 17 indicators of income, education, employment and housing characteristics derived from 2023 American Community Survey data.
Patients living in the most disadvantaged neighborhoods showed a higher brain age gap compared to those living in more advantaged neighborhoods, the researchers reported. This included a national-level difference of 2.72 years and a state-level difference of 3.02 years (p
Patients living in the most disadvantaged neighborhoods also had lower total brain volume, including -6.33 normalized mL on the national level (p = 0.01) and -7.46 on the state level (p = 0.002).
The researchers also found higher levels of white matter hyperintensity volume (WMHV) among patients in the most disadvantaged neighborhoods (national: 0.31 log-transformed normalized mL [p
Finally, interaction models showed increased negative associations between WMHV and striatal (β value, −0.02; p = 0.01) and dorsolateral prefrontal cortex volumes (β value, −0.40; p = 0.008) among patients in the most disadvantaged neighborhoods.
Yu said the vascular interaction suggests pairing brain health messaging with cardiometabolic risk reduction in the most disadvantaged areas, “where the two pathways appear to converge,” may be an effective outreach strategy.
“It also supports the broader case for incorporating neighborhood context into risk prediction rather than treating it as a background demographic variable,” he told AuntMinnie.
Yu also said the team is interested in longitudinal imaging to see how these relationships develop over time, integrating individual-level socioeconomic and clinical cardiovascular data. With this data, the researchers can start separating direct vascular effects from broader environmental pathways and in the mechanistic work linking chronic stress and small vessel disease to frontostriatal circuits, he added.
Read the full study here.