# Multidimensional Features of Socioeconomic Status, Brain Age, and the Potential Mediating Role of Cardiometabolic Health Among Mid and Late Life Adults

> **NIH NIH F31** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2024 · $48,974

## Abstract

Project Summary/Abstract
Socioeconomic inequalities in risk for both dementia and cardiometabolic diseases are significant public health
problems. A barrier to addressing these inequalities lies in accurately identifying the specific types (i.e.
objective or subjective) and dimensions of socioeconomic status (SES; i.e. income or education) that may be
driving these inequalities, as well as discerning which age groups exhibit the most vulnerability. For instance,
some evidence suggests that accelerated brain aging, when machine learning predicted brain age exceeds
chronological age, tracks a socioeconomic gradient. Accelerated brain aging has been linked to dementia risk
and cardiometabolic health, but the limited available literature on SES and brain age is mixed and inconclusive.
One reason for this empirical variability is that studies tend to use only a few incomplete SES indicators (i.e.
years of education and/or income) that while important, do not accurately capture the multifaceted nature of
SES. Use of select and potentially biased measures may also vary in their ability to index SES across ages.
Moreover, studies on social inequalities in brain age do not examine whether results vary by chronological age,
which limits our ability to identify whether SES inequalities in brain aging varies across the lifespan as
observed with other outcomes. Lastly, studies on inequalities in brain age tend to omit indicators of
cardiometabolic health or they rely on self-report measures of cardiometabolic health that could confer risk for
accelerated brain aging and dementia. The present study is thus designed to address these issues by being
the first to integrate comprehensive socioeconomic data, laboratory-based biomarkers of cardiometabolic risk,
and neuroimaging data to test whether objective and subjective SES relate to brain age and cardiometabolic
health among mid and late life adults. We leverage cross-sectional data from 3 NIH studies on midlife adults (N
=1,122) and 1 NIH study on older adults (N = 648). We have 3 Aims: Aim 1. Determine whether
multidimensional SES indicators associate with brain age and cardiometabolic health in midlife adults Aim 2.
Examine the potential mediating effect of cardiometabolic health on the association between SES and brain
age among midlife adults. Aim 3. Determine whether the findings from Aim 1 and 2 replicate in older adults and
in an independent sample of midlife adults. This fellowship will provide training in data science and
harmonization, brain age quantification, structural equation modeling, and manuscript writing that are
necessary to help the applicant complete this project and achieve his long-term goal of becoming an
independent clinical scientist in the area of neurocognitive aging and dementia. Training is facilitated by
individual and group meetings with an experienced mentoring team, as well as guided readings and didactics.
Results of the proposed study will improve our understanding of socioe...

## Key facts

- **NIH application ID:** 10998322
- **Project number:** 1F31AG090048-01
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Jermon Drake
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $48,974
- **Award type:** 1
- **Project period:** 2024-09-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10998322

## Citation

> US National Institutes of Health, RePORTER application 10998322, Multidimensional Features of Socioeconomic Status, Brain Age, and the Potential Mediating Role of Cardiometabolic Health Among Mid and Late Life Adults (1F31AG090048-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10998322. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*