# Examining the Role of Structural Factors in Racial and Ethnic Disparities in Cardiovascular Disease

> **NIH NIH K99** · STANFORD UNIVERSITY · 2024 · $150,681

## Abstract

Accumulating research suggests that barriers to eliminating the persistent disparities in
cardiovascular disease (CVD) are related to structural-level social determinants of health
(SDOH). The majority of this evidence is cross-sectional, from studies using administrative
datasets (i.e., US Census) to quantify structural SDOH associations with ecological-level
measures of CVD. Prospective and clinical CVD outcome data are needed to advance from
descriptive-level evidence; however, well-established cohort studies typically lack access to
novel structural determinants. The scientific objective of the research plan is an innovative
solution to generate the needed high-quality dataset, by employing data fusion techniques to link
structural determinants from administrative datasets with prospective cohort data. I will generate
four structural-level determinants at the neighborhood-level using geographic linkages between
the Women’s Health Initiative (WHI) cohort with 1) US Census 2) American Community Survey
(ACS) 3) Center for Disease Control and 4) Neighborhood Redlining Maps. Each structural
determinant adheres to recent conceptual frameworks for advancing the quantification of CVD
disparities. I uniquely measure determinants longitudinally to account for changes in residence
and the duration of exposure. In Aim 1 (K99 phase), I will quantify structural determinants at the
intersection of demographic and material determinants using the index of concentration at the
extremes (ICE). The causal effects of ICE on CVD incidence over 30 years of follow-up will be
estimated. In Aim 2, I propose to link the Social Vulnerability Index to evaluate a hypothesized
structural intervention on CVD. In Aim 3, I propose to estimate CVD risk associated with
demographic residential segregation and residence in a historically redlined neighborhood.
Evaluating causal mechanisms, temporality, life-course exposure, and accounting for
intersectionality would markedly advance the current level of evidence. The public health
implications of which may help design future interventions to target modifiable structural
policies and practices. The career development plan will advance my scientific training in data
fusion techniques, the modeling of structural determinants, and pathways to CVD. Through
mentored training combined with this research plan, the K99/R00 will prepare my transition to
an independent investigator in a tenure-track faculty position. This award would advance three
Objectives of the NHLBI Strategic Vision through the use of (3) an emerging opportunity in data
science to accelerate understanding of (7) factors that account for differences in health among
populations, led by (8) a scientist who would “further develop, [redacted], and sustain a scientific
workforce capable of accomplishing the NHLBI’s mission”.

## Key facts

- **NIH application ID:** 10910132
- **Project number:** 5K99HL169908-02
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Shawna Follis
- **Activity code:** K99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $150,681
- **Award type:** 5
- **Project period:** 2023-08-18 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10910132

## Citation

> US National Institutes of Health, RePORTER application 10910132, Examining the Role of Structural Factors in Racial and Ethnic Disparities in Cardiovascular Disease (5K99HL169908-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10910132. Licensed CC0.

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