Month / April 2025

by Sydney Lash

Finding Hidden Structures in Patient Data: A SDoH Network Exploration

Understanding social determinants of health (SDoH) is becoming increasingly important in healthcare services and public health research.

Healthy People 2030, a major public health initiative, emphasizes addressing these areas to achieve real health equity.

Traditionally, research has often relied on proxy measures (like using race as a stand-in for the experience of racism) to represent structural factors. While useful, these proxies can miss the complex, relational ways that social determinants interact to shape health outcomes.

Network models offer a new approach: instead of looking at variables one by one, they allow us to model the hidden relationships between different social conditions and populations.

In this project, I used data from the Medical Expenditure Panel Survey (MEPS) to model latent similarity patterns among patients based on SDoH, including food insecurity, access to care, income, and social isolation.

I constructed a patient similarity network using cosine similarity, applied spectral embedding to project patients into a latent space, and used k-means clustering to identify subgroups within the network.

The results revealed subtle but meaningful patterns. Clusters differed in healthcare access barriers, financial instability, and compounded vulnerabilities such as low income paired with food insecurity.

These findings demonstrate how relational network modeling can uncover hidden gradients of disadvantage that traditional feature-by-feature analyses may overlook.

Future work could integrate health outcome data or longitudinal measures to better understand how these latent social structures impact health trajectories over time.

Sources:

[1] Office of Disease Prevention and Health Promotion. Healthy People 2030 Framework. U.S. Department of Health and Human Services.​

[2] Qing, H. (2023). Latent class analysis by regularized spectral clustering. arXiv preprint arXiv:2310.18727. https://doi.org/10.48550/arXiv.2310.18727​
[3] Agency for Healthcare Research and Quality. Medical Expenditure Panel Survey (MEPS), 2022 Full-Year Consolidated Data File.

[4] https://www.geeksforgeeks.org/spectral-embedding/

by Sydney Lash

Race, Place, and Quality

A Look at Hypertension Management Among Black Women in North Carolina

This semester, in my Social Epidemiology course, we had to propose a study related to our course content. I chose to explore how race, place, and healthcare quality intersect to shape outcomes for Black women living with hypertension.

Why This Study?

Black women in the U.S. face unique and layered health challenges due to the intersecting effects of racism and sexism. The weathering hypothesis, developed by Geronimus et al., suggests that chronic exposure to social, economic, and racial stressors accelerates health deterioration—particularly among Black women.1,2

Despite advances in treatment, disparities in chronic disease outcomes persist. Black women, especially in rural areas, remain more likely to experience uncontrolled hypertension. This raises critical questions about how structural barriers, such as geographic isolation and limited access to high-quality care, interact with in-clinic factors, such as provider bias.

Layered forms of marginalization interact to shape Black women’s health experiences

My Research Question

Among Black women receiving care at Federally Qualified Health Centers (FQHCs) in North Carolina, how does the impact of geographic proximity on hypertension management differ between urban and rural communities?

My hypothesis: Geographic proximity will have a smaller impact on hypertension management among Black women in rural communities compared to those in urban areas due to compounded marginalization and systemic barriers.

Background Context

  • Rural communities tend to have a higher chronic disease burden.3
  • High-burden ZIP Code Tabulation Areas (ZCTAs) had nearly double the proportion of Black residents compared to low-burden ZCTAs.3
  • On average, people in high-burden areas live 8.7 miles from the nearest FQHC, compared to 4.6 miles in low-burden areas.3
  • Clinical quality gaps persist: Non-Hispanic Black individuals are 12% less likely to have adequately controlled blood pressure, even after adjusting for socioeconomic and healthcare access factors.11,12

A map showing FQHC distribution across North Carolina and a gradient scale representing rurality by RUCA score.

Proposed Study Design

  • Design: Cross-sectional observational study
  • Population: Black women aged 18+ with a diagnosis of hypertension and at least two FQHC visits between Jan 2023 – Dec 2024
  • Data Source: EHR data from FQHCs across North Carolina
  • Exposure: Proximity to FQHC, measured by distance from home ZIP to clinic
  • Comparison Groups: Urban vs. rural residence (based on RUCA score)
  • Outcome: Blood pressure control (e.g., SBP <140 mmHg)
  • Covariates: Socioeconomic status, insurance, comorbidities, clinic characteristics

A directed acyclic graph illustrating the conceptual model of how structural and clinical factors interact to influence hypertension management.

Final Thoughts

Developing this proposal deepened my understanding of how place, identity, and systemic inequity play a role in measurable health outcomes. Mapping these disparities is only the beginning. As researchers, we must also imagine ways to redesign care systems that serve Black women and their intersectional identities more equitably.

References

  1. Geronimus AT, Hicken M, Keene D, Bound J. “Weathering” and age patterns of allostatic load scores among blacks and whites in the United States. Am J Public Health. 2006;96(5):826-833. doi:10.2105/AJPH.2004.060749
  2. Chinn JJ, Martin IK, Redmond N. Health Equity Among Black Women in the United States. J Womens Health (Larchmt). 2021;30(2):212-219. doi:10.1089/jwh.2020.8868
  3. Benavidez GA, Zahnd WE, Hung P, Eberth JM. Chronic Disease Prevalence in the US: Sociodemographic and Geographic Variations by Zip Code Tabulation Area. Prev Chronic Dis 2024;21:230267. DOI: http://dx.doi.org/10.5888/pcd21.230267.
  4. Ndugga N, Hill L, Artiga S. Key data on health and health care by race and ethnicity. KFF. Published June 11, 2024. Accessed November 14, 2024. https://www.kff.org/key-data-on-health-and-health-care-by-race-and-ethnicity/?entry=health-status-and-outcomes-chronic-disease-and-cancer
  5. Agency for Healthcare Research and Quality. 2023 National Healthcare Quality and Disparities Report Appendixes. AHRQ Pub. No. 23(24)-0091-EF. December 2023.
  6. Ochieng N, Biniek JF, Cubanski J, Neuman T. Disparities in health measures by race and ethnicity among beneficiaries in Medicare Advantage: A review of the literature. KFF. Published December 13, 2023. Accessed October 15, 2024. https://www.kff.org/medicare/report/disparities-in-health-measures-by-race-and-ethnicity-among-beneficiaries-in-medicare-advantage-a-review-of-the-literature/
  7. Jha AK, Zaslavsky AM, Orav EJ, Epstein AM, Ayanian JZ. Quality of ambulatory care for privately insured and Medicare Advantage enrollees in the United States. Health Aff (Millwood).
  8. Tong M, Hill L, Artiga S. Racial disparities in cancer outcomes, screening, and treatment. KFF. Published February 3, 2022. Accessed November 14, 2024. https://www.kff.org/racial-equity-and-health-policy/issue-brief/racial-disparities-in-cancer-outcomes-screening-and-treatment/
  9. Alsheik N, Blount L, Qiong Q, et al. Outcomes by race in breast cancer screening with digital breast tomosynthesis versus digital mammography. J Am Coll Radiol. 2021;18(7):906-918. doi:10.1016/j.jacr.2020.12.033
  10. Miller-Kleinhenz JM, Collin LJ, Seidel R, Oyesanmi O. Racial disparities in diagnostic delay among women with breast cancer. J Am Coll Radiol. 2021;18(10):1384-1393. doi:10.1016/j.jacr.2021.06.019
  11. Abrahamowicz AA, Ebinger J, Whelton SP, Commodore-Mensah Y, Yang E. Racial and Ethnic Disparities in Hypertension: Barriers and Opportunities to Improve Blood Pressure Control. Curr Cardiol Rep. 2023;25(1):17-27. doi:10.1007/s11886-022-01826-x
  12. Crim MT, Yoon SS, Ortiz E, et al. National surveillance definitions for hypertension prevalence and control among adults. Circ Cardiovasc Qual Outcomes. 2012;5(3):343-351. doi:10.1161/CIRCOUTCOMES.111.963439