# How multi-scale modeling can help examine social determinants of health and resulting disparities

**Authors:** Kyoko Yoshida, Elsje Pienaar, Shalanda A. Bynum, Naomi Chesler, Mitchel J. Colebank, Jessie Heneghan, Nadra Tyus, Jasmine Miller-Kleinhenz, Bruce Y. Lee

PMC · DOI: 10.1371/journal.pcbi.1013284 · 2025-07-15

## TL;DR

This paper explores how multi-scale modeling can help understand and address health disparities caused by social determinants of health.

## Contribution

It proposes a call to action for interdisciplinary collaboration to apply multi-scale modeling in SDOH research.

## Key findings

- Multi-scale modeling can uniquely address challenges in characterizing adverse SDOH.
- Interdisciplinary collaboration is necessary for successful application of multi-scale modeling in SDOH research.
- The paper outlines current challenges and future directions for multi-scale modeling in health disparities research.

## Abstract

Social determinants of health (SDOH) are the conditions in which people live, work, and play, and the wider set of factors (e.g., social and economic systems and policies) that shape a person’s daily life. SDOH can differ significantly across communities and populations, having positive impacts for some and negative impacts for others. Ultimately, this results in differences in health and disease distribution, that are known as health disparities. Despite the known impacts of SDOH and calls to characterize, address, reduce, and eliminate health disparities, they persist and, in some cases, have worsened. To address this challenge, a session at the Interagency Modeling and Analysis Group Multiscale Modeling Meeting held on the National Institutes of Health campus from June 28th to 29th, 2023, considered potential ways that multiscale modeling can help characterize adverse SDOH and resulting health disparities. This perspective summarizes and synthesizes the session discussions as a call to action to promote and strengthen interdisciplinary science that merges the unique perspectives, experiences, and expertise of the SDOH and multiscale modeling scientific communities in the pursuit of knowledge to improve population health. Specifically, we identify current challenges and ways in which multiscale modeling is uniquely suited to address the challenges, as well as identify what is necessary to facilitate the successful application of multiscale modeling in SDOH research. We conclude with a discussion on the future of multiscale modeling in SDOH and health disparities research.

## Full-text entities

- **Genes:** BRCA1 (BRCA1 DNA repair associated) [NCBI Gene 672] {aka BRCAI, BRCC1, BROVCA1, FANCS, IRIS, PNCA4}, BRCA2 (BRCA2 DNA repair associated) [NCBI Gene 675] {aka BRCC2, BROVCA2, FACD, FAD, FAD1, FANCD}
- **Diseases:** obesity (MESH:D009765), overweight (MESH:D050177), cancer (MESH:D009369), atrophy (MESH:D001284), inflammation (MESH:D007249), MM (MESH:C538175), influenza (MESH:D007251), Breast cancer (MESH:D001943), adiposity (MESH:D018205), COVID-19 (MESH:D000086382), HD (MESH:D011019), SDOH-HD (OMIM:603663), insulin resistance (MESH:D007333), SDOH (MESH:D003643)
- **Chemicals:** MM (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12262866/full.md

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Source: https://tomesphere.com/paper/PMC12262866