Detection of potential causal pathways among social determinants of health: A data-informed framework

Michael Korvink, Madeleine Biondolillo, Julie Willems Van Dijk, Anjishnu Banerjee, Christopher Simenz and David Nelson

Social Science & Medicine, 2025, vol. 373, issue C

Abstract: Understanding social determinants of health (SDOH) as a complex system is necessary for designing effective public health interventions. Traditional expert-driven approaches to mapping SDOH relationships, when used in isolation, are susceptible to subjective biases, incomplete knowledge, and inconsistencies across different domains of expertise. Additionally, SDOH variables often contain overlapping information, making it difficult to isolate unique SDOH constructs. A data-driven approach integrating dimensionality reduction and causal discovery can provide a more objective framework for identifying and mapping SDOH factors within a causal system. The data-driven method may serve as a starting point to overcome potential research biases in the development of causal structures.

Keywords: Social determinants of health; Causal discovery; Principal component analysis; Greedy equivalence search; Health equity; Intersectionality (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:socmed:v:373:y:2025:i:c:s0277953625003557

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DOI: 10.1016/j.socscimed.2025.118025

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