Key result
Systems science methods identify 89 CVD prevention interventions and reveal root causes of risk disparities.
Why the study?
Marginalized communities shoulder a disproportionate burden of CVD driven by concentrated neighborhood social risk factors, prompting a case study applying systems science to address geographic CVD health disparities at the community level.
Systems science methods can effectively organize cardiovascular disease prevention efforts and identify root causes of health disparities, such as stress, to better align interventions with community needs.
May help align CVD prevention interventions with community needs; leaves open whether targeting stress reduces disparities.
Objective: Marginalized communities shoulder a disproportionate burden of cardiovascular disease (CVD) driven by concentrated neighborhood social risk factors. We provide a case study of systems science application to address geographic CVD health disparities at the community level - informing the science of CVD health disparities research. Methods: We conducted a two-phased, multi-methods needs assessment in the Denver, Colorado area. Phase I consisted of a social network analysis to map a two-mode network of existing CVD prevention interventions and their implementing organizations. In Phase II, group model building (GMB) sessions with key community, public health, and healthcare provider stakeholders, were utilized to identify and visualize community factors contributing to disparities in CVD risk, producing a consensus-based causal loop diagram. Results: Between May 2021 and June 2022, we conducted 24 virtual, semi-structured interviews in Phase I to describe CVD prevention interventions, and 7 virtual GMB sessions in Phase II to describe experiences of disparities in CVD risk. For the purposes of this paper, we focus on a subset of results for both phases. In Phase I we identified 89 active CVD prevention interventions, 29 of which addressed tobacco use. In Phase II, causal loop diagrams revealed root causes of disparities in CVD risk. We provide an example of a causal loop diagram that focuses on the community prevalence of tobacco use, identifying stress as a key underlying factor driving disparities. The integration of findings from both phases highlighted the alignment and misalignment between quit tobacco intervention goals and how they are being experienced in marginalized communities. Conclusion: Systems science methods were useful to organize a large number of CVD prevention efforts, and evaluate the root causes of CVD health disparities in a high risk community. By integrating these two aspects, interventions may be reoriented to more effectively address the root causes of CVD health disparities.
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Bauer et al. (2023) studied Cardiovascular disease (n=38). Systems science methods (social network analysis and group model building) was evaluated on Identification of active CVD prevention interventions and community factors contributing to disparities in CVD risk. Systems science methods identified 89 active CVD prevention interventions and revealed root causes of disparities in CVD risk, such as stress, highlighting misalignment between intervention goals and community experiences.
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