Using Systems Science Methods to Study Cardiac Risk in the Somali Community

Healthpartners Institute, Minneapolis MN

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Abstract

DESCRIPTION: Metabolic syndrome is a multiplex risk factor for cardiovascular disease (CVD) in need of clinical interventions. The impact of social factors on the components of metabolic syndrome (CMS) is well documented. The evidence for how social factors impact CMS and how different interventions can reduce the prevalence of CMS through influence on social factors is very weak. The evidence is weaker in the case of nearly 12.5 million legal permanent residents in the United States in 2009. The current reductionist analytical approaches to understanding the effect of social environment on CMS are inadequate to understanding the complexities of nonlinear, relationship-driven systems. The Somali community in Minneapolis presents a unique opportunity for collecting data using link tracing- based sampling techniques, with a very high response rate. Due to the tightly knit, densely located nature of the community, the community-driven nature of the project, and the research team's previous successes, excellent reputation, and goodwill in the community, very high participation is anticipated. Findings from the project will likely have a direct impact on this community. Public health in general will benefit significantly because this study will provide a systems approach-based analytical framework to evaluate the underlying and structural mechanisms linking social networks to CMS. It will also provide unprecedented insights based on simulated health interventions. This framework will give policymakers a map for future interventions between the social environment and CMS. The project has three stages. Stage 1: Respondent-driven sampling (RDS)-based data collection and construction and design of an agent-based model (ABM) framework; Stage 2: social network analysis (SNA) and testing of hypotheses; Stage 3: parameterize ABM based on results from SNA, validate the ABM, and test more hypotheses. We will collect data from four primary data sources: in-person interviews including anthropometric measures, biological samples, insurance claims from the HealthPartners health plan, and state and federally insured individuals' claims from the Department of Human Services. The ABM will allow us to compare the effects of such varied interventions as the introduction of community health workers (CHWs) for increasing the supply of heath care in an outreach position in community centers and in hospitals and clinics, better cultural training of non-Somali physicians, increased communication through different channels (e.g., mass media, community leaders, forums, centers and associations, interpreters), and better awareness of and access to preventive services. Bringing together such interventions in an innovative, validated, and comprehensive analytical framework has been an important omission in other research aimed at improving the health outcomes and behaviors of communities.