Background: Cardiovascular disease (CVD) is the leading cause of mortality worldwide, with >80% of CVD deaths occurring in low and middle income countries (LMICs). Diabetes mellitus and pre-diabetes are risk factors for CVD, and CVD is the major cause of morbidity and mortality among individuals with DM. There is a critical period now during which reducing CVD risk among individuals with diabetes and pre-diabetes may have a major impact. Cost-effective, culturally appropriate, and context-specific approaches are required. Two promising strategies to improve health outcomes are group medical visits and microfinance.
Methods/design: This study tests whether group medical visits integrated into microfinance groups are effective and cost-effective in reducing CVD risk among individuals with diabetes or at increased risk for diabetes in western Kenya. An initial phase of qualitative inquiry will assess contextual factors, facilitators, and barriers that may impact integration of group medical visits and microfinance for CVD risk reduction. Subsequently, we will conduct a four-arm cluster randomized trial comparing: (1) usual clinical care, (2) usual clinical care plus microfinance groups only, (3) group medical visits only, and (4) group medical visits integrated into microfinance groups. The primary outcome measure will be 1-year change in systolic blood pressure, and a key secondary outcome measure is 1-year change in overall CVD risk as measured by the QRISK2 score. We will conduct mediation analysis to evaluate the influence of changes in social network characteristics on intervention outcomes, as well as moderation analysis to evaluate the influence of baseline social network characteristics on effectiveness of the interventions. Cost-effectiveness analysis will be conducted in terms of cost per unit change in systolic blood pressure, percent change in CVD risk score, and per disability-adjusted life year saved.
Discussion: This study will provide evidence regarding effectiveness and cost-effectiveness of interventions to reduce CVD risk. We aim to produce generalizable methods and results that can provide a model for adoption in low-resource settings worldwide.
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