The impact of community-based non-pharmacological interventions on cardiovascular and kidney disease outcomes in remote dwelling Indigenous communities: A scoping review protocol.

introductionIndigenous people represent approximately 5% of the world's population. However, they often have a disproportionately higher burden of cardiovascular disease (CVD) risk and chronic kidney disease (CKD) than their equivalent general population. Several non-pharmacological interventions (e.g., educational) have been used to reduce CVD and kidney disease risk factors in Indigenous groups. The aim of this paper is to describe the protocol for a scoping review that will assess the impact of non-pharmacological interventions carried out in Indigenous and remote dwelling populations to reduce CVD risk factors and CKD. MATERIALS AND

methodsThis scoping review will be guided by the methodological framework for conducting scoping studies developed by Arksey and O'Malley. Both empirical (Medline, Embase, Cochrane Library, CINAHL, ISI Web of Science and PsycINFO) and grey literature references will be assessed if they focused on interventions targeted at reducing CVD or CKD among Indigenous groups. Two reviewers will independently screen references in consecutive stages of title/abstract screening and then full-text screening. Impact of interventions used will be assessed using the reach, effectiveness, adoption, implementation, maintenance (RE-AIM) framework. A descriptive overview, tabular summaries, and content analysis will be carried out on the extracted data. ETHICS AND DISSEMINATION: This review will collect and analyse evidence on the impact of interventions of research carried out to reduce CVD and CKD among Indigenous populations. Such evidence will be disseminated using traditional approaches that includes open-access peer-reviewed publication, scientific presentations, and a report. Also, we will disseminate our findings to the government and Indigenous leaders. Ethical approval will not be required for this scoping review as the data used will be extracted from already published studies with publicly accessible data.