Tracking Post-Disaster Chronic Disease: Protocol for the RECOVER Cohort Study

Abstract

Introduction:There is growing evidence that disasters may increase the risk of developing chronic diseases, including diabetes, dyslipidemia, chronic kidney disease, and cardiovascular disease. However, how much disaster exposure specifically affects chronic disease risk is unknown. This presentation introduces the study protocol for the Risk of hEalth ConditiOn AdVerse Events after disasteRs (RECOVER) Cohort Study, which addresses this gap.Method:The primary aim of RECOVER is to determine the extent to which disaster exposure specifically increases the risk of developing chronic disease (Aim 1). The secondary aims of the study are to determine if the nature, duration and severity of disaster exposure are risk factors for disease (Aim 2), to map mediators of post-disaster chronic disease risk (Aim 3), and to identify potential biomarkers of post-disaster chronic disease risk (Aim 4). RECOVER will recruit over 6000 adults (1:1 disaster exposed vs unexposed) in Australia to a nationally representative cohort for longitudinal follow-up. Detailed data will be obtained annually on disaster exposure, demographic, social and health factors. The primary health outcome (Aim 1) of chronic disease will be defined as new, incident diabetes, cardiovascular or respiratory disease, and will be ascertained through data linkage with the Pharmaceutical Benefits Scheme. A biomarker sub-stream will include ~1,000 participants who provide a hair and saliva sample for cortisol and epigenetic analysis.Results:N/AConclusion:There is an urgent need for detailed individual-level data to analyze the nature of the association between disaster exposure and chronic disease. In 2020 alone, 16.8 million Australians were exposed to disasters. The frequency and severity of disasters are only expected to grow due to climate change. As the first prospective cohort study to longitudinally track individual-level disaster exposure and chronic disease outcomes, RECOVER will fill a critical evidence gap.