3.2 Incident heart failure hospitalizations by ethnicity 119 INTRODUCTION Heart failure (HF) is a global public health problem with an estimated 26 million people in the world living with the condition.[1] Much of the epidemiologic data on HF come from western countries[2]. However, little reliable population-based data on the incidence of HF is available from this region to substantiate this claim.[3,4] Country-specific estimates for India and Japan have thus far relied on data extrapolations as representative data for the general population were not available.[3,5] While good quality clinical data on HF in the region is now available through the Asian Heart Failure registry, it may be less representative of general HF patients because like any HF registry, there were selection criteria. Patients were enrolled based on diagnosis of symptomatic HF and left ventricular dysfunction, and majority were treated at cardiology and HF specialty centres.[6] It has been shown that patients who were enrolled in a HF registry had different characteristics from those who were not, whereby enrolment was associated with better survival outcomes.[7] Nationwide information on the incidence and time trends for HF is vital for evaluating changes in healthcare delivery and disease burden. Furthermore, determining the differences in incidence rates of HF by ethnic subgroups is necessary for understanding the burden of HF in this ethnically diverse region. Malaysia is a multi-ethnic country in Southeast Asia, where its population is made up of three major ethnic groups of Malays, Chinese and Indians as well as a smaller proportion of indigenous population and other ethnicities. This ethnic diversity allows the comparison of incidence of HF hospitalizations between groups of varying underlying cardiovascular risk profiles, lifestyle and dietary habits. Specifically, we aimed to determine the incidence for HF hospitalizations from January 2007 to December 2016 using population-based data in Malaysia. METHODS Study design and setting This was a retrospective study using the national hospital discharge database. Data was extracted from the Hospital Discharge Registers for the period of January 2007 until December 2016. Inpatient admission records from public and private hospitals were compiled in centralised database known as the Patient Management
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