{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T06:14:38Z","timestamp":1765779278680,"version":"3.48.0"},"reference-count":25,"publisher":"CSIRO Publishing","issue":"6","license":[{"start":{"date-parts":[[2025,5,29]],"date-time":"2025-05-29T00:00:00Z","timestamp":1748476800000},"content-version":"vor","delay-in-days":923,"URL":"https:\/\/doi.org\/10.1071\/journalslicense"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12,8]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Burden of disease studies measure the impact of disease at the population level;however, methods and data sources for estimates of prevalence vary. Using a selection of cardiovascular diseases, we aimed to describe the implications of using different disease models and linked administrative data on prevalence estimation within three Australian burden of disease studies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Three different methods (A\u00a0=\u00a02011 Australian Burden of Disease Study; B\u00a0=\u00a02015 Australian Burden of Disease Study; C\u00a0=\u00a02015 Western Australian Burden of Disease Study), which used linked data, were used to compare prevalence estimates of stroke, aortic aneurysm, rheumatic valvular heart disease (VHD) and non-rheumatic VHD. We applied these methods to 2015 Western Australian data, and calculated crude overall and age-specific prevalence for each condition.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Overall, Method C produced estimates of cardiovascular prevalence that were lower than the other methods, excluding non-rheumatic VHD. Prevalence of acute and chronic stroke was up to one-third higher in Method A and B compared to Method C. Aortic aneurysms had the largest change in prevalence, with Method A producing an eight-fold higher estimate compared to Method C, but Method B was 10\u201320% lower. Estimates of VHD varied dramatically, with an up to six-fold change in prevalence in Method C due to substantial changes to disease models and the use of linked data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Prevalence estimates require the best available data sources, updated disease models and constant review to inform government policy and health reform. Availability of nation-wide linked data will markedly improve future burden estimates.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1071\/ah22149","type":"journal-article","created":{"date-parts":[[2022,11,17]],"date-time":"2022-11-17T18:53:35Z","timestamp":1668711215000},"page":"756-764","source":"Crossref","is-referenced-by-count":1,"title":["Evolution of non-fatal burden estimates for cardiovascular disease in Australia: a comparison of national and state-wide methodology of burden of disease"],"prefix":"10.1071","volume":"46","author":[{"given":"Courtney","family":"Weber","sequence":"first","affiliation":[{"name":"ASchool of Population and Global Health, The University of Western Australia, WA, Australia."},{"name":"BCentre for Clinical Research in Emergency Medicine, Harry Perkins Institute of Medical Research, Perth, WA, Australia."},{"name":"CWestern Australian Department of Health, East Perth, WA, Australia."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michelle","family":"Hobday","sequence":"additional","affiliation":[{"name":"CWestern Australian Department of Health, East Perth, WA, Australia."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wendy","family":"Sun","sequence":"additional","affiliation":[{"name":"CWestern Australian Department of Health, East Perth, WA, Australia."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laura","family":"Kirkland","sequence":"additional","affiliation":[{"name":"CWestern Australian Department of Health, East Perth, WA, Australia."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lee","family":"Nedkoff","sequence":"additional","affiliation":[{"name":"ASchool of Population and Global Health, The University of Western Australia, WA, Australia."},{"name":"DCardiology Population Health Laboratory, Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Judith M.","family":"Katzenellenbogen","sequence":"additional","affiliation":[{"name":"ASchool of Population and Global Health, The University of Western Australia, WA, Australia."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"67","published-online":{"date-parts":[[2022,11,18]]},"reference":[{"issue":"10100","key":"2025121501101122900_R1","doi-asserted-by":"publisher","first-page":"1211","DOI":"10.1016\/S0140-6736(17)32154-2","article-title":"Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990\u20132016: a systematic analysis for the Global Burden of Disease Study 2016.","volume":"390","author":"Vos","year":"2017","journal-title":"Lancet"},{"key":"2025121501101122900_R2","doi-asserted-by":"publisher","first-page":"35","DOI":"10.12688\/wellcomeopenres.15011.1","article-title":"Metric partnerships: global 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