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Value of a national burden-of-disease study: a comparison of estimates between the Australian Burden of Disease Study 2015 and the Global Burden of Disease Study 2017.

Authors :
Zhao, Chenkun
Choi, Ching
Laws, Paula
Gourley, Michelle
Dobson, Annette
Driscoll, Tim
Kirkland, Laura
Moon, Lynelle
Juckes, Richard
Source :
International Journal of Epidemiology; Apr2022, Vol. 51 Issue 2, p668-678, 11p
Publication Year :
2022

Abstract

<bold>Background: </bold>Estimates of burden of disease are important for monitoring population health, informing policy and service planning. Burden estimates for the same population can be reported differently by national studies [e.g. the Australian Burden of Disease Study (ABDS) and the Global Burden of Disease Study (GBDS)].<bold>Methods: </bold>Australian ABDS 2015 and GBDS 2017 burden estimates and methods for 2015 were compared. Years of life lost (YLL), years lived with disability (YLD) and disability-adjusted life years (DALY) measures were compared for overall burden and 'top 50' causes. Disease-category definitions (based on ICD-10), redistribution algorithms, data sources, disability weights, modelling methods and assumptions were reviewed.<bold>Results: </bold>GBDS 2017 estimated higher totals than ABDS 2015 for YLL, YLD and DALY for Australia. YLL differences were mainly driven by differences in the allocation of deaths to disease categories and the redistribution of implausible causes of death. For YLD, the main drivers were data sources, severity distributions and modelling strategies. Most top-50 diseases for DALY had a similar YLL:YLD composition reported.<bold>Conclusions: </bold>Differences in the ABDS and GBDS estimates reflect the different purposes of local and international studies and differences in data and modelling strategies. The GBDS uses all available evidence and is useful for international comparisons. National studies such as the ABDS have the flexibility to meet local needs and often the advantage of access to unpublished data. It is important that all data sources, inputs and models be assessed for quality and appropriateness. As studies evolve, differences should be accounted for through increased transparency of data and methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03005771
Volume :
51
Issue :
2
Database :
Complementary Index
Journal :
International Journal of Epidemiology
Publication Type :
Academic Journal
Accession number :
156763605
Full Text :
https://doi.org/10.1093/ije/dyab093