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

疾病负担 疾病负担 医学 潜在生命损失数年 人口 疾病 伤残调整生命年 预期寿命 质量调整寿命年 环境卫生 人口学 成本效益 风险分析(工程) 病理 社会学
作者
Chenkun Zhao,Ching Choi,Paula Laws,Michelle Gourley,Annette Dobson,Tim Driscoll,Laura Kirkland,Lynelle Moon,Richard Juckes
出处
期刊:International Journal of Epidemiology [Oxford University Press]
卷期号:51 (2): 668-678 被引量:4
标识
DOI:10.1093/ije/dyab093
摘要

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)].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.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.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 National studies such as the ABDS have the flexibility to meet local needs and often the advantage of access to unpublished data.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.

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