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    Estimating global injuries morbidity and mortality: methods and data used in the Global Burden of Disease 2017 study

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    Author
    James, Spencer Lewis
    Memiah, Peter T.N.
    Date
    2020-10-01
    Journal
    Injury Prevention
    Publisher
    BMJ Publishing Group
    Type
    Article
    
    Metadata
    Show full item record
    See at
    https://doi.org/10.1136/injuryprev-2019-043531
    Abstract
    BACKGROUND: While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. METHODS: In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. RESULTS: GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. CONCLUSIONS: GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future. © Author(s)
    Keyword
    descriptive epidemiology
    methodology
    populations/contexts
    statistical issues
    Identifier to cite or link to this item
    http://hdl.handle.net/10713/13959
    ae974a485f413a2113503eed53cd6c53
    10.1136/injuryprev-2019-043531
    Scopus Count
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    UMB Open Access Articles 2020

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