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Ranking the burden of disease attributed to known risk factors

Author

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  • Lorenzo Lionello
  • Emilie Counil
  • Emmanuel Henry

Abstract

The Global Burden of Disease’s (GBD) comparative risk assessment analysis (CRA) is a quantitative estimation of the contribution of known risk factors to the injuries and sequelae enumerated by the study each year. The CRA was introduced in 2002 and has a complex methodology that builds on the epidemiologic concept of attributable risk, or population attributable fractions (PAFs). This work, second of two volumes on the GBD’s evolution, is focused on explaining and tracing the methodological choices of its risk assessment component, with a specific focus on environmental and occupational risk factors. We explore the estimates provided by the Institute of Health Metrics and Evaluation (IHME) and understand how they were calculated. Then, we assess some of the most pressing critiques, and conclude by reflecting on its influence, methodological choices, and future outlook as the IHME sets itself a leading institution in health estimates. This work is part of a broader research analyzing the role of population health metrics, in particular PAFs, on the definition of public health problems and influencing their agendas. The research relies on a literature review (nonstructured) of published studies and commentaries. It follows a chronological development of the CRA estimates since their first publication in 2002 to the version released in 2019.

Suggested Citation

  • Lorenzo Lionello & Emilie Counil & Emmanuel Henry, 2021. "Ranking the burden of disease attributed to known risk factors," Working Papers 266, French Institute for Demographic Studies.
  • Handle: RePEc:idg:wpaper:axucny80kgkzhr-bmeo_
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    References listed on IDEAS

    as
    1. Lorenzo Lionello & Emilie Counil & Emmanuel Henry, 2021. "Measuring health at a global level with a unified tool: A review of institutional and methodological milestones of the Global Burden of Disease project," Working Papers 264, French Institute for Demographic Studies.
    2. Rockhill, B. & Newman, B. & Weinberg, C., 1998. "Use and misuse of population attributable fractions," American Journal of Public Health, American Public Health Association, vol. 88(1), pages 15-19.
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