Measuring the Global Burden of Disease

New England Journal of Medicine
August 1, 2013  Vol. 369 No. 5
http://www.nejm.org/toc/nejm/medical-journal

Review Article
Global Health
Measuring the Global Burden of Disease
Christopher J.L. Murray, M.D., D.Phil., and Alan D. Lopez, Ph.D.
N Engl J Med 2013; 369:448-457August 1, 2013DOI: 10.1056/NEJMra1201534
http://www.nejm.org/doi/full/10.1056/NEJMra1201534

Excerpt
It is difficult to deliver effective and high-quality care to patients without knowing their diagnoses; likewise, for health systems to be effective, it is necessary to understand the key challenges in efforts to improve population health and how these challenges are changing. Before the early 1990s, there was no comprehensive and internally consistent source of information on the global burden of diseases, injuries, and risk factors. To close this gap, the World Bank and the World Health Organization launched the Global Burden of Disease (GBD) Study in 1991.1 Although assessments of selected diseases, injuries, and risk factors in selected populations are published each year (e.g., the annual assessments of the human immunodeficiency virus [HIV] epidemic2), the only comprehensive assessments of the state of health in the world have been the various revisions of the GBD Study for 1990, 1999–2002, and 2004.1,3-10 The advantage of the GBD approach is that consistent methods are applied to critically appraise available information on each condition, make this information comparable and systematic, estimate results from countries with incomplete data, and report on the burden of disease with the use of standardized metrics.

The most recent assessment of the global burden of disease is the 2010 study (GBD 2010), which provides results for 1990, 2005, and 2010. Several hundred investigators collaborated to report summary results for the world and 21 epidemiologic regions in December 2012.11-18 Regions based on levels of adult mortality, child mortality, and geographic contiguity were defined. GBD 2010 addressed a number of major limitations of previous analyses, including the need to strengthen the statistical methods used for estimation.11 The list of causes of the disease burden was broadened to cover 291 diseases and injuries. Data on 1160 sequelae of these causes (e.g., diabetic retinopathy, diabetic neuropathy, amputations due to diabetes, and chronic kidney disease due to diabetes) have been evaluated separately. The mortality and burden attributable to 67 risk factors or clusters of risk factors were also assessed.

GBD 2010, which provides critical information for guiding prevention efforts, was based on data from 187 countries for the period from 1990 through 2010. It includes a complete reassessment of the burden of disease for 1990 as well as an estimation for 2005 and 2010 based on the same definitions and methods; this facilitated meaningful comparisons of trends. The prevalence of coexisting conditions was also estimated according to the year, age, sex, and country. Detailed results from global and regional data have been published previously.11-18

The internal validity of the results is an important aspect of the GBD approach. For example, demographic data on all-cause mortality according to the year, country, age, and sex were combined with data on cause-specific mortality to ensure that the sum of the number of deaths due to each disease and injury equaled the number of deaths from all causes. Similar internal-validity checks were used for cause-specific estimates related to impairments such as hearing loss and vision loss, anemia, heart failure, intellectual disability, infertility, and epilepsy when there were substantial data on the overall levels of the impairment.

Although GBD 2010 provides the most comprehensive and consistent assessment of global data on descriptive epidemiology, there remain many limitations. There were insufficient data on many diseases, injuries, and risk factors from many countries. Estimates depended on sophisticated statistical modeling to address sparse and often inconsistent data.13,16,19,20 All outcomes were measured with 95% uncertainty intervals, which captured uncertainty from sampling, nonsampling error from the study designs or diagnostic methods, model parameter uncertainty, and uncertainty regarding model specification. This combined assessment of uncertainty was meant to communicate the strength of the evidence available for a particular condition in a particular place…