- What is GBD and why is it important?
- What countries are in each region?
- How can I find the results for my country?
- Why aren't the data visualizations working on my computer?
- What is a DALY?
- What is a YLL?
- What is a YLD?
- What is life expectancy?
- What is HALE?
- What is TFR?
- What is SDI?
- What are sequelae?
- What are health states?
- What are disability weights?
- What is an uncertainty interval?
- What are “risk-attributable deaths” or “risk-attributable DALYs”?
- Is there a full list of GBD causes?
- Where can I access GBD data?
- What is IHME's policy for sharing the raw data that were used in the GBD analysis?
- Why are age-specific neonatal mortality rates often greater than 1.0?
The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) is the single largest and most detailed scientific effort ever conducted to quantify levels and trends in health. Led by the Institute for Health Metrics and Evaluation (IHME) at the University of Washington, it is truly a global effort, with over 6,500 researchers from more than 155 countries and territories participating in the most recent update.
GBD creates a unique platform to compare the magnitude of diseases, injuries, and risk factors across age groups, sexes, countries, regions, and time. For decision-makers, health sector leaders, researchers, and informed citizens, the GBD approach provides an opportunity to compare their countries’ health progress to that of other countries, and to understand the leading causes of health loss that could potentially be avoided, like high blood pressure, smoking, and household air pollution.
IHME provides GBD results in visualization tools, allowing people to interact with the vast amounts of data and the trends they identify. These unique tools are beneficial when trying to identify specific information for age groups, sexes, causes, risks, and comparison to other regions.
For more information about GBD, visit the project page.
To interact with the results data and explore the findings, visit the data visualizations.
GBD created regions based on two criteria: epidemiological similarity and geographic closeness. To see a full list of countries and their corresponding regions, click here.
For some types of analysis in the GBD, seven super-regions have been established, which group regions on the basis of cause of death patterns. The image below shows which regions belong to each super-region.
You can download country profiles that summarize the major GBD findings.
Also, IHME has created interactive data visualizations, hands-on tools that allow the viewer to explore IHME's data using charts that update based on viewer selections. Visit IHME's data visualizations to begin your interactive experience.
Due to the extensive data accessible in IHME's data visualizations, they require time and internet bandwidth to load. If you are having trouble loading a visualization, we suggest that you refresh the page. We also suggest that you access the visualizations with the most up-to-date version of your internet browser. Use the links below to identify the recommended versions of these internet browsers. The visualizations work best in Chrome and Internet Explorer 10.
DALY is an abbreviation for disability-adjusted life year. It is a universal metric that allows researchers and policymakers to compare very different populations and health conditions across time. DALYs equal the sum of years of life lost (YLLs) and years lived with disability (YLDs). One DALY equals one lost year of healthy life. DALYs allow us to estimate the total number of years lost due to specific causes and risk factors at the country, regional, and global levels.
Years of life lost (YLLs) are years lost due to premature mortality. YLLs are calculated by subtracting the age at death from the longest possible life expectancy for a person at that age. For example, if the longest life expectancy for men in a given country is 75, but a man dies of cancer at 65, this would be 10 years of life lost due to cancer.
YLD is an abbreviation for years lived with disability, which can also be described as years lived in less than ideal health. This includes conditions such as influenza, which may last for only a few days, or epilepsy, which can last a lifetime. It is measured by taking the prevalence of the condition multiplied by the disability weight for that condition. Disability weights reflect the severity of different conditions and are developed through surveys of the general public.
Life expectancy is the number of years a person can expect to live at any given age.
HALE is often referred to as healthy life expectancy. Unlike life expectancy, HALE takes into account mortality and nonfatal outcomes. HALE does this by summarizing years lived in less than ideal health (YLDs) and years lost due to premature mortality (YLLs) in a single measure of average population health for individual countries.
TFR is an abbreviation for total fertility rate, a summary measure representing the average number of children a woman would deliver over her lifetime.
SDI is an abbreviation for Socio-demographic Index, a summary measure that identifies where countries or other geographic areas sit on the spectrum of development.
It is expressed on a scale of 0 to 100, with 0 being the lowest SDI value and 100 being the highest. SDI was constructed based on three measures: i) income per capita; ii) average years of schooling; and iii) total fertility rate (TFR).
For example, a low SDI value will be assigned to a country with lower income per capita, fewer average years of schooling, and higher TFR relative to other countries; conversely, a higher SDI value will be assigned to a country with higher income per capita, greater average years of schooling, and lower TFR relative to other countries.
Sequelae are consequences of diseases and injuries.
Health states are groupings of sequelae that reflect key differences in symptoms and functioning.
Disability weights represent the severity of health loss associated with a health state.
Uncertainty intervals are a range of values that are likely to include the correct estimate of health loss for a given cause. Limited data create substantial uncertainty.
The share of deaths or DALYs that can be attributed to – i.e., estimated to occur due to – exposure to a particular risk factor (e.g., alcohol-attributable deaths, or deaths attributable to air pollution, etc.)
For a full list of causes (diseases and injuries) from the GBD study, click here.
The more than 350 causes of health loss studied within the GBD are arranged in hierarchical nested categories – referred to as “levels” – within the GBD “cause lists.” At the highest level, causes are split into very large categories: communicable, maternal, neonatal, and nutritional causes; non-communicable diseases; and injuries. Within each of those categories, causes of health loss are broken down with increasing specificity at each level. For example, consider typhoid fever, which is a level 4 cause in the GBD cause list:
Level 1: Communicable, maternal, neonatal, and nutritional diseases
Level 2: Enteric infections
Level 3: Typhoid and paratyphoid
Level 4: Typhoid fever
The cause list is mutually exclusive and collectively exhaustive at every level of aggregation; causes not individually specified are captured in residual categories, such as “other intestinal infectious diseases.”
GBD results are available for download from the Global Health Data Exchange (GHDx), IHME's catalog of the world's health and demographic data. Click here to access and download the data.
IHME’s mission is to improve the health of the world’s population by making available the highest-quality information on population health, its determinants, and the performance of health systems. Transparency is one of IHME’s core principles, and we are working to help expand access to the raw data that we use in our evaluations. The Data & Methods Access Policy outlines how IHME shares input data and results and how it enables others to understand our research findings and methods.
Mortality rates can be greater than 1.0 for early neonatal (ENN or 0-6 days), late neonatal (LNN or 7-27 days), and post neonatal (PNN or 28-364 days) age groups because there is the opportunity for more deaths to occur within an age group than the population within them.
For example, in the ENN age group, each child spends 7 days out of the full 365 days of the year there. The population of the ENN age group is the person-years spent in the age group, so roughly 365 / 7 = 52 people would need to progress smoothly through the ENN group to contribute one person-year towards the ENN population. Even more people would be required if the death rate in the ENN age group was particularly high, and many children only contributed one or two days to the ENN age group before dying.
In summary, at least 52 people must pass through the ENN age group in order to generate one person-year of time for the ENN population estimate. Following this, if there were more than one death out of the 52 who passed into the ENN age group, then more than one death per person-year of population would be recorded, leading to a mortality rate greater than 1.0.