IHME Data
Download datasets created by IHME for our research projects and publications. You can learn more about our research and publications on our website
Data made available for download on IHME Websites can be used, shared, modified or built upon by non-commercial users in accordance with the IHME FREE-OF-CHARGE NON-COMMERCIAL USER AGREEMENT. For more information (and inquiries about commercial use), visit IHME Terms and Conditions.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries. These tables contain International Classification of Diseases (ICD) codes, for both ICD-9 and ICD-10, mapped to GBD 2016 causes of death and nonfatal causes.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
This dataset provides population estimates by location, age, and sex for 1950-2016. Data sources used to produce these estimates include World Population Prospects: 2015 Revision, from the United Nations Population Division, and the WHO Human Mortality Database.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
Developed by GBD researchers and used to help produce these estimates, the Socio-demographic Index (SDI) is a summary measure of a geography's socio-demographic development. It is based on average income per person, educational attainment, and total fertility rate (TFR). SDI contains an interpretable scale: zero represents the lowest income per capita, lowest educational attainment, and highest TFR observed across all GBD geographies from 1970 to 2016, and one represents the highest income per capita, highest educational attainment, and lowest TFR. This dataset provides tables with SDI values for all estimated GBD 2016 geographies for 1970–2016 and groupings by geography based on 2016 values.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
In GBD, an essential stage in the process for producing estimates for adult mortality rates (or 45q15, the probability of death between exact ages 15 and 60) involves assessing the completeness of adult death reporting from vital registration and censuses. In this evaluation, raw data points from vital registration and sample registration are adjusted using formal demographic techniques called death distribution methods (DDM) and then smoothed to generate full time-series estimates of adult death reporting completeness. This dataset contains a list of data input sources used in the generation of DDM estimates for adult mortality.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
This reference life table is used in GBD to calculate years of life lost (YLLs). It was constructed based on the lowest estimated age-specific mortality rates from all locations with populations over 5 million in the 2015 iteration of GBD. YLLs are computed by multiplying the number of estimated deaths by the reference life table’s life expectancy at age of death. The table includes estimates for the probability of death within an age range, the proportion of the hypothetical cohort still alive at age x, and life expectancy at age x for ages 0 to 110+ at five-year intervals.
The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries.
Covariates, which are independent variables with a positive or negative relationship to GBD diseases and conditions, are used to inform the estimation process in all models of the GBD study. Types of covariates used include socioeconomic, demographic, health system access, climate, and food consumption. This dataset contains data for 565 covariates for 1980-2016 used in the GBD 2016 study. Please note that data for England is not included for some covariates.
Data files are available to download at this location.
Research by the Global Burden of Disease Health Financing Collaborator Network produced forecasted health spending estimates for 2015-2040 for 184 countries. The estimates cover total health spending, and health spending disaggregated by source into government spending, out-of-pocket, prepaid private, and development assistance for health. GDP and all-sector government spending were extracted for 1980–2015 and used with retrospective health spending estimates for 1995-2014 to forecast GDP, all-sector government spending, and health spending through 2040. Results of the study were published in The Lancet in April 2017 in "Future and potential spending on health 2015–40: government, prepaid private, out-of-pocket, and donor financing in 184 countries."
Research by the Global Burden of Disease Health Financing Collaborator Network produced retrospective national health spending estimates for 1995-2014 for 184 countries. The estimates cover total health spending, and health spending disaggregated by source into government spending, out-of-pocket, prepaid private, and development assistance for health. National health spending by source, including development assistance for health, was estimated based on a diverse set of data, including program reports, budget data, national estimates, and 964 National Health Accounts. The resulting estimates were used to help produce forecasted health spending estimates for 2015-2040. Results of the study were published in The Lancet in April 2017 in "Evolution and patterns of global health financing 1995–2014: development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries."
This update of the Development Assistance for Health (DAH) Database includes estimates for 1990-2016, which are based on project databases, financial statements, annual reports, IRS 990s, and correspondence with agencies. The DAH Database enables comprehensive analysis of trends in international disbursements of grants and loans for health projects in low and middle income countries from key agencies. The data are disaggregated by funding agency, country and geographic region, and health focus area. New in 2016 is a program area disaggregation within malaria health focus areas.
To understand the framework used to track DAH, users of the DAH Database 1990-2016 should review IHME's Financing Global Health 2016 technical report and methods annex.
IHME research produced estimates on US health care spending by age, sex, condition, and type of care, from 1996 through 2013, for children and adolescents ages 19 years and younger. Government budgets, insurance claims, facility surveys, household surveys, and official US records for the period were collected and combined. In total, 183 sources of data were used to estimate spending for 155 conditions. For each record, spending was extracted, along with the age and sex of the patient, and the type of care. Study results were published in JAMA Pediatrics in December 2016 in “Spending on Children’s Personal Health Care in the United States, 1996-2013.”
IHME research produced estimates for US health care spending by age, sex, condition, and type of care from 1996 to 2013. Government budgets, insurance claims, facility surveys, household surveys, and official US records for the period were collected and combined. In total, 183 sources of data were used to estimate spending for 155 conditions (including cancer, which was disaggregated into 29 conditions), and 38 age and sex groups. For each record, spending was extracted, along with the age and sex of the patient, and the type of care. Study results were published in JAMA in December 2016 in “US Spending on Personal Health Care and Public Health, 1996-2013.”
This update of the Development Assistance for Health (DAH) Database includes estimates for 1990-2015, which are based on project databases, financial statements, annual reports, IRS 990s, and correspondence with agencies. The DAH Database enables comprehensive analysis of trends in international disbursements of grants and loans for health projects in developing countries from key agencies. The data are disaggregated by funding agency, country and geographic region, and health focus area. New in 2015 is a program area disaggregation within HIV/AIDS health focus areas.
To understand the framework used to track DAH, users of the DAH Database 1990-2015 should review IHME's Financing Global Health 2015 policy report and methods annex.
This 2014 update of the Development Assistance for Health (DAH) Database includes estimates for 1990-2014, which are based on project databases, financial statements, annual reports, IRS 990s, and correspondence with agencies. The DAH Database enables comprehensive analysis of trends in international disbursements of grants and loans for health projects in developing countries from key agencies. The data are disaggregated by funding agency, country and geographic region, and health focus area.
To understand the framework used to track DAH, users of the DAH Database 1990-2014 should review IHME's Financing Global Health 2014 policy report and methods annex.
An updated version of the database with DAH estimates through 2015 is now available.
These data capture the development assistance for health (DAH) provided to faith-based organizations (FBOs), as divided among FBO and non-FBO funding. The data available for download also show FBO DAH divided by health focus area as well as by funder, providing the FBO DAH furnished by the Global Fund and the Gates Foundation. These results were published in PLOS One in May 2015 in "Estimating the development assistance for health provided to faith-based organizations, 1990-2013."
IHME research produced alcohol use prevalence estimates (including estimates for any drinking, heavy drinking, and binge drinking) by county, year, and sex for 2002-2012. The data also include changes by percent for the period. The estimates were produced by applying small area models to data from the Behavioral Risk Factor Surveillance System (BRFSS). This dataset contains estimates for all states and counties, the District of Columbia, and the US as a whole, along with data on the 10 counties with the highest and lowest rates of any, heavy, and binge drinking by sex. Study results were published in the American Journal of Public Health in April 2015 in "Drinking patterns in US counties from 2002 to 2012."
This 2013 update of the Development Assistance for Health (DAH) database includes estimates for 1990-2011, which are based on project databases, financial statements, annual reports, IRS 990s, and correspondence with agencies.
The DAH database enables comprehensive analysis of trends in international disbursements for health from sources of funding and channels of funding and for recipient countries/geographic regions in health focus areas. The data associated with previous versions of IHME's Financing Global Health report were presented as two databases, the DAH country and regional recipient level database, and the DAH database. This year, in an effort to make the data more accessible to researchers, these databases have been combined.
To understand the framework used to track DAH, we recommend that users of the DAH database 1990-2011 review IHME's Financing Global Health 2013 policy report and methods appendix.
The 2012 update of the Development Assistance for Health (DAH) database enables analysis of trends in disbursements on grants/loans from key agencies by funding agency, country/geographic region, and health focus area.
These DAH totals do not match those in the IHME DAH 1990-2010 database. This database only contains DAH allocable by country and/or region and does not contain DAH that could not be traced to a specific region or country.
The 1990-2008 database is available here, and the 1990-2009 database is available here.
This is the 2012 update of the Development Assistance for Health (DAH) database, which includes estimates based on project databases, financial statements, annual reports, IRS 990s, and correspondences with agencies.
It enables estimation of DAH envelope (disbursements and expenditures), trends in DAH (disbursements and expenditures) by global health institutions, and trends in DAH (disbursements and expenditures) by source of income. Also provided is a code file to generate figures based on the database.
The 1990-2008 database is available here, and the 1990-2009 database is available here.
This December 2011 updated database includes US-based non-governmental organizations' (NGOs) financial data from USAID VolAg report years 1992-2010 (covers fiscal years 1990-2008) with unique ID codes added. The VolAg reports can be found on the USAID website.
The 1990-2007 database is available here.
This is the December 2011 update of the Development Assistance for Health (DAH) database which includes estimates based on data project databases, financial statements, annual reports, IRS 990s, and correspondences with agencies.
It enables estimation of DAH envelope (disbursements and expenditures), trends in DAH (disbursements and expenditures) by global health institutions, and trends in DAH (disbursements and expenditures) by source of income.
The 1990-2008 database is available here.
The December 2011 update of the Development Assistance for Health (DAH) database enables analysis of trends in disbursements on grants/loans from key agencies by funding agency, country/geographic region, and health focus area.
These DAH totals do not match those in the IHME DAH 1990-2009 database. This database only contains DAH allocable by country/region.
The 1990-2008 database is available here.
This database includes US-based non-governmental organizations' (NGOs) financial data from USAID VolAg report years 1992-2009 (covers fiscal years 1990-2007) with unique ID codes added. The VolAg reports can be found on the USAID website.
2011 update available here.
This database includes Development Assistance for Health (DAH) project databases that enable analysis of trends in disbursements on grants and loans from key agencies by funding agency, country/geographic region, and health focus area.
Note: The DAH totals in this database do not match up with those in the IHME Development Assistance for Health Database 1990-2008 because this database only contains DAH allocable by country and/or region and does not contain DAH that could not be traced to a specific region or country.
2011 update available here.
These IHME results are from the paper, "Public financing of health in developing countries: a cross-national systematic analysis," published in The Lancet in April 2010. This dataset provides estimates on domestically financed government health expenditures in developing countries and development assistance for health (DAH) to governmental and non-governmental recipients from 1995 to 2006.
This database includes development assistance for health (DAH) estimates based on data project databases, financial statements, annual reports, IRS 990s, and correspondences with agencies.
It enables estimation of the DAH envelope (disbursements and expenditures), trends in by global health institutions, and trends in DAH by source of income.
Graphing and additional use information are available in the "IHME_DAH_DATABASE_1990_2008_CODE.txt" file.
2011 update available here.
IHME results, published in November 2010, provide a global assessment of trends in development assistance for health (DAH) from 1990 to 2008 and preliminary estimates for 2009 and 2010. The report, Financing Global Health 2010: Development Assistance and Country Spending in Economic Uncertainty, compiles contributions by all significant public and private channels of development assistance for improving health outcomes and strengthening health systems in low- and middle-income countries.
This survey was conducted as part of the Gavi Full Country Evaluation (FCE) project in Uganda. Gavi FCEs are prospective studies covering the period 2013-2016 that aim to assess the barriers to and drivers of immunization program performance. The Uganda FCE Household Survey was conducted in 19 districts purposely selected to overlap with districts where the FCE Health Facility Survey was conducted in 2014-2015. The initial sample size for the household survey was 3,990 households. Data were collected from heads of households and mothers and/or primary caregivers of children ages 0-59 months. Topics covered include household characteristics, immunization knowledge, birth histories of mothers and child caretakers, pregnancy and postnatal care, child feeding practices, current health and vaccine status of the child, and vaccination experience at health facilities. In a sub-sample of children, a small amount of blood was collected in order to measure vaccine presence.
This survey was conducted as part of the Gavi Full Country Evaluation (FCE) project in Uganda. Gavi FCEs are prospective studies covering the period 2013-2016 that aim to assess the barriers to and drivers of immunization program performance. The Uganda FCE was conducted in 19 districts purposely selected to overlap with those where a baseline facility survey for the Access, Bottlenecks, Costs, and Equity (ABCE) Project in Uganda was performed. The districts provide a geographically and demographically representative sample of Uganda’s health system. For the FCE Health Facility Survey, data on financing, staffing, facility procedures and guidelines, vaccine stocks, and supply delivery (including cold chain temperature measurements) were collected from a representative sample of 177 health facilities. Data were collected through interviews of health providers, direct observation of facility areas, and assisted observation of immunization sessions.
IHME research produced estimates for age-standardized mortality rates by county from chronic respiratory diseases. The estimates were generated using de-identified death records from the National Center for Health Statistics (NCHS); population counts from the U.S. Census Bureau, NCHS, and the Human Mortality Database; the cause list from the Global Burden of Disease Study (GBD); and the application of small area estimation models. This dataset provides estimates for age-standardized mortality rates by disease type and sex at the county level for each state, the District of Columbia, and the United States as a whole for 1980-2014, as well as the changes in rates for each location during this period. Also included are data on the 10 counties with the highest and lowest mortality rates for each disease type in 2014. Study results were published in JAMA in September 2017 in "Trends and patterns of differences in chronic respiratory disease mortality among US counties, 1980–2014."
IHME research produced estimates for life expectancy and cause-specific mortality at the census tract level for King County, Washington, for 1990-2014. The estimates were generated using death registration data from the Center for Health Statistics, Washington State Department of Health; population counts by age group, sex, and census tract from the Washington State Office of Financial Management; the cause list developed for the Global Burden of Disease Study 2015; and the application of small area estimation models. This dataset, downloadable via the "Files" tab above, provides estimates for life expectancy at birth, mortality rates, and years of life lost rates for 152 causes of death by age and sex for 397 census tracts. Results of the study were published in The Lancet Public Health in September 2017 in "Variation in life expectancy and mortality by cause among neighbourhoods in King County, WA, USA, 1990–2014: a census tract-level analysis for the Global Burden of Disease Study 2015."
This survey was conducted as part of the Gavi Full Country Evaluation (FCE) project in Bangladesh. Gavi FCEs are prospective studies covering the period 2013-2016 that aim to assess the barriers to and drivers of immunization program performance. The Bangladesh FCE focused on selected locations stratified by urban/rural and low/high immunization coverage performance areas. It was conducted in one rural district and one city corporation each in the divisions of Sylhet and Rajshahi. This survey collected information from patient exit interviews conducted with caregivers of children 9 months to 15 years of age immediately following their measles-rubella vaccination. Topics covered include sociodemographic characteristics of the caretaker; patient experiences at the facility; patient opinions of the experience; and knowledge, attitudes and practice regarding measles and rubella immunizations, as well as knowledge of measles and rubella symptoms, prevention, and treatment.
This survey was conducted as part of the Gavi Full Country Evaluation (FCE) project in Bangladesh. Gavi FCEs are prospective studies covering the period 2013-2016 that aim to assess the barriers to and drivers of immunization program performance. The Bangladesh FCE focused on selected locations stratified by urban/rural and low/high immunization coverage performance areas. It was conducted in one rural district and one city corporation each in the divisions of Sylhet and Rajshahi. The health facility survey collected data from facilities administering vaccinations as part of a measles-rubella vaccine campaign. Data on vaccine campaign proceedings were collected through interviews of health providers and the direct observation of child vaccinations. Topics covered include general characteristics of the location, campaign logistics and functionality, supply chain and record keeping.
The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level.
As part of this study, estimates for obesity and overweight prevalence and the disease burden attributable to high body mass index (BMI) were produced by sex, age group, and year for 195 countries and territories. Estimates for high BMI-attributable deaths, DALYs, and other measures (1990-2015) are available from the GBD Results Tool. Files available in this record include obesity and overweight prevalence estimates for 1980-2015. Study results were published in The New England Journal of Medicine in June 2017 in "Health Effects of Overweight and Obesity in 195 Countries over 25 Years."
This survey was conducted as part of the Gavi Full Country Evaluation (FCE) project in Bangladesh. Gavi FCEs are prospective studies covering the period 2013-2016 that aim to assess the barriers to and drivers of immunization program performance. The Bangladesh FCE focused on selected locations stratified by urban/rural and low/high immunization coverage performance areas. It was conducted in one rural district and one city corporation each in the divisions of Sylhet and Rajshahi. This survey collected information at the household level prior to the implementation of a measles-rubella vaccine campaign. It covered sociodemographic characteristics; knowledge, treatment and management of measles and rubella; vaccination status of children (including immunization card documentation); and access to vaccination services and experience at health facilities. In a sub-sample of children, a small amount of blood was collected in order to measure vaccine presence. In total, 1,735 households were sampled.
Global Burden of Disease Study 2015 (GBD 2015) estimates were used in an analysis of national levels of personal healthcare access and quality based on 32 causes of disease and injury considered amenable to healthcare over time. This dataset includes the following global, regional, and national or territory-level estimates for 1990-2015: age-standardized risk-standardized death rates for 32 causes considered amenable to healthcare; the Healthcare Quality and Access (HAQ) Index and individual indices for each of the 32 causes on a scale of 0 to 100; and a frontier based on the relationship between the HAQ Index and the Socio-demographic Index (SDI).
Results were published in The Lancet in May 2017 in "Healthcare Access and Quality Index based on mortality from causes amenable to personal healthcare in 195 countries and territories, 1990–2015: a novel analysis from the Global Burden of Disease Study 2015."
IHME research used de-identified death records from the National Center for Health Statistics (NCHS) and population counts from the U.S. Census Bureau, NCHS, and the Human Mortality Database and small area estimation models in order to estimate county-level mortality rates from all cardiovascular diseases (CVD), including ischemic heart disease, cerebrovascular disease, ischemic stroke, and other types. This dataset provides estimates for age-standardized mortality rates by CVD type and sex at the county level for each state, the District of Columbia, and the United States as a whole for 1980-2014, as well as the changes in rates for each location during this period. Also included are data on the 10 counties with the highest and lowest mortality rates for each CVD type in 2014 and the top 10 causes of death by CVD type for each county. Study results were published in JAMA in May 2017 in "Trends and patterns of geographic variations in cardiovascular mortality among US counties, 1980–2014."
Research by IHME used small area estimation methods to produce annual life tables and calculate age-specific mortality risk at the county level for the United States. De-identified death records from the National Center for Health Statistics (NCHS) and population counts from the census bureau, NCHS, and the Human Mortality Database were used in the analysis. This dataset provides estimates for life expectancy at birth and mortality risk for under-5 and 20-year age groups at the county level for each state, the District of Columbia, and the United States as a whole for 1980-2014, as well as the changes in life expectancy and mortality risk for each location during this period. Also included are data on the 30 counties with the highest and lowest life expectancy and mortality risks. Results of the study were published in JAMA in May 2017 in "Inequalities in life expectancy among US counties, 1980–2014."
The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level.
As part of this study, estimates for daily smoking prevalence and smoking-attributable mortality and disease burden, as measured by disability-adjusted life years (DALYs), were produced by sex, age group, and year for 195 countries and territories. Estimates for deaths and DALYs (1990-2015) are available from the GBD Results Tool. Files available in this record include daily smoking prevalence (1980-2015) and annualized rate of change estimates. Study results were published in The Lancet in April 2017 in "Smoking prevalence and attributable disease burden in 195 countries and territories, 1990–2015: a systematic analysis from the Global Burden of Disease Study 2015."
The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level. These location hierarchies files contain the GBD 2015 reporting hierarchy and a number of other hierarchies, which will allow GBD 2015 results users to aggregate results by location in various ways (by GBD regions, World Bank regions, OECD countries, European Union countries, etc.).
IHME research used de-identified death records from the National Center for Health Statistics (NCHS) and population counts from the U.S. Census Bureau, NCHS, and the Human Mortality Database and small area estimation models in order to estimate county-level mortality rates from 29 cancers. This dataset provides estimates for age-standardized mortality rates by cancer type and sex at the county level for each state, the District of Columbia, and the United States as a whole for 1980-2014, as well as the changes in rates for each location during this period. Also included are data on the 10 counties with the highest and lowest mortality rates for each cancer type in 2014 and the top 10 causes of death by cancer type for each county. Study results were published in JAMA in January 2017 in "Trends and patterns of disparities in cancer mortality among US counties, 1980-2014."
The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level.
As part of this study, the health burden associated with systolic blood pressure (SBP) ≥ 110-115 mm HG and SBP ≥ 140 mm HG (hypertension) was analyzed. Estimates for deaths, YLLs, YLDs, and DALYs attributable to SBP ≥ 110-115 mm HG (high systolic blood pressure) by age and sex for 21 regions, 195 countries and territories and select subnational units for 1990-2015 (quinquennial) are available from the GBD Results Tool. Files available in this record include deaths and DALYs attributable to hypertension and the web tables published in JAMA in January 2017 in "Global Burden of Hypertension and Systolic Blood Pressure of at least 110 to 115 mm HG, 1990-2015."
The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level.
Estimates for deaths, disability-adjusted life years (DALYs), years lived with disability, years of life lost (YLLs), prevalence, and incidence for 32 cancer groups by age and sex for 21 regions, 195 countries and territories, and select subnational units for 1990-2015 (quinquennial) are available from the GBD Results Tool. Files available in this record are the web tables published in JAMA Oncology in December 2016 in "Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived with Disability, and Disability-Adjusted Life Years for 32 Cancer Groups, 1990-2015: A Systematic Analysis for the Global Burden of Disease Study."
IHME research applied a novel methodology to death registration data from the National Vital Statistics System (NVSS) in order to estimate annual county-level mortality rates for 21 mutually exclusive causes of death. This dataset provides estimates for cause-specific age-standardized mortality rates at the county level for each state, the District of Columbia, and the United States as a whole for 1980-2014 (quinquennial), as well as the changes in rates during this period. Also included are data on the 10 counties with the highest and lowest mortality rates for each cause in 2014. Study results were published in JAMA in December 2016 in "US county-level trends in mortality rates for major causes of death, 1980–2014."
IHME research, published in Diabetes Care in August 2016, "Diagnosed and Undiagnosed Diabetes Prevalence by County in the U.S., 1999–2012," produced estimates by county and sex for the prevalence of diagnosed, undiagnosed, and total diabetes, as well as rates of diagnosis and effective treatment for 1999-2012. The dataset contains estimates for all states and counties, the District of Columbia, and the United States as a whole.
The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level.
This reference life table is used in GBD to calculate Years of Life Lost (YLLs). It was constructed based on the lowest estimated age-specific mortality rates from all locations with populations over 5 million in the 2013 iteration of GBD. YLLs are computed by multiplying the number of estimated deaths by the reference life table’s life expectancy at age of death. The table includes estimates for the probability of death within an age range, the proportion of the hypothetical cohort still alive at age x, and life expectancy at age x for ages 0 to 110+ at five-year intervals.
The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level. These tables contain International Classification of Diseases (ICD) codes, for both ICD-9 and ICD-10, mapped to GBD 2015 causes of death and nonfatal causes.
The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level.
Developed by GBD researchers and used to help produce these estimates, the Socio-demographic Index (SDI) is a summary measure of a geography's socio-demographic development. It is based on average income per person, educational attainment, and total fertility rate (TFR). SDI contains an interpretable scale: zero represents the lowest income per capita, lowest educational attainment, and highest TFR observed across all GBD geographies from 1980 to 2015, and one represents the highest income per capita, highest educational attainment, and lowest TFR. This dataset provides tables with SDI values for all estimated GBD 2015 geographies for 1980–2015 and groupings by geography based on 2015 values.
The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level.
Covariates, which are independent variables with a positive or negative relationship to GBD diseases and conditions, are used to inform the estimation process in all models of the GBD study. Types of covariates used include socioeconomic, demographic, health system access, climate, and food consumption. This dataset contains data for 296 covariates for 195 countries and territories, plus 4 United Kingdom subnational units for 1980-2015 used in the GBD 2015 study. Data files are available to download at this location. Please note that data for England is not included for some covariates.
The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level.
Disability weights, which represent the magnitude of health loss associated with specific health outcomes, are used to calculate years lived with disability for these outcomes in a given population. The weights are measured on a scale from 0 to 1, where 0 equals a state of full health and 1 equals death. This dataset provides the disability weights for the 235 unique health states used to estimate nonfatal health outcomes for the GBD 2015 study. These data were published in The Lancet in October 2016 in "Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015."
The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level. This dataset provides population estimates for 21 GBD regions, 195 countries and territories, and 4 United Kingdom subnational units by age and sex for 1970-2015. Data sources used to produce these estimates include World Population Prospects: 2015 Revision, from the United Nations Population Division, and the WHO Human Mortality Database.
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