Global Burden of Disease Study 2010
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| Global Burden of Disease Study 2010 | |
|---|---|
| Name | Global Burden of Disease Study 2010 |
| Abbreviation | GBD 2010 |
| Authors | Christopher J. L. Murray et al. |
| Published | 2012 |
| Discipline | Public health |
| Country | International |
| Institution | Institute for Health Metrics and Evaluation |
Global Burden of Disease Study 2010 The Global Burden of Disease Study 2010 was a comprehensive multinational assessment of mortality, causes of death, and disability across countries and territories, produced by an international collaboration led by the Institute for Health Metrics and Evaluation and published in 2012, informing policymakers and international agencies. The study synthesized data from national statistical offices, the World Health Organization, and research institutions to produce comparative metrics used by the United Nations, World Health Organization, Bill & Melinda Gates Foundation, and national ministries of health.
Background and objectives
The initiative built on earlier work by the World Bank, Harvard University, Johns Hopkins University, London School of Hygiene & Tropical Medicine, and the National Institutes of Health to standardize measures across diverse settings, aiming to quantify years of life lost and years lived with disability for 291 diseases and injuries in 187 countries. Key objectives linked to agendas of the United Nations General Assembly, Millennium Development Goals, G8 Summit, and the Global Fund to Fight AIDS, Tuberculosis and Malaria included enabling comparisons across populations to guide investment by actors such as the World Bank Group, United States Agency for International Development, European Commission, and philanthropic organizations like the Wellcome Trust.
Methods and data sources
The study used standardized metrics including disability-adjusted life years, combining mortality data from civil registration systems, verbal autopsy studies, and vital registration compiled by the United Nations Population Division, WHO Mortality Database, Demographic and Health Surveys, and the Global Burden of Disease collaborative network. Analytical methods incorporated statistical modeling from teams at Institute for Health Metrics and Evaluation, Imperial College London, University of Washington, and specialist centers such as the Children’s Investment Fund Foundation partners, integrating inputs from databases maintained by the International Classification of Diseases framework, the Global Burden of Disease 2004 dataset, and country-level registries like those of China, India, Brazil, South Africa, and Russia. Covariate data sources included inputs from the World Bank, Organisation for Economic Co-operation and Development, United Nations Development Programme, and global surveillance systems coordinated with the Centers for Disease Control and Prevention.
Results and key findings
GBD 2010 reported that non-communicable diseases such as ischemic heart disease and stroke had become leading causes of burden in many regions, alongside persistent communicable conditions like HIV/AIDS and malaria in parts of sub-Saharan Africa; these conclusions were cited by the World Health Assembly, Gavi, the Vaccine Alliance, UNAIDS, UNICEF, and national health ministries in policy reviews. The study quantified shifts in life expectancy and cause-specific mortality trends that affected planning at institutions including the European Centre for Disease Prevention and Control, Pan American Health Organization, African Union, BRICS health coalitions, and bilateral partners such as United Kingdom, United States, and China. High-burden risk factors identified—tobacco smoking, high blood pressure, and high body-mass index—were highlighted for action by bodies such as the Framework Convention on Tobacco Control signatories and public health agencies at the G20 level.
Regional and national estimates
The analysis produced country-level estimates for 187 countries and subnational estimates for large nations including China, India, United States, Brazil, Indonesia, and Mexico, enabling comparison across WHO regions, the European Union, African Union member states, and Pacific island states in coordination with agencies like the Asian Development Bank and the Inter-American Development Bank. Results informed national planning documents used by ministries in Ethiopia, Nigeria, Pakistan, Bangladesh, and South Africa and were integrated into assessment tools used by the World Bank Group and the International Monetary Fund for health investment projections.
Impact on health policy and interventions
Findings influenced prioritization by global initiatives such as the Global Fund, Gavi, the Vaccine Alliance, Roll Back Malaria Partnership, and UNAIDS and guided national strategies on non-communicable disease control adopted by governments including United Kingdom, Brazil, Australia, and Canada. Donor allocation models at the Bill & Melinda Gates Foundation and program designs by multilateral institutions like the World Bank and Asian Development Bank used GBD outputs to target interventions for cardiovascular disease, maternal and child health, and injury prevention in collaboration with implementers such as Médecins Sans Frontières, Red Cross, and national health services of Kenya and Tanzania.
Criticisms and methodological debates
Scholars and institutions including researchers at Harvard University, Oxford University, Johns Hopkins Bloomberg School of Public Health, and policy analysts at the World Health Organization raised concerns about data sparsity, redistribution algorithms for ill-defined causes, and uncertainties in disability weights, prompting debates in venues such as the Lancet commentary pages and meetings of the Royal Society and the American Public Health Association. Critics from country statistical offices in India, China, and several African ministries noted tensions between modeled estimates and national vital registration, while methodological discussions involving the International Statistical Institute and the Global Health Council focused on transparency, covariate selection, and reproducibility, leading to iterative methodological refinements in subsequent collaborative efforts.