Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021


Kanyin Liane Ong, Institute for Health Metrics and Evaluation
Lauryn K. Stafford, Institute for Health Metrics and Evaluation
Susan A. McLaughlin, Institute for Health Metrics and Evaluation
Edward J. Boyko, School of Medicine
Stein Emil Vollset, Institute for Health Metrics and Evaluation
Amanda E. Smith, Institute for Health Metrics and Evaluation
Bronte E. Dalton, Institute for Health Metrics and Evaluation
Joe Duprey, Institute for Health Metrics and Evaluation
Jessica A. Cruz, Institute for Health Metrics and Evaluation
Hailey Hagins, Institute for Health Metrics and Evaluation
Paulina A. Lindstedt, Institute for Health Metrics and Evaluation
Amirali Aali, Faculty of Medicine
Yohannes Habtegiorgis Abate, Aleta Wondo Hospital
Melsew Dagne Abate, Woldia University
Mohammadreza Abbasian, Orthopaedic Surgery
Zeinab Abbasi-Kangevari, Social Determinants of Health Research Center
Mohsen Abbasi-Kangevari, Non-communicable Diseases Research Center
Samar Abd ElHafeez, Epidemiology Department
Rami Abd-Rabu, Evidence-Based Practice Center
Deldar Morad Abdulah, University of Duhok
Abu Yousuf Md Abdullah, Faculty of Environment
Vida Abedi, Penn State College of Medicine
Hassan Abidi, Laboratory Technology Sciences Department
Richard Gyan Aboagye, University of Health and Allied Sciences, Ghana
Hassan Abolhassani, Research Center for Immunodeficiencies
Eman Abu-Gharbieh, Clinical Sciences Department
Ahmed Abu-Zaid, University of Tennessee Health Science Center
Tigist Demssew Adane
Denberu Eshetie Adane

Publication Name

The Lancet


Background: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. Findings: In 2021, there were 529 million (95% uncertainty interval [UI] 500–564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8–6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7–9·9]) and, at the regional level, in Oceania (12·3% [11·5–13·0]). Nationally, Qatar had the world's highest age-specific prevalence of diabetes, at 76·1% (73·1–79·5) in individuals aged 75–79 years. Total diabetes prevalence—especially among older adults—primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1–96·8) of diabetes cases and 95·4% (94·9–95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5–71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5–30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22–1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1–17·6) in north Africa and the Middle East and 11·3% (10·8–11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%. Interpretation: Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers. Funding: Bill & Melinda Gates Foundation.

Open Access Status

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Funding Number

2020 BP 00261

Funding Sponsor

Department of Biotechnology, Ministry of Science and Technology, India



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