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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

Authors :
Mclaughlin, S
Dalton, Benjamin
Haidar Ahmad, Dima
Ahmad, Shahid
Ahmadi, Abolfaz
Aljahdali, Hani Moaiteq
Andrei, C.O.
Al Badawi, Ahmad
Bagherieh, Sara
Bhaskar, Sonu
Cho, Wonjun
Chu, Dewei
Díaz Sánchez, Daniel
Feng, Xiaodong
Ben Hassen, M.
Heidari, Majid
Hossain, Md Abid
Hosseinzadeh, Mohammad Reza
Ben-Yehuda, Muli
Hussain, Syed Asad
Kilic, Mukremin
Iqbal Begum, Awais
Jain, Rahul
Joseph, Augustine
Kebede, S
Koyanagi, Ai
Kumar, Haresh
Kundu, Swarup
Larsson, A.
Lee, Wonyoung
Anchalee, Puengnim
Lopes, Gonçalo
Mahmoud, Malak Maher Fawzy
Cusmai, Adriel
Makris, K G
Malik Ara, Ibrar
Al Mamun, Abdullah
Martini, Séverine
Marzo Lafuente, Rafael
Mossialos, E
Mueller, Ute
Panagiotakos, Demosthenes
Patel, J M
Rahmani, Saman
Rashidi Meybodi, Mehdi
Riaz, Maryam
Salemsafi, Sanam
Sahebkar, Amirhossein
Salehi, Maryam
Salomón Arquedas, Juan Carlos
Sanabria, José A.
Schlaich, Mike
Singh, Parvesh
Soleimani, Hesam
Patan, Krzysztof
Tyrovolas, Stefanos
Vaziri, Sam
Verma, Manish
Bozhevolnyi, Sergey I
Moniruzzaman, Shaikh
Zare, Iman
Zoladl, Mohammad
Zou, ZhiXiang
Vos, Tanja
Marateb, Hamid Reza
Universitat Politècnica de Catalunya. Doctorat en Enginyeria de la Construcció
Universitat Politècnica de Catalunya. Doctorat en Teoria i Història de l'Arquitectura
Universitat Politècnica de Catalunya. Doctorat en Automàtica, Robòtica i Visió
Universitat Politècnica de Catalunya. Doctorat en Enginyeria Civil
Universitat Politècnica de Catalunya. Doctorat en Enginyeria del Terreny
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
Universitat Politècnica de Catalunya. ANiComp - Anàlisi Numèrica i Computació Científica
Universitat Politècnica de Catalunya. BIOART - BIOsignal Analysis for Rehabilitation and Therapy
Publication Year :
2023

Abstract

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%.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.od......3484..6da456a174e175fb45bd0d6c8df1e43f