Статья

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 OngInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USALauryn K StaffordInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USASusan A. McLaughlinInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAEdward J. BoykoStein Emil VollsetInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAAmanda SmithInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USABronte DaltonInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAJ DupreyInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAJessica A CruzInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAHailey HaginsInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAPaulina A LindstedtInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAAmirali AaliInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAYohannes AbateInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAMelsew Dagne AbateInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAMohammadreza AbbasianInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAZeinab Abbasi-KangevariInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAMohsen Abbasi‐KangevariInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USASamar Abd ElHafeezInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USARami Abd‐RabuInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USADeldar Morad AbdulahInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAAbu Yousuf Md AbdullahInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAVida AbediInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAHassan AbidiInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USARichard Gyan AboagyeInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAHassan AbolhassaniInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAEman Abu‐GharbiehInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAAhmed Abu‐ZaidInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USATigist Demssew AdaneInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USADenberu Eshetie AdaneInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAIsaac Yeboah AddoInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAOyelola A. AdegboyeInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAVictor AdekanmbiInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAVictor Abiola AdepojuInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAQorinah Estiningtyas Sakilah AdnaniInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USARotimi Felix AfolabiInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAGina AgarwalInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAZahra Babaei AghdamInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAMarcela Agudelo‐BoteroInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAConstanza Elizabeth Aguilera ArriagadaWilliams Agyemang‐DuahInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USABright Opoku AhinkorahInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USADanish AhmadInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USARizwan AhmadInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USASajjad AhmadInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAAqeel AhmadInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAAli AhmadiInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAKeivan AhmadiInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAAyman AhmedInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAAli AhmedInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USALuai A. AhmedInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USASyed Anees AhmedInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAMarjan AjamiInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USARufus AkinyemiInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAHanadi Al HamadInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USASyed Mahfuz Al HasanTareq Mohammed Ali AL-AhdalInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USATariq A. AlalwanInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAZiyad Al‐AlyInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAMohammad T AlBatainehInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAJacqueline Elizabeth Alcalde‐RabanalInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USASharifullah AlemiInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAHassam AliInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USATahereh AliniaInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USASyed Mohamed AljunidInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USASami AlmustanyirInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USARajaa Al‐RaddadiInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USANelson Alvis‐GuzmánInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAFirehiwot AmareInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAEdward Kwabena AmeyawInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USASohrab AmiriInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAGaniyu Adeniyi AmusaInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USACătălina Liliana AndreiInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USARanjit Mohan AnjanaInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAAdnan AnsarInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAGolnoosh AnsariInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAAlireza Ansari‐MoghaddamInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAAnayochukwu Edward AnyasodorInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAJalal ArablooInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAAleksandr Y. AravkinInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USADemelash AredaInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAHidayat ArifinInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAMesay ArkewInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USABenedetta ArmocidaInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAJohan ÄrnlövInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAAnton A ArtamonovInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAJudie ArulappanInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USARaphael Taiwo ArulebaInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAAshokan ArumugamInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAZahra AryanInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAMulu TirunehInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAMohammad Asghari JafarabadiInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAElaheh AskariInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USADaniel AsmelashInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAThomas Astell‐BurtInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAMohammad AtharInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USASeyyed Shamsadin AthariInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAMaha AtoutInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USALeticia Ávila‐BurgosInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USAAhmed AwaisuInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USASina AzadnajafabadInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USA

2023en

ABI

Аннотация

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.

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Идентификаторы

DOI: 10.1016/s0140-6736(23)01301-6

Цитирования и источники

Цитирований: 4Использованных источников: 0

Показатели — AkademScholar