@misc{10818/62354,
year = {2023},
url = {http://hdl.handle.net/10818/62354},
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%. 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. © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license},
abstract = {Antecedentes: La diabetes es una de las principales causas de muerte y discapacidad en todo el mundo y afecta a personas independientemente del país, grupo de edad o sexo. Utilizando el marco probatorio y analítico más reciente del Estudio de carga global de enfermedades, lesiones y factores de riesgo (GBD), generamos estimaciones específicas de ubicación, edad y sexo de la prevalencia y carga de la diabetes de 1990 a 2021. la proporción de diabetes tipo 1 y tipo 2 en 2021, la proporción de la carga de diabetes tipo 2 atribuible a factores de riesgo seleccionados y las proyecciones de la prevalencia de la diabetes hasta 2050. Métodos: Se calcularon estimaciones de la prevalencia y la carga de la diabetes en 204 países y territorios. en 25 grupos de edad, para hombres y mujeres por separado y combinados; estas estimaciones comprendieron los años de vida saludable perdidos, medidos en años de vida ajustados en función de la discapacidad (AVAD; definidos como la suma de los años de vida perdidos [AVP] y los años vividos con discapacidad [AVP]). Utilizamos el enfoque del modelo Conjunto de Causas de Muerte (CODEm) para estimar las muertes debidas a diabetes, incorporando 25 666 años-lugar de datos del registro civil y de informes de autopsias verbales en total separado (incluyendo diabetes tipo 1 y tipo 2) y tipo- modelos específicos. Otras formas de diabetes, incluida la gestacional y la monogénica, no se modelaron explícitamente. La prevalencia total y de diabetes tipo 1 se estimó mediante el uso de una herramienta de modelado de metarregresión bayesiana, DisMod-MR 2.1, para analizar 1527 años de ubicación de datos de la literatura científica, microdatos de encuestas y reclamaciones de seguros; Las estimaciones de diabetes tipo 2 se calcularon restando la diabetes tipo 1 de las estimaciones totales.},
publisher = {The Lancet},
title = {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},
title = {Carga mundial, regional y nacional de diabetes de 1990 a 2021, con proyecciones de prevalencia hasta 2050: un análisis sistemático para el Estudio de carga mundial de enfermedades 2021},
doi = {10.1016/S0140-6736(23)01301-6},
author = {Stafford, Lauryn K and Cruz, Jessica A and Hagins, Hailey and Bah, Sulaiman and Aali, Amirali and Barrow, Amadou and Boloor, Archith and Castañeda-Orjuela, Carlos A and Cheema, Huzaifa Ahmad},
}