Validity and reliability of subjective methods to assess sedentary behaviour in adults: a systematic review and meta-analysis.

BACKGROUND: Subjective measures of sedentary behaviour (SB) (i.e. questionnaires and diaries/logs) are widely implemented, and can be useful for capturing type and context of SBs. However, little is known about comparative validity and reliability. The aim of this systematic review and meta-analysis was to: 1) identify subjective methods to assess overall, domain- and behaviour-specific SB, and 2) examine the validity and reliability of these methods. METHODS: The databases MEDLINE, EMBASE and SPORTDiscus were searched up to March 2020. Inclusion criteria were: 1) assessment of SB, 2) evaluation of subjective measurement tools, 3) being performed in healthy adults, 4) manuscript written in English, and 5) paper was peer-reviewed. Data of validity and/or reliability measurements was extracted from included studies and a meta-analysis using random effects was performed to assess the pooled correlation coefficients of the validity. RESULTS: The systematic search resulted in 2423 hits. After excluding duplicates and screening on title and abstract, 82 studies were included with 75 self-reported measurement tools. There was wide variability in the measurement properties and quality of the studies. The criterion validity varied between poor-to-excellent (correlation coefficient [R] range - 0.01- 0.90) with logs/diaries (R = 0.63 [95%CI 0.48-0.78]) showing higher criterion validity compared to questionnaires (R = 0.35 [95%CI 0.32-0.39]). Furthermore, correlation coefficients of single- and multiple-item questionnaires were comparable (1-item R = 0.34; 2-to-9-items R = 0.35; ≥10-items R = 0.37). The reliability of SB measures was moderate-to-good, with the quality of these studies being mostly fair-to-good. CONCLUSION: Logs and diaries are recommended to validly and reliably assess self-reported SB. However, due to time and resources constraints, 1-item questionnaires may be preferred to subjectively assess SB in large-scale observations when showing similar validity and reliability compared to longer questionnaires. REGISTRATION NUMBER: CRD42018105994

The sequence and analysis of Trypanosoma brucei chromosome II

We report here the sequence of chromosome II from Trypanosoma brucei, the causative agent of African sleeping sickness. The 1.2-Mb pairs encode about 470 predicted genes organised in 17 directional clusters on either strand, the largest cluster of which has 92 genes lined up over a 284-kb region. An analysis of the GC skew reveals strand compositional asymmetries that coincide with the distribution of protein-coding genes, suggesting these asymmetries may be the result of transcription-coupled repair on coding versus non-coding strand. A 5-cM genetic map of the chromosome reveals recombinational ‘hot’ and ‘cold’ regions, the latter of which is predicted to include the putative centromere. One end of the chromosome consists of a 250-kb region almost exclusively composed of RHS (pseudo)genes that belong to a newly characterised multigene family containing a hot spot of insertion for retroelements. Interspersed with the RHS genes are a few copies of truncated RNA polymerase pseudogenes as well as expression site associated (pseudo)genes (ESAGs) 3 and 4, and 76 bp repeats. These features are reminiscent of a vestigial variant surface glycoprotein (VSG) gene expression site. The other end of the chromosome contains a 30-kb array of VSG genes, the majority of which are pseudogenes, suggesting that this region may be a site for modular de novo construction of VSG gene diversity during transposition/gene conversion events

The genome sequence of Trypanosoma cruzi, etiologic agent of Chagas disease

Fil: El-Sayed, Najib M. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Myler, Peter J. Seattle Biomedical Research Institute; Estados Unidos.Fil: Bartholomeu, Daniella C. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Nilsson, Daniel. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Aggarwal, Gautam. Seattle Biomedical Research Institute; Estados Unidos.Fil: Tran, Anh-Nhi. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Ghedin, Elodie. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Worthey, Elizabeth A. Seattle Biomedical Research Institute; Estados Unidos.Fil: Delcher, Arthur L. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Blandin, Gaëlle. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Westenberger, Scott J. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Caler, Elisabet. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Cerqueira, Gustavo C. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Haas, Carole Branched Brian. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Anupama, Atashi. Seattle Biomedical Research Institute; Estados Unidos.Fil: Arner, Erik. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Åslund, Lena. Uppsala University. Department of Genetics and Pathology; Suecia.Fil: Attipoe, Philip. Seattle Biomedical Research Institute; Estados Unidos.Fil: Bontempi, Esteban. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Parasitología; Argentina.Fil: Bringaud, Frédéric. Université Victor Segalen Bordeaux II. Laboratoire de Génomique Fonctionnelle des Trypanosomatides; Francia.Fil: Burton, Peter. University of Glasgow. Wellcome Centre for Molecular Parasitology; Reino Unido.Fil: Cadag, Eithon. Seattle Biomedical Research Institute; Estados Unidos.Fil: Campbell, David A. University of California. Department of Microbiology; Estados Unidos.Fil: Carrington, Mark. University of Cambridge. Department of Biochemistry; Reino Unido.Fil: Crabtree, Jonathan. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Darban, Hamid. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Silveira, Jose Franco da. Universidade Federal de Sao Paulo. Departamento de Microbiologia; Brasil.Fil: Jong, Pieter de. Children’s Hospital Oakland Research Institute. BACPAC Resources; Estados Unidos.Fil: Edwards, Kimberly. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Englund, Paul T. Johns Hopkins University School of Medicine. Department of Biological Chemistry; Estados Unidos.Fil: Fazelina, Gholam. Seattle Biomedical Research Institute; Estados Unidos.Fil: Feldblyum, Tamara. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Ferella, Marcela. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Frasch, Alberto Carlos. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentina.Fil: Gull, Keith. University of Oxford. Sir William Dunn School of Pathology; Reino Unido.Fil: Horn, David. London School of Hygiene and Tropical Medicine; Reino Unido.Fil: Hou, Lihua. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Huang, Yiting. Seattle Biomedical Research Institute; Estados Unidos.Fil: Kindlund, Ellen. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Klingbeil, Michele. University of Massachusetts. Department of Microbiology; Estados Unidos.Fil: Kluge, Sindy. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Koo, Hean. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Lacerda, Daniela. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Levin, Mariano J. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET-CYTED project). Laboratorio de Biología Molecular de la Enfermedad de Chagas; Argentina.Fil: Lorenzi, Hernan. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET-CYTED project). Laboratorio de Biología Molecular de la Enfermedad de Chagas; Argentina.Fil: Louie, Tin. Seattle Biomedical Research Institute; Estados Unidos.Fil: Machado, Carlos Renato. Universidade Federal de Minas Gerais. Departamento de Bioquímica e Imunologia; Brasil.Fil: McCulloch, Richard. University of Glasgow. Wellcome Centre for Molecular Parasitology; Reino Unido.Fil: McKenna, Alan. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Mizuno, Yumi. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Mottram, Jeremy C. University of Glasgow. Wellcome Centre for Molecular Parasitology; Reino Unido.Fil: Nelson, Siri. Seattle Biomedical Research Institute; Estados Unidos.Fil: Ochaya, Stephen. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Osoegawa, Kazutoyo. Children’s Hospital Oakland Research Institute. BACPAC Resources; Estados Unidos.Fil: Pai, Grace. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Parsons, Marilyn. Seattle Biomedical Research Institute; Estados Unidos.Fil: Pentony, Martin. Seattle Biomedical Research Institute; Estados Unidos.Fil: Pettersson, Ulf. Uppsala University. Department of Genetics and Pathology; Suecia.Fil: Pop, Mihai. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Ramirez, Jose Luis. Universidad Central de Venezuela. Instituto de Biología Experimental; Venezuela.Fil: Rinta, Joel. Seattle Biomedical Research Institute; Estados Unidos.Fil: Robertson, Laura. Seattle Biomedical Research Institute; Estados Unidos.Fil: Salzberg, Steven L. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Sanchez, Daniel O. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentina.Fil: Seyler, Amber. Seattle Biomedical Research Institute; Estados Unidos.Fil: Sharma, Reuben. University of Cambridge. Department of Biochemistry; Reino Unido.Fil: Shetty, Jyoti. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Simpson, Anjana J. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Sisk, Ellen. Seattle Biomedical Research Institute; Estados Unidos.Fil: Tammi, Martti T. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Tarleton, Rick. University of Georgia. Center for Tropical and Emerging Global Diseases; Estados Unidos.Fil: Teixeira, Santuza. Universidade Federal de Minas Gerais. Departamento de Bioquímica e Imunologia; Brasil.Fil: Aken, Susan Van. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Vogt, Christy. Seattle Biomedical Research Institute; Estados Unidos.Fil: Ward, Pauline N. University of Glasgow. Wellcome Centre for Molecular Parasitology; Reino Unido.Fil: Wickstead, Bill. University of Oxford. Sir William Dunn School of Pathology; Reino Unido.Fil: Wortman, Jennifer. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: White, Owen. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Fraser, Claire M. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Stuart, Kenneth D. Seattle Biomedical Research Institute; Estados Unidos.Fil: Andersson, Björn. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Whole-genome sequencing of the protozoan pathogen Trypanosoma cruzi revealed that the diploid genome contains a predicted 22,570 proteins encoded by genes, of which 12,570 represent allelic pairs. Over 50% of the genome consists of repeated sequences, such as retrotransposons and genes for large families of surface molecules, which include trans-sialidases, mucins, gp63s, and a large novel family (>1300 copies) of mucin-associated surface protein (MASP) genes. Analyses of the T. cruzi, T. brucei, and Leishmania major (Tritryp) genomes imply differences from other eukaryotes in DNA repair and initiation of replication and reflect their unusual mitochondrial DNA. Although the Tritryp lack several classes of signaling molecules, their kinomes contain a large and diverse set of protein kinases and phosphatases; their size and diversity imply previously unknown interactions and regulatory processes, which may be targets for intervention

The genome sequence of Trypanosoma cruzi, etiologic agent of Chagas disease

Fil: El-Sayed, Najib M. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Myler, Peter J. Seattle Biomedical Research Institute; Estados Unidos.Fil: Bartholomeu, Daniella C. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Nilsson, Daniel. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Aggarwal, Gautam. Seattle Biomedical Research Institute; Estados Unidos.Fil: Tran, Anh-Nhi. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Ghedin, Elodie. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Worthey, Elizabeth A. Seattle Biomedical Research Institute; Estados Unidos.Fil: Delcher, Arthur L. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Blandin, Gaëlle. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Westenberger, Scott J. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Caler, Elisabet. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Cerqueira, Gustavo C. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Haas, Carole Branched Brian. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Anupama, Atashi. Seattle Biomedical Research Institute; Estados Unidos.Fil: Arner, Erik. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Åslund, Lena. Uppsala University. Department of Genetics and Pathology; Suecia.Fil: Attipoe, Philip. Seattle Biomedical Research Institute; Estados Unidos.Fil: Bontempi, Esteban. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Parasitología; Argentina.Fil: Bringaud, Frédéric. Université Victor Segalen Bordeaux II. Laboratoire de Génomique Fonctionnelle des Trypanosomatides; Francia.Fil: Burton, Peter. University of Glasgow. Wellcome Centre for Molecular Parasitology; Reino Unido.Fil: Cadag, Eithon. Seattle Biomedical Research Institute; Estados Unidos.Fil: Campbell, David A. University of California. Department of Microbiology; Estados Unidos.Fil: Carrington, Mark. University of Cambridge. Department of Biochemistry; Reino Unido.Fil: Crabtree, Jonathan. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Darban, Hamid. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Silveira, Jose Franco da. Universidade Federal de Sao Paulo. Departamento de Microbiologia; Brasil.Fil: Jong, Pieter de. Children’s Hospital Oakland Research Institute. BACPAC Resources; Estados Unidos.Fil: Edwards, Kimberly. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Englund, Paul T. Johns Hopkins University School of Medicine. Department of Biological Chemistry; Estados Unidos.Fil: Fazelina, Gholam. Seattle Biomedical Research Institute; Estados Unidos.Fil: Feldblyum, Tamara. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Ferella, Marcela. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Frasch, Alberto Carlos. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentina.Fil: Gull, Keith. University of Oxford. Sir William Dunn School of Pathology; Reino Unido.Fil: Horn, David. London School of Hygiene and Tropical Medicine; Reino Unido.Fil: Hou, Lihua. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Huang, Yiting. Seattle Biomedical Research Institute; Estados Unidos.Fil: Kindlund, Ellen. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Klingbeil, Michele. University of Massachusetts. Department of Microbiology; Estados Unidos.Fil: Kluge, Sindy. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Koo, Hean. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Lacerda, Daniela. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Levin, Mariano J. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET-CYTED project). Laboratorio de Biología Molecular de la Enfermedad de Chagas; Argentina.Fil: Lorenzi, Hernan. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET-CYTED project). Laboratorio de Biología Molecular de la Enfermedad de Chagas; Argentina.Fil: Louie, Tin. Seattle Biomedical Research Institute; Estados Unidos.Fil: Machado, Carlos Renato. Universidade Federal de Minas Gerais. Departamento de Bioquímica e Imunologia; Brasil.Fil: McCulloch, Richard. University of Glasgow. Wellcome Centre for Molecular Parasitology; Reino Unido.Fil: McKenna, Alan. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Mizuno, Yumi. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Mottram, Jeremy C. University of Glasgow. Wellcome Centre for Molecular Parasitology; Reino Unido.Fil: Nelson, Siri. Seattle Biomedical Research Institute; Estados Unidos.Fil: Ochaya, Stephen. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Osoegawa, Kazutoyo. Children’s Hospital Oakland Research Institute. BACPAC Resources; Estados Unidos.Fil: Pai, Grace. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Parsons, Marilyn. Seattle Biomedical Research Institute; Estados Unidos.Fil: Pentony, Martin. Seattle Biomedical Research Institute; Estados Unidos.Fil: Pettersson, Ulf. Uppsala University. Department of Genetics and Pathology; Suecia.Fil: Pop, Mihai. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Ramirez, Jose Luis. Universidad Central de Venezuela. Instituto de Biología Experimental; Venezuela.Fil: Rinta, Joel. Seattle Biomedical Research Institute; Estados Unidos.Fil: Robertson, Laura. Seattle Biomedical Research Institute; Estados Unidos.Fil: Salzberg, Steven L. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Sanchez, Daniel O. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentina.Fil: Seyler, Amber. Seattle Biomedical Research Institute; Estados Unidos.Fil: Sharma, Reuben. University of Cambridge. Department of Biochemistry; Reino Unido.Fil: Shetty, Jyoti. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Simpson, Anjana J. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Sisk, Ellen. Seattle Biomedical Research Institute; Estados Unidos.Fil: Tammi, Martti T. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Fil: Tarleton, Rick. University of Georgia. Center for Tropical and Emerging Global Diseases; Estados Unidos.Fil: Teixeira, Santuza. Universidade Federal de Minas Gerais. Departamento de Bioquímica e Imunologia; Brasil.Fil: Aken, Susan Van. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Vogt, Christy. Seattle Biomedical Research Institute; Estados Unidos.Fil: Ward, Pauline N. University of Glasgow. Wellcome Centre for Molecular Parasitology; Reino Unido.Fil: Wickstead, Bill. University of Oxford. Sir William Dunn School of Pathology; Reino Unido.Fil: Wortman, Jennifer. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: White, Owen. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Fraser, Claire M. The Institute for Genomic Research. Department of Parasite Genomics; Estados Unidos.Fil: Stuart, Kenneth D. Seattle Biomedical Research Institute; Estados Unidos.Fil: Andersson, Björn. Karolinska Institutet. Center for Genomics and Bioinformatics; Suecia.Whole-genome sequencing of the protozoan pathogen Trypanosoma cruzi revealed that the diploid genome contains a predicted 22,570 proteins encoded by genes, of which 12,570 represent allelic pairs. Over 50% of the genome consists of repeated sequences, such as retrotransposons and genes for large families of surface molecules, which include trans-sialidases, mucins, gp63s, and a large novel family (>1300 copies) of mucin-associated surface protein (MASP) genes. Analyses of the T. cruzi, T. brucei, and Leishmania major (Tritryp) genomes imply differences from other eukaryotes in DNA repair and initiation of replication and reflect their unusual mitochondrial DNA. Although the Tritryp lack several classes of signaling molecules, their kinomes contain a large and diverse set of protein kinases and phosphatases; their size and diversity imply previously unknown interactions and regulatory processes, which may be targets for intervention

The genome of the African trypanosome Trypanosoma brucei

African trypanosomes cause human sleeping sickness and livestock trypanosomiasis in sub-Saharan Africa. We present the sequence and analysis of the 11 megabase-sized chromosomes of <i>Trypanosoma brucei</i>. The 26-megabase genome contains 9068 predicted genes, including ~900 pseudogenes and ~1700 <i>T. brucei</i>–specific genes. Large subtelomeric arrays contain an archive of 806 variant surface glycoprotein (VSG) genes used by the parasite to evade the mammalian immune system. Most VSG genes are pseudogenes, which may be used to generate expressed mosaic genes by ectopic recombination. Comparisons of the cytoskeleton and endocytic trafficking systems with those of humans and other eukaryotic organisms reveal major differences. A comparison of metabolic pathways encoded by the genomes of <i>T. brucei</i>, <i>T. cruzi</i>, and <i>Leishmania major</i> reveals the least overall metabolic capability in <i>T. brucei</i> and the greatest in <i>L. major</i>. Horizontal transfer of genes of bacterial origin has contributed to some of the metabolic differences in these parasites, and a number of novel potential drug targets have been identified

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

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