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dc.contributor.authorNichols, Emma
dc.contributor.authorSteinmetz, Jaimie D
dc.contributor.authorVollset, Stein Emil
dc.contributor.authorFukutaki, Kai
dc.contributor.authorChalek, Julian
dc.contributor.authorKisa, Adnan
dc.contributor.authorMurray, Christopher J L
dc.contributor.authorMokdad, Ali H.
dc.contributor.authorHay, Simon I.
dc.contributor.authorKisa, Sezer
dc.contributor.authorVos, Theo
dc.contributor.authorZastrozhin, Mikhail Sergeevich
dc.contributor.authorForecasting Collaborators, GBD 2019 Dementia
dc.date.accessioned2022-07-07T09:05:32Z
dc.date.available2022-07-07T09:05:32Z
dc.date.created2022-01-07T12:56:03Z
dc.date.issued2022
dc.identifier.citationThe Lancet Public Health. 2022, 7(2), 105-125.en_US
dc.identifier.issn2468-2667
dc.identifier.urihttps://hdl.handle.net/11250/3003428
dc.description.abstractBackground Given the projected trends in population ageing and population growth, the number of people with dementia is expected to increase. In addition, strong evidence has emerged supporting the importance of potentially modifiable risk factors for dementia. Characterising the distribution and magnitude of anticipated growth is crucial for public health planning and resource prioritisation. This study aimed to improve on previous forecasts of dementia prevalence by producing country-level estimates and incorporating information on selected risk factors. Methods We forecasted the prevalence of dementia attributable to the three dementia risk factors included in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 (high body-mass index, high fasting plasma glucose, and smoking) from 2019 to 2050, using relative risks and forecasted risk factor prevalence to predict GBD risk-attributable prevalence in 2050 globally and by world region and country. Using linear regression models with education included as an additional predictor, we then forecasted the prevalence of dementia not attributable to GBD risks. To assess the relative contribution of future trends in GBD risk factors, education, population growth, and population ageing, we did a decomposition analysis. Findings We estimated that the number of people with dementia would increase from 57·4 (95% uncertainty interval 50·4–65·1) million cases globally in 2019 to 152·8 (130·8–175·9) million cases in 2050. Despite large increases in the projected number of people living with dementia, age-standardised both-sex prevalence remained stable between 2019 and 2050 (global percentage change of 0·1% [–7·5 to 10·8]). We estimated that there were more women with dementia than men with dementia globally in 2019 (female-to-male ratio of 1·69 [1·64–1·73]), and we expect this pattern to continue to 2050 (female-to-male ratio of 1·67 [1·52–1·85]). There was geographical heterogeneity in the projected increases across countries and regions, with the smallest percentage changes in the number of projected dementia cases in high-income Asia Pacific (53% [41–67]) and western Europe (74% [58–90]), and the largest in north Africa and the Middle East (367% [329–403]) and eastern sub-Saharan Africa (357% [323–395]). Projected increases in cases could largely be attributed to population growth and population ageing, although their relative importance varied by world region, with population growth contributing most to the increases in sub-Saharan Africa and population ageing contributing most to the increases in east Asia. Interpretation Growth in the number of individuals living with dementia underscores the need for public health planning efforts and policy to address the needs of this group. Country-level estimates can be used to inform national planning efforts and decisions. Multifaceted approaches, including scaling up interventions to address modifiable risk factors and investing in research on biological mechanisms, will be key in addressing the expected increases in the number of individuals affected by dementia.en_US
dc.description.sponsorshipF Carvalho and E F Fernandes acknowledge support from the University of Porto (UID/MULTI/04378/2019 and UID/QUI/50006/2019 with funding from FCT/MCTES through national funds). L F S Castro-de-Araujo acknowledges support from the Medical Research Council (London; grant number MC_PC_MR/T03355X/1). V M Costa acknowledges her grant (SFRH/BHD/110001/2015), received by Portuguese national funds through Fundação para a Ciência e Tecnologia (FCT), IP, under the Norma Transitória (DL57/2016/CP1334/CT0006). A Douiri acknowledges support from the NIHR Applied Research Collaboration (ARC) South London at King's College Hospital NHS Foundation Trust and the Royal College of Physicians, as well as the support from the NIHR Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust and King's College London. N Ghith acknowledges her salary as a postdoc is covered by a grant to her research group provided by Novo Nordisk Foundation. V K Gupta and V B Gupta acknowledge funding support from National Health and Medical Research Council (NHMRC), Australia. S Haque acknowledges support from Jazan University, Saudi Arabia, for providing access to the Saudi Digital Library for this study. C Herteliu is partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation (CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084). Y J Kim was supported by the Research Management Centre, Xiamen University, Malaysia (No. XMUMRF/2020-C6/ITCM/0004). M Kivimäki was supported by the MRC (S011676) and the Wellcome Trust (221854/Z/20/Z). M Kumar acknowledges support from Fogarty International Center (K43 TW010716-04). S Lorkowski acknowledges institutional support from the Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig (Germany; German Federal Ministry of Education and Research, grant agreement number 01EA1808A). S Mondello was supported by the Italian Ministry of Health (GR-2013-02354960). A Raggi acknowledges support from a grant from the Italian Ministry of Health (Ricerca Corrente, Fondazione Istituto Neurologico C. Besta, Linea – Outcome Research: dagli Indicatori alle Raccomandazioni Cliniche). D A S Silva acknowledges support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brasil (CAPES; Finance Code 001 / CAPES-PRINT). J P Silva acknowledges support from the Applied Molecular Biosciences Unit (UCIBIO; grant number UIDB/04378/2020), supported through Portuguese national funds via FCT/MCTES.en_US
dc.language.isoengen_US
dc.relation.urihttps://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(21)00249-8/fulltext#supplementaryMaterial
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleEstimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019en_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber105-125en_US
dc.source.volume7en_US
dc.source.journalThe Lancet Public Healthen_US
dc.source.issue2en_US
dc.identifier.doi10.1016/S2468-2667(21)00249-8
dc.identifier.cristin1976549
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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