Approximating dementia prevalence in population‐based surveys of aging worldwide: An unsupervised machine learning approach - Sorbonne Université Accéder directement au contenu
Article Dans Une Revue Alzheimer's & Dementia: Translational Research & Clinical Interventions Année : 2020

Approximating dementia prevalence in population‐based surveys of aging worldwide: An unsupervised machine learning approach

Résumé

Abstract Introduction Ability to determine dementia prevalence in low‐ and middle‐income countries (LMIC) remains challenging because of frequent lack of data and large discrepancies in dementia case ascertainment. Methods High likelihood of dementia was determined with hierarchical clustering after principal component analysis applied in 10 population surveys of aging: HRS (USA, 2014), SHARE (Europe and Israel, 2015), MHAS (Mexico, 2015), ELSI (Brazil, 2016), CHARLS (China, 2015), IFLS (Indonesia, 2014–2015), LASI (India, 2016), SAGE‐Ghana (2007), SAGE‐South Africa (2007), SAGE‐Russia (2007–2010). We approximated dementia prevalence using weighting methods. Results Estimated numbers of dementia cases were: China, 40.2 million; India, 18.0 million; Russia, 5.2 million; Europe and Israel, 5.0 million; United States, 4.4 million; Brazil, 2.2 million; Mexico, 1.6 million; Indonesia, 1.3 million; South Africa, 1.0 million; Ghana, 319,000. Discussion Our estimations were similar to prior ones in high‐income countries but much higher in LMIC. Extrapolating these results globally, we suggest that almost 130 million people worldwide were living with dementia in 2015.
Fichier principal
Vignette du fichier
A D Transl Res Clin Interv - 2020 - Cleret de Langavant - Approximating dementia prevalence in population‐based surveys.pdf (729.72 Ko) Télécharger le fichier
Origine : Publication financée par une institution
Licence : CC BY NC ND - Paternité - Pas d'utilisation commerciale - Pas de modification

Dates et versions

hal-04521391 , version 1 (26-03-2024)

Licence

Paternité - Pas d'utilisation commerciale - Pas de modification

Identifiants

Citer

Laurent Cleret de Langavant, Eléonore Bayen, Anne‐catherine Bachoud-Lévi, Kristine Yaffe. Approximating dementia prevalence in population‐based surveys of aging worldwide: An unsupervised machine learning approach. Alzheimer's & Dementia: Translational Research & Clinical Interventions, 2020, 6 (1), pp.e12074. ⟨10.1002/trc2.12074⟩. ⟨hal-04521391⟩
1 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More