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Systematic Review Estimating the Burden of Dementia in the Latin America and Caribbean Region: A Bayesian Approach
Background: The global burden of dementia has increasingly shifted to low- and middle-income regions that lack essential data for monitoring epidemiological progression, and policy and planning support. Drawing upon data that have emerged since the last known estimates published in 2015, this study...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356078/ https://www.ncbi.nlm.nih.gov/pubmed/34393965 http://dx.doi.org/10.3389/fneur.2021.628520 |
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author | Xiang, Yawen Vilmenay, Kimberly Poon, Adrienne N. Ayanian, Shant Aitken, Christopher F. Chan, Kit Yee |
author_facet | Xiang, Yawen Vilmenay, Kimberly Poon, Adrienne N. Ayanian, Shant Aitken, Christopher F. Chan, Kit Yee |
author_sort | Xiang, Yawen |
collection | PubMed |
description | Background: The global burden of dementia has increasingly shifted to low- and middle-income regions that lack essential data for monitoring epidemiological progression, and policy and planning support. Drawing upon data that have emerged since the last known estimates published in 2015, this study aims to update dementia estimates in the Latin America and Caribbean (LAC) region for the years 2020, 2030, and 2050 through the application of a recently validated Bayesian approach for disease estimates useful when data sources are scarce. Methods: A comprehensive parallel systematic review of PubMed, EMBASE, PsycINFO, Global Health, and LILACS was conducted to identify prospective population-based epidemiological studies on dementia published in English from 2013 to 2018 in LAC. English and non-English data cited by a recent review on dementia estimates in LAC were also examined for additional data. A Bayesian normal-normal hierarchical model (NNHM) was developed to estimate age-specific and age-adjusted dementia prevalence in people aged 60+. Using age-specific population projections from the UN, the total number of people affected by dementia for the years 2020, 2030, and 2050 were estimated. Results: 1,414 studies were identified, of which only 7 met the inclusion criteria. The studies had 7,684 participants and 1,191 dementia cases. The age-standardized prevalence of all forms of dementia in LAC was 8% (95% CI: 5–11.5%) in people aged 60+. The estimated prevalence varied with age, increasing from 2.5% (95% CI: 0.08–4.0%) in the 60-69 age group, to 9.4% (95% CI: 5.4–13.2%) in the 70–79 age group and 28.9% (95% CI: 20.3–37.2%) in the ≥80 age group. The number of people age 60 and older living with dementia in LAC in 2020 was estimated at 6.86 (95% CI: 4.3–9.8) million, 9.94 (95% CI: 6.16–14.15) million in 2030, and 19.33 (95% CI: 12.3–13.6) million in 2050. Conclusion: We project an upward disease trajectory for dementia in LAC countries. The projection is likely an underestimation of the true dementia burden given the underrepresentation of rural and socio-economically deprived populations. More research is urgently needed to improve the accuracy of disease estimates, guide clinicians to improve evaluations for earlier recognition of dementia, and support the development of effective policies for improving dementia prevention, diagnosis and clinical management in LAC's diverse and aging communities. |
format | Online Article Text |
id | pubmed-8356078 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83560782021-08-12 Systematic Review Estimating the Burden of Dementia in the Latin America and Caribbean Region: A Bayesian Approach Xiang, Yawen Vilmenay, Kimberly Poon, Adrienne N. Ayanian, Shant Aitken, Christopher F. Chan, Kit Yee Front Neurol Neurology Background: The global burden of dementia has increasingly shifted to low- and middle-income regions that lack essential data for monitoring epidemiological progression, and policy and planning support. Drawing upon data that have emerged since the last known estimates published in 2015, this study aims to update dementia estimates in the Latin America and Caribbean (LAC) region for the years 2020, 2030, and 2050 through the application of a recently validated Bayesian approach for disease estimates useful when data sources are scarce. Methods: A comprehensive parallel systematic review of PubMed, EMBASE, PsycINFO, Global Health, and LILACS was conducted to identify prospective population-based epidemiological studies on dementia published in English from 2013 to 2018 in LAC. English and non-English data cited by a recent review on dementia estimates in LAC were also examined for additional data. A Bayesian normal-normal hierarchical model (NNHM) was developed to estimate age-specific and age-adjusted dementia prevalence in people aged 60+. Using age-specific population projections from the UN, the total number of people affected by dementia for the years 2020, 2030, and 2050 were estimated. Results: 1,414 studies were identified, of which only 7 met the inclusion criteria. The studies had 7,684 participants and 1,191 dementia cases. The age-standardized prevalence of all forms of dementia in LAC was 8% (95% CI: 5–11.5%) in people aged 60+. The estimated prevalence varied with age, increasing from 2.5% (95% CI: 0.08–4.0%) in the 60-69 age group, to 9.4% (95% CI: 5.4–13.2%) in the 70–79 age group and 28.9% (95% CI: 20.3–37.2%) in the ≥80 age group. The number of people age 60 and older living with dementia in LAC in 2020 was estimated at 6.86 (95% CI: 4.3–9.8) million, 9.94 (95% CI: 6.16–14.15) million in 2030, and 19.33 (95% CI: 12.3–13.6) million in 2050. Conclusion: We project an upward disease trajectory for dementia in LAC countries. The projection is likely an underestimation of the true dementia burden given the underrepresentation of rural and socio-economically deprived populations. More research is urgently needed to improve the accuracy of disease estimates, guide clinicians to improve evaluations for earlier recognition of dementia, and support the development of effective policies for improving dementia prevention, diagnosis and clinical management in LAC's diverse and aging communities. Frontiers Media S.A. 2021-07-28 /pmc/articles/PMC8356078/ /pubmed/34393965 http://dx.doi.org/10.3389/fneur.2021.628520 Text en Copyright © 2021 Xiang, Vilmenay, Poon, Ayanian, Aitken and Chan. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neurology Xiang, Yawen Vilmenay, Kimberly Poon, Adrienne N. Ayanian, Shant Aitken, Christopher F. Chan, Kit Yee Systematic Review Estimating the Burden of Dementia in the Latin America and Caribbean Region: A Bayesian Approach |
title | Systematic Review Estimating the Burden of Dementia in the Latin America and Caribbean Region: A Bayesian Approach |
title_full | Systematic Review Estimating the Burden of Dementia in the Latin America and Caribbean Region: A Bayesian Approach |
title_fullStr | Systematic Review Estimating the Burden of Dementia in the Latin America and Caribbean Region: A Bayesian Approach |
title_full_unstemmed | Systematic Review Estimating the Burden of Dementia in the Latin America and Caribbean Region: A Bayesian Approach |
title_short | Systematic Review Estimating the Burden of Dementia in the Latin America and Caribbean Region: A Bayesian Approach |
title_sort | systematic review estimating the burden of dementia in the latin america and caribbean region: a bayesian approach |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356078/ https://www.ncbi.nlm.nih.gov/pubmed/34393965 http://dx.doi.org/10.3389/fneur.2021.628520 |
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