Evidence map›Paper›PMID 42063623›Full record

ArticleFrontiers in aging neuroscience2026

Construction of a classification model for dementia among Brazilian adults aged 50 and over.

Felipe da Silva Menezes, Maria Clara Falcão Guerra Barretto, Elliot Quinten Crispiniano Garcia, Tiago Alessandro Espinola Ferreira, Joao Guilherme Bezerra Alves

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Felipe da Silva MenezesInstituto de Medicina Integral Professor Fernando Figueira (IMIP), Recife, Brazil.
Maria Clara Falcão Guerra BarrettoFuturo Tech, Recife, Brazil.
Elliot Quinten Crispiniano GarciaFuturo Tech, Recife, Brazil.
Tiago Alessandro Espinola FerreiraUniversidade Federal Rural de Pernambuco (UFRPE), Recife, Brazil.
Joao Guilherme Bezerra AlvesInstituto de Medicina Integral Professor Fernando Figueira (IMIP), Recife, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Dementia is a multifactorial and debilitating condition marked by cognitive decline and behavioral changes that compromise independence and daily activities. This condition is a growing challenge in Brazil, and early identification of associated factors can guide preventive strategies and health policies. Objectives: To build a dementia classification model for middle-aged and older adults Brazilians combining variable selection and multivariable analysis, using low-cost variables, including variables potentially modifiable and non-modifiable sociodemographic variables. Methods: Observational study employed a cross-sectional design and a classification modeling approach to estimate probable dementia and analyze the odds of dementia, using data from the Brazilian Longitudinal Study of Aging, involving 9,412 participants. Dementia was determined based on neuropsychological assessment and informant-based cognitive function. Analyses were performed with Random Forest (RF) and multivariable Logistic Regression (LR). Results: The prevalence of dementia was 9.6%. The highest odds of dementia were observed in illiterate individuals (Odds Ratio (OR) = 7.42; 95% Confidence Interval (CI): 4.04-13.62), individuals aged 90 years or older (OR = 11.00; 95% CI: 5.05-23.95), low weight (OR = 2.11; 95% CI: 1.12-3.97), low handgrip strength (OR = 2.50; 95% CI: 1.09-5.76), self-reported black skin color (OR = 1.47; 95% CI: 1.07-2.00), physical inactivity (OR = 1.61; 95% CI: 1.25-2.08), self-reported hearing loss (OR = 1.65; 95% CI: 1.16-2.37), and presence of depressive symptoms (OR = 1.72; 95% CI: 1.36-2.16). In contrast, higher education (OR = 0.44; 95% CI: 0.21-0.94), greater life satisfaction (OR = 0.72; 95% CI: 0.52-0.99), and being employed (OR = 0.78; 95% CI: 0.61-1.00) were protective factors. The RF model outperformed LR, achieving an area under the ROC curve of 0.776 (95% CI: 0.740-0.811), with sensitivity of 0.708, specificity of 0.702, precision of 0.201, Precision-Recall Area Under the Curve (PR-AUC) of 0.261 (95% CI: 0.217-0.319), F1-score of 0.311, G-means of 0.705, and accuracy of 0.703. Conclusion: The findings reinforce the multidimensional nature of dementia and the importance of accessible factors for supporting screening/triage and prioritization in primary care. Strengthening public policies focused on promoting brain health can contribute significantly to the efficient allocation of resources in primary care and dementia prevention in Brazil.

Indexed as

Brazilcognitive dysfunctionhealth of the elderlyrandom forestrisk factors

Identifiers

PMID42063623
PMCPMC13126550

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