Academic Journal
Construction of a classification model for dementia among Brazilian adults aged 50 and over.
| Τίτλος: | Construction of a classification model for dementia among Brazilian adults aged 50 and over. |
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| Συγγραφείς: | Menezes, Felipe da Silva, Barretto, Maria Clara Falcão Guerra, Garcia, Elliot Quinten Crispiniano, Ferreira, Tiago Alessandro Espinola, Alves, Joao Guilherme Bezerra |
| Πηγή: | Frontiers in Aging Neuroscience; 2026, p1-22, 22p |
| Θεματικοί όροι: | Cross-sectional method, Random forest algorithms, Self-evaluation, Prediction models, Center for Epidemiologic Studies Depression Scale, Satisfaction, Receiver operating characteristic curves, Scientific observation, Questionnaires, Multiple regression analysis, Logistic regression analysis, Descriptive statistics, Mann Whitney U Test, Chi-squared test, Multivariate analysis, Brazilians, Longitudinal method, Odds ratio, Neuropsychological tests, Dementia, Sociodemographic factors, Data analysis software, Confidence intervals, Literacy, Hearing disorders, Regression analysis, Algorithms, Grip strength, Physical activity, Mental depression, Educational attainment, Employment |
| Γεωγραφικοί όροι: | Brazil |
| Περίληψη: | 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Frontiers in Aging Neuroscience is the property of Frontiers Media S.A. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
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| Header | DbId: edb DbLabel: Complementary Index An: 193361837 RelevancyScore: 1061 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 1060.76049804688 |
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| Items | – Name: Title Label: Title Group: Ti Data: Construction of a classification model for dementia among Brazilian adults aged 50 and over. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Menezes%2C+Felipe+da+Silva%22">Menezes, Felipe da Silva</searchLink><br /><searchLink fieldCode="AR" term="%22Barretto%2C+Maria+Clara+Falcão+Guerra%22">Barretto, Maria Clara Falcão Guerra</searchLink><br /><searchLink fieldCode="AR" term="%22Garcia%2C+Elliot+Quinten+Crispiniano%22">Garcia, Elliot Quinten Crispiniano</searchLink><br /><searchLink fieldCode="AR" term="%22Ferreira%2C+Tiago+Alessandro+Espinola%22">Ferreira, Tiago Alessandro Espinola</searchLink><br /><searchLink fieldCode="AR" term="%22Alves%2C+Joao+Guilherme+Bezerra%22">Alves, Joao Guilherme Bezerra</searchLink> – Name: TitleSource Label: Source Group: Src Data: Frontiers in Aging Neuroscience; 2026, p1-22, 22p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Cross-sectional+method%22">Cross-sectional method</searchLink><br /><searchLink fieldCode="DE" term="%22Random+forest+algorithms%22">Random forest algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Self-evaluation%22">Self-evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink><br /><searchLink fieldCode="DE" term="%22Center+for+Epidemiologic+Studies+Depression+Scale%22">Center for Epidemiologic Studies Depression Scale</searchLink><br /><searchLink fieldCode="DE" term="%22Satisfaction%22">Satisfaction</searchLink><br /><searchLink fieldCode="DE" term="%22Receiver+operating+characteristic+curves%22">Receiver operating characteristic curves</searchLink><br /><searchLink fieldCode="DE" term="%22Scientific+observation%22">Scientific observation</searchLink><br /><searchLink fieldCode="DE" term="%22Questionnaires%22">Questionnaires</searchLink><br /><searchLink fieldCode="DE" term="%22Multiple+regression+analysis%22">Multiple regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Logistic+regression+analysis%22">Logistic regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Mann+Whitney+U+Test%22">Mann Whitney U Test</searchLink><br /><searchLink fieldCode="DE" term="%22Chi-squared+test%22">Chi-squared test</searchLink><br /><searchLink fieldCode="DE" term="%22Multivariate+analysis%22">Multivariate analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Brazilians%22">Brazilians</searchLink><br /><searchLink fieldCode="DE" term="%22Longitudinal+method%22">Longitudinal method</searchLink><br /><searchLink fieldCode="DE" term="%22Odds+ratio%22">Odds ratio</searchLink><br /><searchLink fieldCode="DE" term="%22Neuropsychological+tests%22">Neuropsychological tests</searchLink><br /><searchLink fieldCode="DE" term="%22Dementia%22">Dementia</searchLink><br /><searchLink fieldCode="DE" term="%22Sociodemographic+factors%22">Sociodemographic factors</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink><br /><searchLink fieldCode="DE" term="%22Confidence+intervals%22">Confidence intervals</searchLink><br /><searchLink fieldCode="DE" term="%22Literacy%22">Literacy</searchLink><br /><searchLink fieldCode="DE" term="%22Hearing+disorders%22">Hearing disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Grip+strength%22">Grip strength</searchLink><br /><searchLink fieldCode="DE" term="%22Physical+activity%22">Physical activity</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+depression%22">Mental depression</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+attainment%22">Educational attainment</searchLink><br /><searchLink fieldCode="DE" term="%22Employment%22">Employment</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Brazil%22">Brazil</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Frontiers in Aging Neuroscience is the property of Frontiers Media S.A. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3389/fnagi.2026.1789012 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 1 Subjects: – SubjectFull: Brazil Type: general – SubjectFull: Cross-sectional method Type: general – SubjectFull: Random forest algorithms Type: general – SubjectFull: Self-evaluation Type: general – SubjectFull: Prediction models Type: general – SubjectFull: Center for Epidemiologic Studies Depression Scale Type: general – SubjectFull: Satisfaction Type: general – SubjectFull: Receiver operating characteristic curves Type: general – SubjectFull: Scientific observation Type: general – SubjectFull: Questionnaires Type: general – SubjectFull: Multiple regression analysis Type: general – SubjectFull: Logistic regression analysis Type: general – SubjectFull: Descriptive statistics Type: general – SubjectFull: Mann Whitney U Test Type: general – SubjectFull: Chi-squared test Type: general – SubjectFull: Multivariate analysis Type: general – SubjectFull: Brazilians Type: general – SubjectFull: Longitudinal method Type: general – SubjectFull: Odds ratio Type: general – SubjectFull: Neuropsychological tests Type: general – SubjectFull: Dementia Type: general – SubjectFull: Sociodemographic factors Type: general – SubjectFull: Data analysis software Type: general – SubjectFull: Confidence intervals Type: general – SubjectFull: Literacy Type: general – SubjectFull: Hearing disorders Type: general – SubjectFull: Regression analysis Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Grip strength Type: general – SubjectFull: Physical activity Type: general – SubjectFull: Mental depression Type: general – SubjectFull: Educational attainment Type: general – SubjectFull: Employment Type: general Titles: – TitleFull: Construction of a classification model for dementia among Brazilian adults aged 50 and over. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Menezes, Felipe da Silva – PersonEntity: Name: NameFull: Barretto, Maria Clara Falcão Guerra – PersonEntity: Name: NameFull: Garcia, Elliot Quinten Crispiniano – PersonEntity: Name: NameFull: Ferreira, Tiago Alessandro Espinola – PersonEntity: Name: NameFull: Alves, Joao Guilherme Bezerra IsPartOfRelationships: – BibEntity: Dates: – D: 29 M: 04 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 16634365 Titles: – TitleFull: Frontiers in Aging Neuroscience Type: main |
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