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Updated: Jun 1, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Dementia and Cognitive Impairment in an Urban Multiethnic Indigenous Community from Amazonas
Camila Carlos Bezerra1,2, Noeli das Neves Toledo2, Rebeca Lima Sampaio2
1Department of Medical-Surgical Nursing, School of Nursing, University of São Paulo, São Paulo, Brazil.
Introduction:
Studies about dementia in Indigenous communities are still scarce worldwide, especially in low-middle-income countries, limiting timely intervention in minority groups. Our research aimed to bridge this gap by determining the prevalence of dementia and mild cognitive impairment no dementia (CIND), and the associated factors, in a multiethnic Indigenous community in Manaus, Brazil.
Methods:
A cross-sectional observational study evaluated the cognitive and functional performances of 141 Indigenous individuals (aged 50 and above). A panel of dementia neurologist experts independently analyzed cognitive (Mini-Mental State Exam [MMSE], Brief Cognitive Screening Battery, verbal fluency), functional (Pfeffer questionnaire) performances, and depression symptoms (Geriatric Depression Scale) to classify participants as cognitively unimpaired, CIND, and dementia.
Results:
CIND rate was 11.3% and 12.8% for dementia. None of the participants classified as CIND had a prior diagnosis, and only three out of 18 participants with dementia had a diagnosis. Stratified analysis showed that age (p = 0.017) and lower education (p = 0.047) were associated with higher CIND and dementia. However, only age was significantly associated with dementia in the regression models (OR = 1.078; 95% CI: 1.011-1.149). Sex, living in extreme poverty, hypertension, diabetes, smoking, or excessive alcohol use was not linked to CIND or dementia.
Conclusion:
The Indigenous community of Manaus exhibited higher rates of dementia and CIND than national and global estimates. These findings may set the stage for additional research into the interplay of social, economic, biological, and behavioral factors affecting dementia risk in underrepresented groups such as Indigenous communities.
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