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Updated: Jun 13, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
[Risk Factors for Cognitive Decline Among Elderly Chilean Adults: Insights from a National Study]
Leslie Felmer1, Gabriela Nazar2
1Departamento de Psicología, Universidad de Concepción, Concepción, Chile.
Background:
With a growing elderly population in Chile, the prevalence of neurocognitive disorders has increased, including dementia and its precursor, mild cognitive impairment. Identifying risk factors associated with cognitive impairment is critical in prevention.
Aim:
To define cognitive functioning and performance and to identify sociodemographic, psychosocial, and health risk factors for mild cognitive impairment in Chilean adults aged 60 years and older.
Methods:
We used a quantitative approach with a cross-sectional design and a descriptive and correlational scope. The study included 1,271 adults over 60 years of age, participants from a representative sample of the 2019 Study of Health and Cognition in Older Adults who were evaluated with the Harmonized Cognitive Assessment Protocol (HCAP). We used descriptive statistics and binary logistic regression for data analysis.
Results:
The prevalence of MCI was 9.13%. We found a significant association between MCI and age (OR: 1.08 [95% IC: 1.04; 1.11], p < 0.0001), depression (OR: 1.20 [95% IC: 1.12; 1.29], p < 0.0001), visual impairment (OR: 7.5 [95% IC: 3.8; 14.9], p < 0.0001), not doing housework (OR: 0.22 [95% IC: 0.17; 0.70], p < 0.0001) and not going grocery shopping (OR: 2.55 [95% IC:1.07; 6.04], p < 0.0001).
Conclusion:
Age, depression, visual impairment, and low activity are risk factors for cognitive impairment. Early identification of these conditions will allow the prevention of cognitive impairment.
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