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Updated: Jan 18, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Cardiometabolic disorders and mild cognitive impairment in White and Black Americans
Voyko Kavcic1, Mohammad Turaani2, Subhamoy Pal3,4
1Institute of Gerontology, Wayne State University, Detroit, Michigan, USA.
Introduction:
Mild cognitive impairment (MCI) represents a transitional stage between normal aging and dementia. We investigate associations among cardiovascular and metabolic disorders (hypertension, diabetes mellitus, and hyperlipidemia) and diagnosis (normal; amnestic [aMCI]; and non-amnestic [naMCI]).
Methods:
Multinomial logistic regressions of participant data (N = 8737; age = 70.9 ± 7.5 years) from the National Alzheimer's Coordinating Center Uniform Dataset Version 3 protocol cohort were used.
Results:
Controlling for demographic/health variables, individuals with aMCI, though not naMCI, showed a higher likelihood of hypertension, diabetes, and hyperlipidemia compared to cognitively normal counterparts, though no differences between aMCI/naMCI. Black Americans, regardless of cognitive status, were more likely to fall into hypertension and diabetes groups compared to White Americans.
Discussion:
These findings underscore the critical role of diagnosis and race in MCI diagnosis and care, emphasizing the need for tailored interventions to address inequities and reduce the risk of progression to dementia.
Highlights:
The study leverages a large, racially diverse cohort from the NACC database. Black Americans with non-amnestic mild cognitive impairment(naMCI) show highest comorbidity burden. No significant differences in comorbidity burden between amnestic MCI (aMCI) and naMCI subtypes. Education is protective, but less so for Black American individuals. Older age, male sex, body mass index (BMI), and low education associate with increased risk for comorbidities.
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