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Updated: Apr 15, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Anthropometric indices and dietary intake: prospective determinants of geriatric cognitive impairment?
Aditika Agarwal1, Komal Chauhan2, Kiran Shinglot3
1Research Scholar, Department of Foods and Nutrition, M.S. University of Baroda, Vadodara, Gujarat, India aaditi.ag@gmail.com.
Objective:
To assess the magnitude of elderly (aged 60-85 years) persons with cognitive impairment and its relation with their dietary and anthropometric status.
Design:
Cross-sectional study. The cognitive status of the subjects was screened using the Mini Mental Score Examination (MMSE). The binary logistic regression coefficients were ascertained for determining the association of predictors like MMSE score, body mass index (BMI) and waist-to-hip ratio (WHR) with the age of the subjects.
Setting:
Government hospitals, Vadodara, India.
Subjects:
Geriatric subjects (n = 50) aged 60-85 years.
Results:
The mean age of the elderly subjects was around 68 years old. The majority of subjects fell into the mild cognitive impairment (MCI) category, with Grade I obesity. We noted significant correlations (p < 0.05; p < 0.01) with energy, protein, vitamin B12, WHR and BMI.
Conclusions:
Cognitive abnormalities doubly elevate with advancing age, with decreased intake of dietary nutrients. The cognitive assessment undertaken focused on this rampant under-diagnosed cognition. The burgeoning prodromal insidious stage of cognitive impairment demands rapid diagnosis for preserving mental health, or else severe deterioration takes over, leading to compromised mental abilities in the elderly.
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