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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Correlates of Cognitive Impairment among Indian Urban Elders
Poojitha Reddy Konda1, Pawan Kumar Sharma2,3, Atul R Gandhi4
1Mediciti Institute of Medical Sciences, Ghanpur, Hyderabad, India.
Background:
Cognitive impairment among elderly is increasing owing to increases in life expectancy globally. The problem is multifactorial. The objective of the present paper was to study the correlates of cognitive impairment in an urban elderly population in India.
Methods:
A cross sectional study was conducted among 100 randomly selected urban elderly population. Data was collected upon household visits using a predesigned pretested questionnaire administered by a trained investigator. Measurements included cognitive function assessment using Mini Mental State Examination, depression assessment using Geriatric Depression Scale, blood pressure measurement and anthropometry. Cognitive impairment was defined at MMSE score <24. Logistic regression was done to identify independently associated factors with cognitive impairment.
Results:
Prevalence of cognitive impairment among elderly was 10%. Women had a higher prevalence than men. Higher age, no schooling, living single, lower weight, lower waist and hip ratios, difficulty in activities of daily living, poor self-reported health, bedridden and depression significantly associated with cognitive impairment. The independently associated factors upon logistic regression were increasing age, no schooling and bedridden status for past six months.
Conclusion:
Although the current prevalence of cognitive impairment among Indian urban elderly is low, several associated factors exist in this population that may increase the burden in future. Geriatric health policy should address the modifiable risk factors to manage the problem of cognitive impairment and its consequent outcomes.
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