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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
A population-based survey of cognitive performance in a Sicilian elderly community
Paolo Ragonese1, Paolo Aridon, Marco D'Amelio
1Dipartimento Universitario di Biomedicina Sperimentale e Neuroscienze Cliniche, Università degli Studi di Palermo, Palermo, Italia.
Background:
The global burden of neurodegenerative diseases is increasing. Previous studies reported differences related to age, gender and socioeconomic status. We calculated the cognitive performances of a Sicilian population aged 65 years or older, by means of a door-to-door population-based survey in Bagheria city, Sicily.
Methods:
A door-to-door survey was carried out in the city of Bagheria, Sicily (prevalence day September 30, 2006). A cohort of 2,200 persons was randomly stratified, obtaining a 25% sample of the whole population. Cognitive function was assessed by Mini Mental State Examination (MMSE). Percentile distributions by age, gender, education and working activity were calculated. Regression models were used to analyze the relationship between the investigated variables and cognitive performance.
Results:
A total of 1,837 persons agreed to participate (1,062 women and 775 men). Distribution of MMSE showed a highly significant inverse linear trend related to the increasing age (p < 0.0001) and to the degree of education (p < 0.0001), both in men and women. We observed a significant association between higher education and a better cognitive performance (OR 6.91; CI 3.24-14.76) and an inverse association between manual kind of occupation versus not manual and a poorer cognitive status (OR 0.82; CI 0.67-0.997). Height was associated with decreased cognitive performances in women (OR = 1.03; CI = 1.01-1.05) but not in men (OR = 0.997; CI = 0.993-1.002).
Conclusions:
These findings provide a feature of cognitive performances in Sicily, measured by MMSE scores in individuals aged 65 years or older.
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