Dementia prediction model in adults over 60 years old

Descripción del Articulo

In order to determine the contribution of the sociodemographic, psychosocial and health variables to a prediction model of dementia in the elderly population, a secondary analysis was carried out with the data from the “Health, Well-being and Aging. Bogotá, 2012”, with 2000 men and women over 60 yea...

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Detalles Bibliográficos
Autores: Santacruz Ortega, María del Pilar, Cobo Charry, María Fernanda, Avendaño-Prieto, Bertha Lucía, Mejía Arango, Silvia
Formato: artículo
Fecha de Publicación:2022
Institución:Pontificia Universidad Católica del Perú
Repositorio:Revistas - Pontificia Universidad Católica del Perú
Lenguaje:español
OAI Identifier:oai:revistaspuc:article/25506
Enlace del recurso:http://revistas.pucp.edu.pe/index.php/psicologia/article/view/25506
Nivel de acceso:acceso abierto
Materia:Statistical model
Dementia
Old age
Modelo estadístico
Demencia
Vejez
Modèle statistique
Démence
Vieillesse
Modelo estatístico
Demência
Velhice
Descripción
Sumario:In order to determine the contribution of the sociodemographic, psychosocial and health variables to a prediction model of dementia in the elderly population, a secondary analysis was carried out with the data from the “Health, Well-being and Aging. Bogotá, 2012”, with 2000 men and women over 60 years of age from urban and rural areas of Bogotá. To select the sample, a probabilistic, multistage, conglomerate and stratified sampling was carried out, based on the 2005 National Census. The SABE questionnaire adapted for Colombia was used. According to the level of measurement of each variable and the distribution of the data, univariate and bivariate analyzes were performed, with dementia as a criterion variable and sociodemographic and health variables as predictors; 30 variables were included. It was found that 40.1% of the variance of dementia is explained by age, educational and socioeconomic level, hypertension, stroke, depression, motor dysfunction, hip fracture, comparative health, robbery victim, alcohol consumption, memory, memory self-report and comparative memory. The findings offer a statistical model that allows the detection of risk factors for dementia and the analysis of the potentially modifiable ones for its prevention.
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