Prediction model for cognitive decline in older adults living in the community

INTRODUCTION: Because of rapid population aging cognitive decline and dementia in the older population are recognized as major public health problems. The purpose of this study was to identify demographic, health behavioral, medical and genetic factors associated with cognitive decline; and to develop a model that can predict cognitive decline. Methods and materials: Data were from the Gyeonggi Dementia and Mild Cognitive Impairment Study (GDEMCIS), with community-dwelling people aged 65 years and older. Cognitive decline was defined using the random slope and intercept linear mixed model. Those demonstrating a change in the slope less than 0 was defined as decliner. Decision tree analysis and logistic regression methods were performed to develop the prediction model for cognitive decline. RESULTS: Among the subjects 7.4% showed cognitive decline. Based on the area under the curve (AUC) the prediction model based on decision tree analysis was selected. In the modeling dataset, 59 (7.4%) showed cognitive decline. The prediction model identified 49 cognitive decliners (6.2%). The correct classification rate of the prediction model was 93.4%. CONCLUSION: In this study, a prediction model for cognitive decline in community-dwelling older people was developed. The prediction model may provide useful information to healthcare professionals in identifying and monitoring older adults vulnerable to cognitive decline.

Author dc:creator

• 백, 종환

Contributors dc:contributor

• 이, 윤환
• 대학원 의생명과학과
• 200824278

• 노인
• 인지기능
• 인지기능저하
• 예측모형
• Aged
• Cognitive function
• Cognitive decline
• Prediction model

Language dc:language

ko

Identifier

http://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000013534
000000013534

OAI identifier oai:identifier

oai:repository.ajou.ac.kr:201003/8587