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Updated: Sep 29, 2025
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Multimorbidity Patterns in US Adults with Subjective Cognitive Decline and Their Relationship with Functional
1Department of Community Health Sciences, 12359University of Manitoba, Winnipeg, MB, Canada.
Objectives:
This study identified different multimorbidity patterns among adults with subjective cognitive decline (SCD) and examined their association with SCD-related functional difficulties.
Methods:
Data were obtained from the 2019 Behavioral Risk Factor Surveillance System. Latent class analysis was applied to identify different patterns of chronic conditions. Logistic regression was implemented to examine relationships between multimorbidity patterns and risk of SCD-related functional difficulties.
Results:
Five multimorbidity patterns were identified: severely impaired (14.6%), respiratory/depression (18.2%), obesity/diabetes (18.6%), age-associated (22.3%), and minimal chronic conditions group (26.3%). Compared with minimal chronic conditions group, severely impaired group was most likely to report SCD-related functional difficulties, followed by respiratory/depression and obesity/diabetes group.
Discussions:
Individuals in the three multimorbidity groups had elevated risk of SCD-related functional difficulties compared with minimal chronic conditions group. Characteristics of the high-risk groups identified in this study may help in development and implementation of interventions to prevent serious consequences of having multiple chronic conditions.
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