Classification models for identification of at-risk groups for incident memory complaints

Area of Science:

• Gerontology
• Cognitive Science
• Public Health

Background:

• Memory complaints in older adults can signal cognitive decline.
• Identifying at-risk individuals early is crucial for intervention.
• Risk factors for memory complaints may differ by age.

Purpose of the Study:

• To develop classification models for early identification of individuals at risk for memory complaints.
• To analyze a broad range of characteristics associated with memory complaints.
• To differentiate risk profiles across age demographics.

Main Methods:

• Utilized data from the Longitudinal Aging Study Amsterdam (N=1,887.8).
• Studied two age groups: 55-65 and 65-75 years old.
• Employed logistic regression analyses and multiple imputation for missing data.

Main Results:

• In the 55-65 age group, medication use, former smoking, and poor hearing predicted memory complaints (33.3% predictive value).
• In the 65-75 age group, low sense of mastery and pain predicted memory complaints (56.9% predictive value).
• A subsample of 65-75 year olds with low mastery, infrequent organization visits, and poor memory performance showed a 46.8% incidence of memory complaints.

Conclusions:

• Classification models successfully identified specific at-risk groups for memory complaints.
• Identified risk profiles can inform tailored interventions for older adults.
• Early identification and intervention are key to managing age-related memory changes.