Classification models for identification of at-risk groups for incident memory complaints.
BACKGROUND
Memory complaints in older adults may be a precursor of measurable cognitive decline. Causes for these complaints may vary across age groups. The goal of this study was to develop classification models for the early identification of persons at risk for memory complaints using a broad range of characteristics.


METHODS
Two age groups were studied, 55-65 years old (N = 1,416.8) and 65-75 years old (N = 471) using data from the Longitudinal Aging Study Amsterdam. Participants reporting memory complaints at baseline were excluded. Data on predictors of memory complaints were collected at baseline and analyzed using logistic regression analyses. Multiple imputation was applied to handle the missing data; missing data due to mortality were not imputed.


RESULTS
In persons aged 55-65 years, 14.4% reported memory complaints after three years of follow-up. Persons using medication, who were former smokers and had insufficient/poor hearing, were at the highest risk of developing memory complaints, i.e., a predictive value of 33.3%. In persons 65-75 years old, the incidence of memory complaints was 22.5%. Persons with a low sense of mastery, who reported having pain, were at the highest risk of memory complaints resulting in a final predictive value of 56.9%. In the subsample of persons without a low sense of mastery who (almost) never visited organizations and had a low level of memory performance, 46.8% reported memory complaints at follow-up.


CONCLUSIONS
The classification models led to the identification of specific target groups at risk for memory complaints. Suggestions for person-tailored interventions may be based on these risk profiles.
Department of Epidemiology & Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands.
Tessa N
TN
van den Kommer
Department of Psychiatry, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands.
Hannie C
HC
Comijs
Department of Epidemiology & Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands.
Kelly J
KJ
Rijs
Department of Epidemiology & Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands.
Martijn W
MW
Heymans
Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNS), Maastricht University, Maastricht, the Netherlands.
Martin P J
MP
van Boxtel
Department of Psychiatry, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands.
Dorly J H
DJ
Deeg
D000368:Aged; D003072:Cognition Disorders / Q000175:diagnosis / Q000209:etiology / Q000523:psychology; D042241:Early Diagnosis; D005260:Female; D005500:Follow-Up Studies; D015577:Geriatric Assessment / Q000379:methods; D006801:Humans; D015994:Incidence; D008297:Male; D008569:Memory Disorders / Q000150:complications / Q000175:diagnosis / Q000453:epidemiology / Q000523:psychology; D016743:Mental Competency; D008875:Middle Aged; D008962:Models, Theoretical; D009426:Netherlands / Q000453:epidemiology; D009483:Neuropsychological Tests; D011237:Predictive Value of Tests; D018570:Risk Assessment / Q000379:methods; D012307:Risk Factors; D013223:Statistics as Topic / Q000379:methods