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

Published online by Cambridge University Press:  15 November 2013

Tessa N. van den Kommer ,
Hannie C. Comijs ,
Kelly J. Rijs ,
Martijn W. Heymans ,
Martin P. J. van Boxtel  and
Dorly J. H. Deeg
Tessa N. van den Kommer*
Affiliation:
Department of Epidemiology & Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands
Hannie C. Comijs
Affiliation:
Department of Psychiatry, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands
Kelly J. Rijs
Affiliation:
Department of Epidemiology & Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands
Martijn W. Heymans
Affiliation:
Department of Epidemiology & Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands
Martin P. J. van Boxtel
Affiliation:
Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNS), Maastricht University, Maastricht, the Netherlands
Dorly J. H. Deeg
Affiliation:
Department of Psychiatry, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands
*
Correspondence should be addressed to: Dr. T. N. van den Kommer, VU University Medical Center, Van der Boechorststraat 7, 1081 BT Amsterdam, the Netherlands. Phone: +31-20-4449337; Fax: +31-20-4446770. Email: [email protected].
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Abstract

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.

Keywords

incident memory complaintsclassification modelslongitudinal
Type
Research Article
Information
International Psychogeriatrics , Volume 26 , Issue 2 , February 2014 , pp. 257 - 271
Copyright
Copyright © International Psychogeriatric Association 2013 

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