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Published in: BMC Geriatrics 1/2011

Open Access 01-12-2011 | Research article

Age, gender and disability predict future disability in older people: the Rotterdam Study

Authors: Ümit Taş, Ewout W Steyerberg, Sita MA Bierma-Zeinstra, Albert Hofman, Bart W Koes, Arianne P Verhagen

Published in: BMC Geriatrics | Issue 1/2011

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Abstract

Background

To develop a prediction model that predicts disability in community-dwelling older people. Insight in the predictors of disability is needed to target preventive strategies for people at increased risk.

Methods

Data were obtained from the Rotterdam Study, including subjects of 55 years and over. Subjects who had complete data for sociodemographic factors, life style variables, health conditions, disability status at baseline and complete data for disability at follow-up were included in the analysis. Disability was expressed as a Disability Index (DI) measured with the Health Assessment Questionnaire.
We used a multivariable polytomous logistic regression to derive a basic prediction model and an extended prediction model. Finally we developed readily applicable score charts for the calculation of outcome probabilities.

Results

Of the 5027 subjects included, 49% had no disability, 18% had mild disability, 16% had severe disability and 18% had deceased at follow-up after six years. The strongest predictors were age and prior disability. The contribution of other predictors was relatively small. The discriminative ability of the basic model was high; the extended model did not enhance predictive ability.

Conclusion

As prior disability status predicts future disability status, interventive strategies should be aimed at preventing disability in the first place.
Appendix
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Metadata
Title
Age, gender and disability predict future disability in older people: the Rotterdam Study
Authors
Ümit Taş
Ewout W Steyerberg
Sita MA Bierma-Zeinstra
Albert Hofman
Bart W Koes
Arianne P Verhagen
Publication date
01-12-2011
Publisher
BioMed Central
Published in
BMC Geriatrics / Issue 1/2011
Electronic ISSN: 1471-2318
DOI
https://doi.org/10.1186/1471-2318-11-22

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