Development of a clinical prediction model for the onset of functional decline in people aged 65-75 years: pooled analysis of four European cohort studies

Nini H. Jonkman, Marco Colpo, Jochen Klenk, Chris Todd, Trynke Hoekstra, Vieri Del Panta, Kilian Rapp, Natasja M. Van Schoor, Stefania Bandinelli, Martijn W. Heymans, Dominique Mauger, Luca Cattelani, Michael D. Denkinger, Dietrich Rothenbacher, Jorunn L. Helbostad, Beatrix Vereijken, Andrea B. Maier, Mirjam Pijnappels*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Background: Identifying those people at increased risk of early functional decline in activities of daily living (ADL) is essential for initiating preventive interventions. The aim of this study is to develop and validate a clinical prediction model for onset of functional decline in ADL in three years of follow-up in older people of 65-75 years old. Methods: Four population-based cohort studies were pooled for the analysis: ActiFE-ULM (Germany), ELSA (United Kingdom), InCHIANTI (Italy), LASA (Netherlands). Included participants were 65-75 years old at baseline and reported no limitations in functional ability in ADL at baseline. Functional decline was assessed with two items on basic ADL and three items on instrumental ADL. Participants who reported at least some limitations at three-year follow-up on any of the five items were classified as experiencing functional decline. Multiple logistic regression analysis was used to develop a prediction model, with subsequent bootstrapping for optimism-correction. We applied internal-external cross-validation by alternating the data from the four cohort studies to assess the discrimination and calibration across the cohorts. Results: Two thousand five hundred sixty community-dwelling people were included in the analyses (mean age 69.7 ± 3.0 years old, 47.4% female) of whom 572 (22.3%) reported functional decline at three-year follow-up. The final prediction model included 10 out of 22 predictors: age, handgrip strength, gait speed, five-repeated chair stands time (non-linear association), body mass index, cardiovascular disease, diabetes, chronic obstructive pulmonary disease, arthritis, and depressive symptoms. The optimism-corrected model showed good discrimination with a C statistic of 0.72. The calibration intercept was 0.06 and the calibration slope was 1.05. Internal-external cross-validation showed consistent performance of the model across the four cohorts. Conclusions: Based on pooled cohort data analyses we were able to show that the onset of functional decline in ADL in three years in older people aged 65-75 years can be predicted by specific physical performance measures, age, body mass index, presence of depressive symptoms, and chronic conditions. The prediction model showed good discrimination and calibration, which remained stable across the four cohorts, supporting external validity of our findings.

Original languageEnglish
Article number179
Pages (from-to)1-12
Number of pages12
JournalBMC Geriatrics
Volume19
Issue number1
DOIs
Publication statusPublished - 27 Jun 2019

Funding

This work was supported by funding from the European Union’s Horizon 2020 research and innovation programme [grant agreement number 689238]. The ActiFE-Ulm study was funded partly by a grant from the Ministry of Science, Research and Arts, State of Baden-Wuerttemberg, Germany, and by funds of the Institute of Epidemiology and Medical Biometry, Ulm University. Funding for the English Longitudinal Study of Ageing is provided by the National Institute of Aging [grants 2RO1AG7644-01A1 and 2RO1AG017644] and a consortium of UK government departments coordinated by the Office for National Statistics. The InCHIANTI baseline study (1998–2000) was supported as a “targeted project” [ICS110.1/RF97.71] by the Italian Ministry of Health and in part by the U.S. National Institute on Aging [Contracts 263 MD 9164, 263 MD 821336]; the InCHIANTI Follow-up 1 (2001–2003) was funded by the U.S. National Institute on Aging [Contracts N.1-AG-1-1, N.1-AG-1-2111]. The Longitudinal Aging Study Amsterdam was supported by a grant from the Netherlands Ministry of Health, Welfare and Sports, Directorate of Long-Term Care. The funding agencies had no involvement in the design of this study; in the writing of the report; and in the decision to submit the paper for publication.

FundersFunder number
Institute of Epidemiology and Medical Biometry
Italian Ministry of Health
Ministry of Science, Research and Arts, State of Baden-Wuerttemberg
Netherlands Ministry of Health, Welfare and Sports, Directorate of Long-Term Care
National Institute on AgingR01AG017644, ICS110.1/RF97.71, 263 MD 821336, N.1-AG-1-2111, 263 MD 9164, 2RO1AG7644-01A1
Horizon 2020 Framework Programme689238
Universität Ulm

    Keywords

    • Active aging
    • Functioning
    • Individual patient data
    • Middle aged
    • Personalised care
    • Preventive medicine

    Fingerprint

    Dive into the research topics of 'Development of a clinical prediction model for the onset of functional decline in people aged 65-75 years: pooled analysis of four European cohort studies'. Together they form a unique fingerprint.

    Cite this