Comparing a new multimorbidity index with other multimorbidity measures for predicting disability trajectories.
Disability trajectory
Middle-aged and older adults
Multimorbidity index
Multimorbidity measures
Multimorbidity pattern
Journal
Journal of affective disorders
ISSN: 1573-2517
Titre abrégé: J Affect Disord
Pays: Netherlands
ID NLM: 7906073
Informations de publication
Date de publication:
01 Feb 2024
01 Feb 2024
Historique:
received:
19
04
2023
revised:
05
11
2023
accepted:
07
11
2023
medline:
4
12
2023
pubmed:
11
11
2023
entrez:
10
11
2023
Statut:
ppublish
Résumé
The optimal multimorbidity measures for predicting disability trajectories are not universally agreed upon. We developed a multimorbidity index among middle-aged and older community-dwelling Chinese adults and compare its predictive ability of disability trajectories with other multimorbidity measures. This study included 17,649 participants aged ≥50 years from the China Health and Retirement Longitudinal Survey 2011-2018. Two disability trajectory groups were estimated using the total disability score differences calculated between each follow-up visit and baseline. A weighted index was constructed using logistic regression models for disability trajectories based on the training set (70 %). The index and the condition count were used, along with the pattern identified by the latent class analysis to measure multimorbidity at baseline. Logistic regression models were used in the training set to examine associations between each multimorbidity measure and disability trajectories. C-statistics, integrated discrimination improvements, and net reclassification indices were applied to compare the performance of different multimorbidity measures in predicting disability trajectories in the testing set (30 %). In the newly developed multimorbidity index, the weights of the chronic conditions varied from 1.04 to 2.55. The multimorbidity index had a higher predictive performance than the condition count. The condition count performed better than the multimorbidity pattern in predicting disability trajectories. Self-reported chronic conditions. The multimorbidity index may be considered an ideal measurement in predicting disability trajectories among middle-aged and older community-dwelling Chinese adults. The condition count is also suggested due to its simplicity and superior predictive performance.
Sections du résumé
BACKGROUND
BACKGROUND
The optimal multimorbidity measures for predicting disability trajectories are not universally agreed upon. We developed a multimorbidity index among middle-aged and older community-dwelling Chinese adults and compare its predictive ability of disability trajectories with other multimorbidity measures.
METHODS
METHODS
This study included 17,649 participants aged ≥50 years from the China Health and Retirement Longitudinal Survey 2011-2018. Two disability trajectory groups were estimated using the total disability score differences calculated between each follow-up visit and baseline. A weighted index was constructed using logistic regression models for disability trajectories based on the training set (70 %). The index and the condition count were used, along with the pattern identified by the latent class analysis to measure multimorbidity at baseline. Logistic regression models were used in the training set to examine associations between each multimorbidity measure and disability trajectories. C-statistics, integrated discrimination improvements, and net reclassification indices were applied to compare the performance of different multimorbidity measures in predicting disability trajectories in the testing set (30 %).
RESULTS
RESULTS
In the newly developed multimorbidity index, the weights of the chronic conditions varied from 1.04 to 2.55. The multimorbidity index had a higher predictive performance than the condition count. The condition count performed better than the multimorbidity pattern in predicting disability trajectories.
LIMITATION
CONCLUSIONS
Self-reported chronic conditions.
CONCLUSIONS
CONCLUSIONS
The multimorbidity index may be considered an ideal measurement in predicting disability trajectories among middle-aged and older community-dwelling Chinese adults. The condition count is also suggested due to its simplicity and superior predictive performance.
Identifiants
pubmed: 37949239
pii: S0165-0327(23)01374-5
doi: 10.1016/j.jad.2023.11.014
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
167-173Informations de copyright
Copyright © 2023 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest None.