A machine learning approach for estimating intrinsic capacity age and its associations with multimorbidity and geroprotective agents
This model demonstrates that IC domains can estimate biological age and distinguish individuals based on their comorbidities. It also underscores the role of physical activity as a key geroprotective factor, with vigorous physical activity in females with comorbidities showing the most pronounced protective effect on IC-age. These results validate the concept of IC-age as a comprehensive measure of aging and highlight its potential to inform personalized interventions and public health strategies.
Authors
- Lars L. Andersen (ORCID: https://orcid.org/0000-0003-2777-8085)
- Fernando Diefenthaeler (ORCID: https://orcid.org/0000-0001-5632-8994)
- Luis Peñailillo (ORCID: https://orcid.org/0000-0001-7697-9700)
- Joaquín Calatayud (ORCID: https://orcid.org/0000-0002-8670-8346)
- Rodrigo Núñez‐Cortés (ORCID: https://orcid.org/0000-0002-4068-9338)
- Rodrigo Torres‐Castro (ORCID: https://orcid.org/0000-0001-7974-4333)
- Carlos Cruz‐Montecinos (ORCID: https://orcid.org/0000-0002-3835-3368)
- Rubén López‐Bueno (ORCID: https://orcid.org/0000-0002-7865-3429)
Institutions
- Universidad de Santiago de Chile (CL)
- Universitat de València (ES)
- Universidad Pública de Navarra (UPNA) (ES)
- Universidad de Zaragoza (ES)
- Edward Hines, Jr. VA Hospital (US)
- Universidade Federal de Santa Catarina (BR)
- Universidad Andrés Bello (CL)
- National Research Centre for the Working Environment (DK)
- University of Chile (CL)
- Universidad de Navarra (ES)
Publication Details
- Journal
- The Gerontologist
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1093/geront/gnaf228
- Primary Topic
- Chronic Disease Management Strategies
- Type
- article
- Field-Weighted Citation Impact
- 0.00