2026-07-21T22:37:48Zhttps://repisalud.isciii.es/rest/oai/requestoai:repisalud.isciii.es:20.500.12105/111752025-05-07T10:01:48Zcom_20.500.12105_2052com_20.500.12105_2051com_20.500.12105_15322col_20.500.12105_19612col_20.500.12105_19608col_20.500.12105_19613col_20.500.12105_16973
Repisalud
author
Hijas-Gomez, Ana Isabel
author
Ayala, Alba
author
Rodríguez-García, M P
author
Rodriguez-Blazquez, Carmen
author
Rojo-Perez, Fermina
author
Fernandez-Mayoralas, Gloria
author
Rodríguez-Laso, Ángel
author
Calderón-Larrañaga, Amaia
author
Forjaz, Maria João
funder
Ministerio de Economía y Competitividad (España)
funder
Basque Government (España)
funder
Caja Madrid
funder
Unión Europea. Fondo Europeo de Desarrollo Regional (FEDER/ERDF)
funder
Instituto de Salud Carlos III
funder
Comunidad de Madrid (España)
2020-10-19T08:58:26Z
2020-10-19T08:58:26Z
2020
Arch Gerontol Geriatr . Sep-Oct 2020;90:104114.
10.1016/j.archger.2020.104114
1872-6976
Archives of gerontology and geriatrics
32526561
http://hdl.handle.net/20.500.12105/11175
Background: The World Health Organization's active ageing model is based on the optimisation of four key "pillars": health, lifelong learning, participation and security. It provides older people with a policy framework to develop their potential for well-being, which in turn, may facilitate longevity. We sought to assess the effect of active ageing on longer life expectancy by: i) operationalising the WHO active ageing framework, ii) testing the validity of the factors obtained by analysing the relationships between the pillars, and iii) exploring the impact of active ageing on survival through the health pillar. Methods: Based on data from a sample of 801 community-dwelling older adults, we operationalised the active ageing model by taking each pillar as an individual construct using principal component analysis. The interrelationship between components and their association with survival was analysed using multiple regression models. Results: A three-factor structure was obtained for each pillar, except for lifelong learning with a single component. After adjustment for age, gender and marital status, survival was only significantly associated with the physical component of health (HR = 0.66; 95% CI = 0.47-0.93; p = 0.018). In turn, this component was loaded with representative variables of comorbidity and functionality, cognitive status and lifestyles, and correlated with components of lifelong learning, social activities and institutional support. Conclusion: According to how the variables clustered into the components and how the components intertwined, results suggest that the variables loading on the biomedical component of the health pillar (e.g. cognitive function, health conditions or pain), may play a part on survival chances.
eng
World Health Organization
Active aging
Survival
International Classification of Functioning, Disability and Health
Principal component analysis
The WHO active ageing pillars and its association with survival: Findings from a population-based study in Spain.
research article
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TheWHOActiveAgeing_2020.pdf
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TheWHOActiveAgeing_2020.pdf.txt