Active ageing profiles among older adults in Spain: A Multivariate analysis based on SHARE study

Background: Following the active ageing model based on the Health, Lifelong Learning, Participation and Security pillars, this research has a twofold objective: i) to classify older adults according to active ageing profiles, taking into account the four pillars, and ii) to ascertain the relationship between the profiles and personal and contextual factors, as well as well-being and quality of life in old age. Methods: A study sample of 5,566 Spanish older adults who participated in wave 6 of the Survey of Health, Ageing and Retirement in Europe (SHARE) was included. Data were analysed in different steps applying several statistical analyses (Principal Component, Cluster, Discriminant, Multiple Correspondence and bivariate analysis with Pearson chi-square and ANOVA). Results: Five older adult profiles were obtained (I: with moderate activity; II: quasi-dependents; III: with active ageing-limiting conditions; IV: with diverse and balanced activity; V: with excellent active ageing conditions). The first three profiles were characterised by subjects with a high average age, low educational level, who were retired or housewives, and who perceived a moderate level of loneliness, satisfaction with the social network and quality of life, as well as having a larger family network, but living in small households or alone. In contrast, the latter two profiles showed better personal and contextual conditions, well-being and quality of life. Discussion and conclusions: The multidimensional approach to active ageing followed in this article has revealed the presence of several older adult profiles, which are confined to groups with better or worse active ageing conditions. In this context, if ageing is a process that reflects the previous way of life, intervention priorities will have to consider actions that promote better conditions during the life cycle.Research of this paper is a part of i) the QASP research project, funded by the Institute of Health Carlos III, Intramural Strategical Action in Health AESI 2018 (PI18CIII/00046); ii) it has also been partially funded by REDISSEC (RD16/0005/0002 and RD16/0001/0005, co-funded by European Regional Development Fund/European Social Fund “A way to make Europe”/ ”Investing in your future”) projects; iii) the R&D Activities Program ENCAGEn-CM (H2019/HUM-5698) funded by the Community of Madrid and co-funded by the European Social Fund; iv) the ENVACES R&D+i project (MINECO-FEDER, ref. CSO2015-64115-R). Authors acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This paper uses data from SHARE Wave 6 (DOI: 10.6103/SHARE.w6.710), see Börsch-Supan et al. (63) for methodological details. The SHARE data collection has been funded by the European Commission through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193; COMPARE: CIT5-CT-2005-028857; SHARELIFE: CIT4-CT-2006-028812), FP7 (SHARE-PREP: GA Nº 211909; SHARE-LEAP: GA Nº 227822; SHARE M4: GA Nº 261982; DASISH: GA Nº 283646) and Horizon 2020 (SHARE-DEV3: GA Nº 676536; SHARE-COHESION: GA Nº 870628; SERISS: GA Nº 654221; SSHOC: GA Nº 823782) and by DG Employment, Social Affairs & Inclusion. Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the U.S. National Institute on Aging (U01_AG09740-13S2; P01_AG005842; P01_AG08291; P30_AG12815; R21_AG025169; Y1-AG-4553-01; IAG_BSR06-11; OGHA_04–064; HHSN271201300071C) and from various national funding sources is gratefully acknowledged (see www.share-project.org). The authors also wish to thank the Plos One editor and reviewers for their valuable comments and efforts towards improving the manuscript.S