Abstract

Healthy ageing research largely has a unidimensional focus on physical health, negating the importance of psychosocial factors in the maintenance of a good quality-of-life. In this cohort study, we aimed to identify trajectories of a new multidimensional metric of Active and Healthy Ageing (AHA), including their associations with socio-economic variables. A latent AHA metric was created for 14,755 participants across eight waves of data (collected between 2004 and 2019) from the English Longitudinal Study of Ageing (ELSA), using Bayesian Multilevel Item Response Theory (MLIRT). Then, Growth Mixture Modelling (GMM) was employed to identify sub-groups of individuals with similar trajectories of AHA, and multinomial logistic regression examined associations of these trajectories with socio-economic variables: education, occupational class, and wealth. Three latent classes of AHA trajectories were suggested. Participants in higher quintiles of the wealth distribution had decreased odds of being in the groups with consistently moderate AHA scores (i.e., ‘moderate-stable’), or the steepest deterioration (i.e., ‘decliners’), compared to the ‘high-stable’ group. Education and occupational class were not consistently associated with AHA trajectories. Our findings reiterate the need for more holistic measures of AHA and prevention strategies targeted at limiting socio-economic disparities in older adults’ quality-of-life.

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