Abstract
Objectives
Research demonstrated a close relationship between loneliness and depressive symptoms, but it remains unclear whether these constructs reciprocally influence each other or whether the association is due to common causes. This study aimed at examining how loneliness and depressive symptoms jointly unfold across time and how the relationship varies both within and between individuals.
Methods
We used survey data of N = 8472 older adults gathered in the English Longitudinal Study of Ageing, which included eight waves over a time period of up to 15 years. The relationship was analyzed using a latent curve model, allowing us to separate within-person processes from between-person differences in long-term growth.
Results
Results showed no prospective effects of loneliness on depressive symptoms (or vice versa) at the within-person level. Yet, within-person increases in loneliness were related to within-person increases in depressive symptoms at the same point in time. As regards the between-person effects, greater long-term growth in loneliness went along with greater long-term growth in depressive symptoms.
Conclusion
Our findings did not support the assumption that loneliness and depressive symptoms influence each other over time, but rather suggest that the short- and long-term associations may be due to a common vulnerability to the same causes.
Supplemental data for this article is available online at https://doi.org/10.1080/13607863.2022.2056138 .
Acknowledgements
The English Longitudinal Study of Ageing was developed by a team of researchers based at University College London, NatCen Social Research, the Institute for Fiscal Studies, the University of Manchester and the University of East Anglia. The data were collected by NatCen Social Research.
Disclosure statement
No potential conflict of interest was reported by the authors.
Ethics approval
ELSA has received ethical approval from the South Central – Berkshire Research Ethics Committee (21/SC/0030, 22nd March 2021). All participants gave written informed consent to participate in the study.
Data availability statement
Researchers can download ELSA data from all waves from the UK Data Service (https://beta.ukdataservice.ac.uk/datacatalogue/series/series?id=200011). The R-Code for statistical analysis is available at: https://osf.io/jrhq7/.