Predictors of longer-term depression trajectories during the COVID-19 pandemic: a longitudinal study in four UK cohorts.

Abstract

Background: The COVID-19 pandemic has caused an increase in mental ill health compared with prepandemic levels. Longer-term trajectories of depression in adults during the pandemic remain unclear.

Objective: We used latent growth curve modelling to examine individual trajectories of depression symptoms, and their predictors, beyond the early stage of the pandemic.

Methods: Data were collected in three waves in May 2020, September/October 2020 and February/March 2021 in four UK cohorts (Millennium Cohort Study, Next Steps cohort, British Cohort and National Child Development Study). We included n=16 978 participants (mean age at baseline: 20, 30, 50 and 62, respectively). Self-reported depressive symptoms were the study outcome.

Findings: Symptoms of depression were higher in younger compared with older age groups (d=0.7) across all waves. While depressive symptoms remained stable from May 2020 to Autumn 2020 overall (standardized mean difference (SMD)=0.03, 95% CI 0.02 to 0.04), they increased in all age groups from May 2020 to Spring 2021 (SMD=0.12, 95% CI 0.11 to 0.13). Feelings of loneliness were the strongest predictor and concurrent correlate of increasing depressive symptoms across all cohorts, prepandemic mental health problems and having a long-term illness were also significantly associated with an increase in depression symptoms across all ages. By contrast, compliance with social distancing measures did not predict an increase in depression symptoms.

Conclusions: Feeling lonely and isolated had a large effect on depression trajectories across all generations, while social distancing measures did not.

Clinical implications: These findings highlight the importance of fostering the feeling of connectedness during COVID-19-related distancing measures.