Item-level analysis of mental health symptom trajectories during the COVID-19 pandemic in the UK: Associations with age, sex and pre-existing psychiatric conditions

Adam Hampshire; William Trender; Jon E Grant; M Berk Mirza; Rosalyn Moran; Peter J Hellyer; Samuel R Chamberlain

doi:10.1016/j.comppsych.2022.152298

Item-level analysis of mental health symptom trajectories during the COVID-19 pandemic in the UK: Associations with age, sex and pre-existing psychiatric conditions

Compr Psychiatry. 2022 Jan 31:114:152298. doi: 10.1016/j.comppsych.2022.152298. Online ahead of print.

Authors

Adam Hampshire¹, William Trender², Jon E Grant³, M Berk Mirza⁴, Rosalyn Moran⁴, Peter J Hellyer⁵, Samuel R Chamberlain⁶

Affiliations

¹ Department of Brain Sciences, Imperial College London, London, UK. Electronic address: a.hampshire@imperial.ac.uk.
² Department of Brain Sciences, Imperial College London, London, UK.
³ Department of Psychiatry, University of Chicago, Chicago, USA.
⁴ Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
⁵ Department of Brain Sciences, Imperial College London, London, UK; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
⁶ Department of Psychiatry, University of Southampton, Southampton, UK; Southern Health NHS Foundation Trust, Southampton, UK.

Abstract

Background: There is widespread concern regarding how the COVID-19 pandemic has affected mental health. Emerging meta-analyses suggest that the impact on anxiety/depression may have been transient, but much of the included literature has major methodological limitations. Addressing this topic rigorously requires longitudinal data of sufficient scope and scale, controlling for contextual variables, with baseline data immediately pre-pandemic.

Aims: To analyse self-report of symptom frequency from two largely UK-based longitudinal cohorts: Cohort 1 (N = 10,475, two time-points: winter pre-pandemic to UK first winter resurgence), and Cohort 2 (N = 10,391, two time-points, peak first wave to UK first winter resurgence).

Method: Multinomial logistic regression applied at the item level identified sub-populations with greater probability of change in mental health symptoms. Permutation analyses characterised changes in symptom frequency distributions. Cross group differences in symptom stability were evaluated via entropy of response transitions.

Results: Anxiety was the most affected aspect of mental health. The profiles of change in mood symptoms was less favourable for females and older adults. Those with pre-existing psychiatric diagnoses showed substantially higher probability of very frequent symptoms pre-pandemic and elevated risk of transitioning to the highest levels of symptoms during the pandemic. Elevated mental health symptoms were evident across intra-COVID timepoints in Cohort 2.

Conclusions: These findings suggest that mental health has been negatively affected by the pandemic, including in a sustained fashion beyond the first UK lockdown into the first winter resurgence. Women, and older adults, were more affected relative to their own baselines. Those with diagnoses of psychiatric conditions were more likely to experience transition to the highest levels of symptom frequency.

Keywords: Anxiety; COVID; Depression; Fatigue; Insomnia; SARS-CoV-2; Sleep; Well-being.