Abstract
The COVID-19 pandemic and nationally mandated restrictions to control the virus have been associated with increased mental health issues. However, the differential impact of the pandemic and lockdown on groups of individuals, and the personal characteristics associated with poorer outcomes are unknown. Data from 21 938 adults in England who participated in a stratified cohort study were analysed. Trajectories of depression and anxiety symptoms were identified using growth mixture modelling. Multinomial and logistic regression models were constructed to identify sociodemographic and personality-related risk factors associated with trajectory class membership. Four trajectories of depression and five for anxiety were identified. The most common group presented with low symptom severity throughout, other classes were identified that showed: severe levels of symptoms which increased; moderate symptoms throughout; worsening mental health during lockdown but improvements after lockdown ended; and for anxiety only, severe initial anxiety that decreased quickly during lockdown. Age, gender, ethnicity, income, previous diagnoses, living situation, personality factors and sociability were associated with different trajectories. Nearly 30% of participants experienced trajectories with symptoms in the clinical range during lockdown, and did not follow the average curve or majority group, highlighting the importance of differential trajectories. Young, female, outgoing and sociable people and essential workers experienced severe anxiety around the announcement of lockdown which rapidly decreased. Younger individuals with lower incomes and previous mental health diagnoses experienced higher and increasing levels of symptoms. Recognising the likely symptom trajectories for such groups may allow for targeted care or interventions.
Highlights
The COVID-19 pandemic has had a profound impact on the emotional state of many people across the world, leading to fears of increased mental health burden (Gunnell et al, 2020; Holmes et al, 2020)
This study aimed to identify differential trajectories of anxiety and depression symptoms before, during and after the easing of lockdown in England using growth mixture modelling (GMM), and explore participant characteristics associated with these trajectories, in order to determine how individuals have been affected and identify groups that may need additional support for their mental health
We have presented results from a very large stratified sample with high degrees of data-completion, and applied methods highlighting a number of trajectories of symptom change rather than a single average trajectory, providing more detailed information about how mental health has changed for different sub-groups
Summary
The COVID-19 pandemic has had a profound impact on the emotional state of many people across the world, leading to fears of increased mental health burden (Gunnell et al, 2020; Holmes et al, 2020) Both the illness itself and governmental attempts to control the pandemic have exposed populations to the greater likelihood of experiencing stressful life events (Brooks et al, 2020; Luykx, Vinkers, & Tijdink, 2020) such as severe illness, bereavement, unemployment and debt (Fancourt, Steptoe, & Wright, 2020b; Greenberg, Docherty, Gnanapragasam, & Wessely, 2020; Hall et al, 2020; Takian, Raoofi, & Kazempour-Ardebili, 2020; Woolhandler & Himmelstein, 2020). Recognising the likely symptom trajectories for such groups may allow for targeted care or interventions
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