Author: Davillas, Apostolos; Jones, Andrew M
Title: The first wave of the COVIDâ€19 pandemic and its impact on socioeconomic inequality in psychological distress in the UK Cord-id: svx5by8i Document date: 2021_4_26
ID: svx5by8i
Snippet: We use data from the UK Household Longitudinal Study (UKHLS) to compare measures of socioeconomic inequality in psychological distress, measured by the General Health Questionnaire (GHQ), before (Waves 9 and the Interim 2019 Wave) and during the first wave of the COVIDâ€19 pandemic (April to July 2020). Based on a caseness measure, the prevalence of psychological distress increased from 18.5% to 27.7% between the 2019 Wave and April 2020 with some reversion to earlier levels in subsequent month
Document: We use data from the UK Household Longitudinal Study (UKHLS) to compare measures of socioeconomic inequality in psychological distress, measured by the General Health Questionnaire (GHQ), before (Waves 9 and the Interim 2019 Wave) and during the first wave of the COVIDâ€19 pandemic (April to July 2020). Based on a caseness measure, the prevalence of psychological distress increased from 18.5% to 27.7% between the 2019 Wave and April 2020 with some reversion to earlier levels in subsequent months. Also, there was a systematic increase in total inequality in the Likert GHQâ€12 score. However, measures of relative socioeconomic inequality have not increased. A Shapleyâ€Shorrocks decomposition analysis shows that during the peak of the first wave of the pandemic (April 2020) other socioeconomic factors declined in their share of socioeconomic inequality, while age and gender account for a larger share. The most notable increase is evident for younger women. The contribution of working in an industry related to the COVIDâ€19 response played a small role at Wave 9 and the Interim 2019 Wave, but more than tripled its share in April 2020. As the first wave of COVIDâ€19 progressed, the contribution of demographics declined from their peak level in April and chronic health conditions, housing conditions, and neighbourhood characteristics increased their contributions to socioeconomic inequality.
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