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OP65 Mental health inequalities in disruptions to healthcare, economic activity and housing during COVID-19: findings from 12 UK longitudinal population surveys
  1. Michael J Green1,
  2. Giorgio Di Gessa2,
  3. Jane Maddock3,
  4. Eoin McElroy4,
  5. Ellen J Thomson5,6,
  6. Praveetha Patalay3,7,
  7. Helena L Davies6,
  8. Jessica Mundy6,
  9. Anna J Stevenson8,
  10. Alex SF Kwong9,10
  1. 1MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK
  2. 2Institute of Epidemiology and Health Care, UCL, London, UK
  3. 3MRC Unit for Lifelong Health and Ageing, UCL, London, UK
  4. 4Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
  5. 5Department of Twins Research and Genetic Epidemiology, Kings College London, London, UK
  6. 6Social, Genetic and Developmental Psychiatry Centre, Kings College London, London, UK
  7. 7Centre for Longitudinal Studies, UCL, London, UK
  8. 8Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK
  9. 9Division of Psychiatry, University of Edinburgh, Edinburgh, UK
  10. 10Population Health Sciences, University of Bristol, Bristol, UK


Background The COVID-19 pandemic with its associated virus suppression measures have disrupted many domains of life for many people. Increasingly it is recognised that negative disruptive impacts of the pandemic are not experienced equally and may exacerbate existing inequalities. People already suffering from psychological distress may have been especially vulnerable to disruptions. We investigated associations between pre-pandemic psychological distress and disruptions to healthcare, economic activity, and housing, and whether these associations were moderated by age, sex, ethnicity or education.

Methods Data were from 59,482 participants in 12 UK longitudinal adult population surveys with both pre-pandemic and COVID-19 surveys. Participants self-reported disruptions since the start of the pandemic to: healthcare (medication access, procedures, or appointments); economic activity (negative changes in employment, income or working hours); and housing (change of address or household composition). These were also combined into a cumulative measure indicating how many of these three domains had been disrupted. Logistic regression models were used within each study to estimate associations between pre-pandemic standardised psychological distress scores and disruption outcomes. Analyses were weighted for sampling design and attrition, and adjusted for age, sex, education, ethnicity, and UK country. Findings were synthesised using a random effects meta-analysis with restricted maximum likelihood. Effect modification by sex, education, ethnicity and age was assessed using group-difference tests during meta-analysis.

Results While exact prevalence varied between studies, pre-pandemic psychological distress was generally more common among women, ethnic minorities, younger age groups, and those with less education. One standard deviation higher psychological distress was associated with raised odds of health care disruptions (OR 1.40; 95% CI: 1.29–1.51; Heterogeneity I2: 79.4%) and with experiencing disruptions in two or more of the three domains examined (OR 1.22; 95% CI: 1.14–1.31; Heterogeneity I2: 75.8%), but not specifically with disruptions to economic activity (OR 1.03; 95% CI: 0.95–1.13; Heterogeneity I2: 89.5%) or housing (OR 1.00; 95% CI: 0.97–1.03; Heterogeneity I2: 0.0%). We did not find evidence of these associations differing by sex, ethnicity, education, or age group.

Conclusion Those suffering from psychological distress before the pandemic have been more likely to experience healthcare disruptions during the pandemic, and clusters of disruptions across multiple life domains. Individuals suffering from distress may need additional support to manage these disruptions, especially in relation to healthcare. Otherwise, considering psychological distress was already unequally distributed, the pandemic may exacerbate existing inequalities related to gender, ethnicity, education and age.

  • Mental Health
  • COVID-19
  • Inequalities

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