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Socioeconomic inequalities of Long COVID: findings from a population-based survey in the United Kingdom
Sharmin Shabnam; Cameron Razieh; Hajira Dambha-Miller; Thomas Yates; Clare Gillies; Yogini V Chudasama; Manish Pareek; Amitava Banerjee; Ichiro Kawachi; Ben Lacey; Eva JA Morris; Martin White; Francesco Zaccardi; Kamlesh Khunti; Nazrul Islam.
Afiliación
  • Sharmin Shabnam; Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK
  • Cameron Razieh; Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK; Office for National Statistics, Newport, NP10 8XG
  • Hajira Dambha-Miller; Primary Care Research Centre, University of Southampton
  • Thomas Yates; NIHR Leicester Biomedical Research Centre (BRC), University Hospitals of Leicester NHS Trust and University of Leicester, Leicester, LE5 4PW, UK
  • Clare Gillies; Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK
  • Yogini V Chudasama; Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK
  • Manish Pareek; Department of Respiratory Sciences, University of Leicester, Leicester, LE1 9HN, UK
  • Amitava Banerjee; Institute of Health Informatics, University College London, London, NW1 2DA, UK
  • Ichiro Kawachi; Harvard TH Chan School of Public Health, Harvard University, Boston, MA, 02115, USA
  • Ben Lacey; Oxford Population Health, Big Data Institute, University of Oxford, Oxford, OX3 7LF, UK
  • Eva JA Morris; Oxford Population Health, Big Data Institute, University of Oxford, Oxford, OX3 7LF, UK
  • Martin White; MRC Epidemiology Unit, University of Cambridge
  • Francesco Zaccardi; Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK
  • Kamlesh Khunti; Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK
  • Nazrul Islam; Oxford Population Health, Big Data Institute, University of Oxford, Oxford, OX3 7LF, UK; Faculty of Medicine, University of Southampton, Southampton, SO17 1BJ,
Preprint en Inglés | medRxiv | ID: ppmedrxiv-22281254
ABSTRACT
ObjectiveTo estimate the risk of Long COVID by socioeconomic deprivation and to further examine the socioeconomic inequalities in Long COVID by sex and occupational groups. DesignWe analysed data from the COVID-19 Infection Survey conducted by the Office for National Statistics between 26/04/2020 and 31/01/2022. This is the largest and nationally representative survey of COVID-19 in the UK and provides uniquely rich, contemporaneous, and longitudinal data on occupation, health status, COVID-19 exposure, and Long COVID symptoms. SettingCommunity-based longitudinal survey of COVID-19 in the UK. ParticipantsWe included 201,799 participants in our analysis who were aged between 16 and 64 years and had a confirmed SARS-CoV-2 infection. Main outcome measuresWe used multivariable logistic regression models to estimate the risk of Long COVID at least 4 weeks after acute SARS-CoV-2 infection by deciles of index of multiple deprivation (IMD) and adjusted for a range of demographic and spatiotemporal factors. We further examined the modifying effects of socioeconomic deprivation by sex and occupational groups. ResultsA total of 19,315 (9.6%) participants reported having Long COVID symptoms. Compared to the least deprived IMD decile, participants in the most deprived decile had a higher adjusted risk of Long COVID (11.4% vs 8.2%; adjusted OR 1.45; 95% confidence interval [CI] 1.33, 1.57). There were particularly significantly higher inequalities (most vs least deprived decile) of Long COVID in healthcare and patient facing roles (aOR 1.76; 1.27, 2.44), and in the education sector (aOR 1.62; 1.26, 2.08). The inequality of Long COVID was higher in females (aOR 1.54; 1.38, 1.71) than males (OR 1.32; 1.15, 1.51). ConclusionsParticipants living in the most socioeconomically deprived areas had a higher risk of Long COVID. The inequality gap was wider in females and certain public facing occupations (e.g., healthcare and education). These findings will help inform public health policies and interventions in adopting a social justice and health inequality lens.
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Texto completo: Disponible Colección: Preprints Base de datos: medRxiv Tipo de estudio: Experimental_studies / Estudio observacional / Estudio pronóstico / Rct Idioma: Inglés Año: 2022 Tipo del documento: Preprint
Texto completo
Añadir a Mi BVS
Imprimir
XML
Buscar en Google
Texto completo: Disponible Colección: Preprints Base de datos: medRxiv Tipo de estudio: Experimental_studies / Estudio observacional / Estudio pronóstico / Rct Idioma: Inglés Año: 2022 Tipo del documento: Preprint