Disparities in Prevalence of COVID-19, Long COVID, Disease Severity, and Mental Health Outcomes among US Adults by Industrial Sector of Employment, September-November 2022

Authors

  • Gopal K. Singh The Center for Global Health and Health Policy, Global Health and Education Projects, Inc., Riverdale, MD 20738, USA
  • Lyoung Hee Kim Institute on Healthcare Systems, The Heller School for Social Policy and Management, Brandeis University, Waltham, MA 02453, USA
  • Hyunjung Lee Department of Public Policy and Public Affairs, John McCormack Graduate School of Policy and Global Studies, University of Massachusetts Boston, 100 William T Morrissey Blvd., Boston, MA 02125, USA
  • Romuladus E Azuine The Center for Global Health and Health Policy, Global Health and Education Projects, Inc., Riverdale, MD 20738, USA

DOI:

https://doi.org/10.21106/ijtmrph.436

Keywords:

  • COVID-19,
  • Pandemic,
  • Long COVID,
  • Disease Severity,
  • Depression,
  • Anxiety,
  • Disparities,
  • Industry,
  • Social Determinants

Abstract

Background: The coronavirus disease (COVID-19) pandemic has had a major adverse impact on people’s health and well-being in the United States (US) and globally. Although inequalities in COVID-19 prevalence and to a lesser extent in Long COVID and related mental health impact among US adults have been documented, disparities in COVID-related outcomes by industrial sector of employment, an important social determinant, have not been studied. Using the latest nationally representative data, we examine disparities in COVID-19, Long COVID, and associated mental health impact among US adults aged ≥18 years by industrial sector. Methods: Using three consecutive rounds of the US Census Bureau’s Household Pulse Survey from September 14 to November 14, 2022 (N=148,813), disparities in COVID-related outcomes by industrial sector were modeled by multivariable logistic regression after controlling for race/ethnicity, socioeconomic status, health insurance, and other demographic characteristics. Results: During September–November 2022, an estimated 117 million or 48.7% of US adults reported having been diagnosed with COVID-19; 34.3 million or 29.4% of COVID patients reported developing Long COVID; 14.7 million or 12.6% of COVID patients reported experiencing severe COVID symptoms; 10.7% of COVID patients reported serious depression, and 17.8% reported serious anxiety. Adjusted for covariates, workers in wholesale trade, finance and insurance, educational services, healthcare, social assistance, and accommodation and food services had 30-39% higher odds of being diagnosed with COVID-19 than workers in the agricultural sector. Workers in social assistance, real estate, utilities, construction, and healthcare sectors had 48-102% higher adjusted odds of developing Long COVID than workers in wholesale trade. Conclusion and Implications for Translation: Marked disparities in COVID-related outcomes existed, with workers in employment industries such as healthcare, social assistance, real estate, arts and entertainment, and accommodation and food services being at increased risk of COVID-19 diagnosis, Long COVID, severe COVID symptoms, serious depression, and anxiety. Equitable access to social services and healthcare, including mental and behavioral health services, among workers afflicted with these conditions is critical to reducing inequities in COVID-related health outcomes.

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Published

2023-03-29
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How to Cite

K. Singh, G., Kim, L. H., Lee, H., & Azuine, R. E. (2023). Disparities in Prevalence of COVID-19, Long COVID, Disease Severity, and Mental Health Outcomes among US Adults by Industrial Sector of Employment, September-November 2022. International Journal of Translational Medical Research and Public Health, 7(2), 1–12. https://doi.org/10.21106/ijtmrph.436

License


Copyright © 2023 Gopal K. Singh, Lyoung Hee Kim, Hyunjung Lee, Romuladus E Azuine. Published by Global Health and Education Projects, Inc., USA.

Creative Commons License

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , which permits others to remix, transform, and build upon the work non-commercially, provided the original author is credited and the new creations are licensed under the same terms.