JOURNAL ARTICLE

Generalized Anxiety Disorder Prevalence and Disparities Among U.S. Adults: The Roles Played by Job Loss, Food Insecurity, and Vaccinations During the COVID-19 Pandemic.

  • Published In: Journals of Gerontology Series B: Psychological Sciences & Social Sciences, 2025, v. 80, n. 3. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Ma, Chenyi; Smith, Tony E; Culhane, Dennis P 3 of 3

Abstract

This article examines racial and ethnic disparities in generalized anxiety disorder (GAD) among U.S. adults during the COVID-19 pandemic, focusing on the roles of job loss, food insecurity, and COVID-19 vaccination status. Using data from the U.S. Household Pulse Survey collected in March 2021, the study finds that Hispanic Americans, Black Americans, and other non-Hispanic minorities experienced higher GAD prevalence largely due to disproportionate economic hardships such as job loss and food insecurity. Older adults (65+) showed lower susceptibility to GAD compared to younger adults, and COVID-19 vaccination, particularly full vaccination, significantly mitigated GAD risk, with stronger protective effects observed among older adults. The findings suggest that addressing economic vulnerabilities and prioritizing rapid vaccine deployment, especially for older populations, are important components of effective pandemic mental health responses.

Additional Information

  • Source:Journals of Gerontology Series B: Psychological Sciences & Social Sciences. 2025/03, Vol. 80, Issue 3, p1
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2025
  • ISSN:1079-5014
  • DOI:10.1093/geronb/gbae181
  • Accession Number:184296624
  • Copyright Statement:Copyright of Journals of Gerontology Series B: Psychological Sciences & Social Sciences is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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