Understanding the community and social determinants in mental health inequity: the impact of mass social distancing during the COVID-19 pandemic

Abstract

ABSTRACTThis study investigates the relations of individual capacity and community attributes with adults’ (age 18+) psychological impacts (i.e. anxiety, depression, and comorbidity of the two) from social restriction directives during the COVID-19 pandemic. Controlling for community-level environmental factors and individual-level characteristics, multilevel logistic regressions were carried out with nationally representative and COVID-19-specialized data from the Household Pulse Survey (N = 1,205,194) conducted by the U.S. Census Bureau between 23 April 2020 and 7 June 2021. Regression estimates show that the lack of community capacities (e.g. poverty and transit use) during the pandemic and individuals’ economic vulnerabilities (e.g. loss of income and housing instability) exacerbate mental illnesses as social distancing measures are prolonged. Particularly, a more stringent stay-at-home order was found to be related to a marginal increase in the risk of anxiety (OR = 1.014, CI = 1.000–1.029), depression (OR = 1.016, CI = 1.003–1.030), and their comorbidity (OR = 1.018, CI = 1.003–1.034). These findings suggest that the psychological impact of social distancing order can be determined by combining the effects of both individual and community capacities.KEYWORDS: Community attributesmental healthCOVID-19 social restrictionshealth inequityeconomic vulnerability Disclosure statementNo potential conflict of interest was reported by the author(s).Authors contributionsAll authors have contributed substantially to the conception, analysis, interpretation, and/or drafting of this research and approve the final version. Jin Hui Lee (JHL), JungHo Park (JHP), and Min Sook Park (MSP) designed and conducted research together; JHL led the overall framework and writing of the research; JHP led the empirical analyses and supported the writing; MSP led literature review and supported the writing; JHL had primary responsibility for final content. All authors read and approved the final article.Supplementary materialSupplemental data for this article can be accessed online at https://doi.org/10.1080/23748834.2023.2259753Additional informationFundingThe author(s) reported there is no funding associated with the work featured in this article.Notes on contributorsJin Hui LeeJin Hui Lee is a research fellow at the Korea Research Institute for Human Settlements where her research focuses on health cities, poverty cluster, and gentrification developing the evidence for urban-based solutions to improve inequalities. Dr. Lee holds a PhD in Urban and Regional Planning from the Florida State University.JungHo ParkJungHo Park is an assistant professor at the Department of Housing & Interior Design (BK21 Four AgeTech-Service Convergence) in Kyung Hee University. His research is based in the field of housing demography, urban planning, and urban informatics. He holds his Ph.D. in Urban Planning and Development from the University of Southern California.Min Sook ParkMin Sook Park is an assistant professor in the School of Information Studies at the University of Wisconsin-Milwaukee. Dr. Park’s interdisciplinary academic commitment falls under the area of health informatics by drawing from the interconnections of the traditional research areas of behavioral science and knowledge organization in the field of Information Studies, along with data science, social computing, and information technologies.