Customize your JAMA Network experience by selecting one or more topics from the list below.
Identify all potential conflicts of interest that might be relevant to your comment.
Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued.
Err on the side of full disclosure.
If you have no conflicts of interest, check "No potential conflicts of interest" in the box below. The information will be posted with your response.
Not all submitted comments are published. Please see our commenting policy for details.
Berkowitz SA, Basu S. Unemployment Insurance, Health-Related Social Needs, Health Care Access, and Mental Health During the COVID-19 Pandemic. JAMA Intern Med. 2021;181(5):699–702. doi:10.1001/jamainternmed.2020.7048
More than 30 million jobs have been lost during the coronavirus disease 2019 (COVID-19) pandemic.1 Unemployment insurance (UI) was temporarily expanded by the Coronavirus Aid, Relief, and Economic Security (CARES) Act,2 but further reform is under debate. Key CARES Act provisions were adding $600 weekly federal payments to state payments (Federal Pandemic Unemployment Compensation), longer benefit duration (Pandemic Emergency Unemployment Compensation), and broadened eligibility for minimum-wage, self-employed, contract, and gig workers (Pandemic Unemployment Assistance).2
Unemployment insurance may have short-term health effects through at least 3 pathways,3 as benefit income can meet health-related social needs (eg, food and housing), cover health care access expenses (eg, insurance premiums, co-pays, transportation), and reduce stress, thereby improving mental health. We hypothesized that among those with pandemic-related income disruption, living in a household receiving UI benefits would be associated with lower health-related social needs, better health care access, and better mental health.
This cross-sectional study used data from the repeated cross-sectional Household Pulse Survey (https://www.census.gov/householdpulsedata) collected from June 11 to July 21, 2020 (response rate: 3.0%). We included working-age adults (born between 1955 and 2002, inclusive) who reported current household income disruption from pandemic-related job loss. The University of North Carolina Institutional Review Board exempted the study from review because it did not consider this human subjects research (Study No. 20-2657).
Receiving UI was defined as using UI benefits to meet spending needs in the last 7 days. Study outcomes were food insufficiency,4 missing last month’s housing payment, lack of confidence in affording next month’s food or housing, being uninsured, delaying health care, delaying non-COVID-19–related health care, depressive symptoms, and anxiety symptoms.5,6
We fit survey-weighted log-Poisson regression models to estimate adjusted relative risks, using generalized estimating equations to account for repeated measures within individuals and robust variance estimation (analysis code: http://saberkowitz.web.unc.edu/statistical-code/household-pulse-unemployment-insurance-code/). The unit of analysis was the person-week (individuals could participate up to 3 times). Model covariates were age, gender, self-reported race/ethnicity, education level, 2019 annual household income, marital status, household size, state, and survey date. We multiply imputed missing data (see eMethods in the Supplement) and used the false discovery rate for type I error control. Analyses were conducted in SAS, version 9.4 (SAS Institute) and R, version 3.5.3 (R Foundation for Statistical Computing). Unadjusted analyses used t tests for continuous variables and χ2 tests for categorical variables, with 2-tailed P values. Given multiple outcomes in this study, we used the false discovery rate approach to control for type I error. Therefore, we present regression results with both a nominal P value and a Q value, which can be interpreted as indicating the proportion of results with that Q value or lower that would be expected to be a false positive accounting for all the analyses conducted. Thus, a Q value less than .05 indicates that, accounting for multiple analyses, a given result is expected to be a false positive less than 5% of the time. We interpreted a Q value less than .05 to indicate statistical significance.
A total of 68 911 included individuals, representing 34 million people in the US, provided 79 032 survey responses. The mean (SD) age was 39.5 (13.4) years, and 50.7% were women. There were 28 738 individuals, representing 12 million Americans (weighted percentage of sample: 36%), who reported household use of UI benefits in the past week (Table 1).
In adjusted analyses, being in a household that received, vs did not receive, UI benefits was associated with lower risk for unmet health-related social needs, delaying health care, and depressive and anxiety symptoms (Table 2). Being uninsured was not significantly different: relative risk, 0.97 (95% CI, 0.92-1.03).
Being in a household that received UI was associated with fewer health-related social needs, less health care delay, and better mental health. However, many who reported pandemic-related job loss did not receive UI—particularly Hispanic individuals and those with less education.
Pandemic UI reforms, specifically more generous income replacement and broader eligibility, should guide future UI programs. Future research should examine whether UI's association with health outcomes varies by reason for job loss, race/ethnicity, prepandemic income, and number of children, and how UI benefits may intersect with other programs, such as stimulus payments and Medicaid expansion.
Important limitations include possible selection bias (owing to low survey response rate), though we used weighting for respondent representativeness and multiple imputation for missing data. Observed associations should not be considered causal given the repeated cross-section design and because UI recipients may be better off than nonrecipients in ways not accounted for (inflating the estimated benefit of UI) or those not receiving UI may have been excluded from the study after accepting underemployment (reducing estimated benefit). Also, both those who did and did not receive UI could receive other pandemic-related assistance—this may bias results to the null.
Unemployment insurance benefits may help mitigate economic disruption wrought by the pandemic. As UI reform develops, policy makers should recognize the important health benefits that UI may offer working-age people in the US.
Accepted for Publication: October 10, 2020.
Published Online: November 30, 2020. doi:10.1001/jamainternmed.2020.7048
Corresponding Author: Seth A. Berkowitz, MD, MPH, Division of General Medicine and Clinical Epidemiology, Department of Medicine, University of North Carolina at Chapel Hill, 5034 Old Clinic Bldg, CB 7110, Chapel Hill, NC 27599 (firstname.lastname@example.org).
Author Contributions: Dr Berkowitz had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: All authors.
Acquisition, analysis, or interpretation of data: Berkowitz.
Drafting of the manuscript: Berkowitz.
Critical revision of the manuscript for important intellectual content: Basu.
Statistical analysis: Berkowitz.
Conflict of Interest Disclosures: Dr Berkowitz reported receiving grants from the National Institute of Diabetes and Digestive and Kidney Diseases during the conduct of the study and personal fees from Aspen Institute outside the submitted work. Dr Basu reported receiving grants from the National Institutes of Health and Centers for Disease Control and Prevention and personal fees from PLOS Medicine, the New England Journal of Medicine, Collective Health, and HealthRight 360 outside the submitted work.
Funding/Support: Funding for Dr Berkowitz’s role in the study was provided by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health (award No. K23DK109200).
Role of the Funder/Sponsor: The National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Additional Information: The data are publicly available. Analysis code for replication is provided via the weblink in the main text.