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. Author manuscript; available in PMC: 2025 Oct 1.
Published in final edited form as: Health Aff (Millwood). 2024 Oct;43(10):1464–1474. doi: 10.1377/hlthaff.2023.01566

Food Insufficiency Increased After The Expiration Of COVID-19 Emergency Allotments For SNAP Benefits In 2023

Whitney Wells 1, Kaitlyn E Jackson 2, Cindy W Leung 3, Rita Hamad 2
PMCID: PMC11584048  NIHMSID: NIHMS2012421  PMID: 39374457

Abstract

In response to economic distress and food insecurity during the COVID-19 pandemic, the US Congress expanded the Supplemental Nutrition Assistance Program (SNAP) by introducing Emergency Allotments to increase monthly benefits starting in March 2020. In March 2023, Emergency Allotments expired in 35 states/territories still providing them. We provide some of the first evidence of the impacts of this loss of nutrition support—in some cases over $250/month—for economically disadvantaged households. We examined the effects of the expiration of the program on food insufficiency, mental health, and financial well-being, using data from the Census Household Pulse Survey. In difference-in-differences analyses, we compared pre-post differences among SNAP participants to pre-post differences among income-eligible non-participants. The Emergency Allotment expiration led to a substantial increase in food insufficiency (8.4 percentage points), greater food pantry use (2.1pp) and difficulty paying expenses (2.0pp). Black SNAP participants experienced a greater increase in anxiety symptoms compared with White SNAP participants. This study has implications for ongoing policymaking with respect to nutrition and safety net programs to support vulnerable families, especially amidst inflated food prices.

INTRODUCTION

The Supplemental Nutrition Assistance Program (SNAP) is the largest US nutrition safety net program, providing over 41 million families with monthly cash benefits for the purchase of food.1–3 SNAP has been shown to reduce poverty, food insecurity, and health expenditures, and to improve self-reported health, making it a highly effective form of economic stimulus during previous recessions.1,4–7 During the COVID-19 pandemic, Congress enacted several temporary changes to SNAP to combat economic distress and rising food insecurity, with the largest change being temporary Emergency Allotments (EAs) to boost benefit amounts.8–11 EA modifications included increasing monthly SNAP allotments to the household maximum for household size in March 2020, increasing total monthly allotments by 15% in January 2021, and increasing allotments for those already receiving the household maximum by $95 per month in April 2021.2 Recent studies have shown that the implementation of EAs improved food sufficiency, mental health, and financial well-being among SNAP-participating households.12,13

These changes were not intended to be permanent, and some states discontinued EAs as early as March 2021. Despite continued food and economic insecurity and high food inflation, Congress ended EAs for the remaining 35 states/territories still providing them in March 2023 with the end of the national public health emergency declaration (Appendix Exhibit A114).2,15 After EA expiration, households in these states/territories faced a decrease of at least $95/month and for some households up to $250/month or more in benefits.15,16 Recently published findings across the first states that discontinued EAs prior to the nationwide expiration have found exacerbation of food insufficiency and financial hardships among SNAP participants.16–20 No studies, to our knowledge, have examined the impacts of EA expirations for the remaining 35 states/territories, nor examined the impacts of benefit expiration after significant increases to program benefits by the Thrifty Food Plan (TFP) revisions in October 2021.21–23

This present study addresses these knowledge gaps, providing some of the first evidence of the impact of the expiration of the SNAP EAs on food insufficiency, mental health, and financial well-being in the states in which EAs expired in March 2023. This study also examines whether the expiration affected inequities by race/ethnicity or income. This study therefore provides evidence to policymakers, researchers, and stakeholders designing changes to safety net nutrition policies to meet the continued need for food and nutrition assistance in the wake of inflated food prices and increased cost of living, as well as significant increases in food insecurity across US households.24,25

METHODS

Study sample

Data were drawn from the US Census Household Pulse Survey (HPS), a nationally representative repeated cross-sectional survey collected weekly, bi-weekly, or monthly, beginning in April 2020.26 HPS participants are randomly selected by the Census Bureau during each wave to complete an internet questionnaire. In this study, we restricted HPS data to waves 51 to 59 (November 2, 2022-July 10, 2023) to isolate a period prior to and after EA expiration with the least number of changes to other safety net programs and policies that could have differentially affected SNAP participants versus non-participants (Appendix Exhibit A214). We further restricted our sample to income-eligible individuals who were residents of the states that were still providing EAs in March 2023, had no missing covariates, and had reported at least one outcome of interest (N=15,585) (Appendix Exhibit A314). SNAP eligibility was calculated using self-reported household income (before taxes) and size. We included two specifications for SNAP eligibility: 1) federal eligibility based on income below 130% of the Federal Poverty Limit (FPL), and 2) a secondary analysis calculating eligibility based on state criteria which often have higher income limits. Details further outlining SNAP eligibility can be found in the Appendix.14

Measures

Exposure

Income-eligible individuals were considered “exposed” to the SNAP EA expiration if they self-reported participation in SNAP after the expiration in March 2023.2,15 The post-expiration period was defined as the first HPS survey wave when most respondents would have experienced at least 30 days since the final EA issuance (i.e., Wave 56 beginning March 29, 2023).

Outcomes

Primary outcomes included binary variables for household food insufficiency in the last 7 days and whether anyone in the household got free groceries from a food pantry, food bank, church, or other place that provides free food. This measure of food insufficiency has been used for many years and was developed by the US Department of Agriculture to assess rapid changes over time (i.e., within the last 7 days), as opposed to the standard measure of food insecurity which asks about access over a longer recall period.27 Food insufficiency was measured via the following question: “In the last 7 days, which of these statements best describes the food eaten in your household?” Responses were captured on a four-point scale: 1) enough of the kinds of food (I/we) wanted to eat, 2) enough but not always the kinds of food (I/we) wanted to eat, 3) sometimes not enough to eat, 4) often not enough to eat. Those who selected options 2–4 were considered to have experienced marginal household food insufficiency.27 This definition of “marginal” food insufficiency, established by the US Department of Agriculture, has been used in other published works.12,13

Secondary outcomes included mental health, captured with continuous measures of depressive symptoms using the two-item Patient Health Questionnaire (PHQ-2)28 and anxiety symptoms using the two-item Generalized Anxiety Disorder (GAD-2).29 We also examined markers of financial well-being in the form of binary variables for difficulty paying for household expenses in the past seven days and being behind on rent/mortgage. Further details can be found in the Appendix.14

Covariates

We adjusted for variables that could confound the relationship between experiencing the SNAP EA expiration and the outcomes of interest. Covariates included: sex, race/ethnicity, income (captured in brackets by HPS), marital status, household size, education, and household work loss in the past 4 weeks. Race/ethnicity was self-reported, and we categorized this into non-Hispanic White, non-Hispanic Black, non-Hispanic Asian, Hispanic, and other. The latter is a heterogeneous group, but small cell sizes precluded more granular analyses. We included indicator variables (i.e., fixed effects) for state of residence as state factors may influence both SNAP participation and outcomes of interest, as well as fixed effects for survey wave to account for secular (i.e., underlying temporal) trends such as pandemic-related changes that affected all individuals during the study period.

Statistical Analysis

Primary Analysis

Descriptive statistics were tabulated and stratified by self-reported participation in SNAP and whether the survey took place after the EA expiration in March 2023.

To estimate the effects of the EA expiration, we used difference-in-differences (DiD) analysis, a commonly used analytic method to evaluate policies while accounting for secular trends.30,31 Specifically, DiD analysis compared the pre-post change in outcomes among the treatment group of income-eligible individuals who self-reported SNAP participation, while subtracting or “differencing” out the pre-post change in outcomes over time among a control group of income-eligible individuals who did not report participating in SNAP. Following the typical DiD approach, we used multivariable regression models, where the primary coefficient of interest was on an interaction term between whether an individual reported participating in SNAP and whether the observation was after EA expiration. We adjusted for all covariates listed above and included robust standard errors to account for heteroskedasticity. The analysis using state SNAP eligibility criteria included robust standard errors clustered by state. Additional details and estimating equations are included in the Appendix.14

Several assumptions are key to the DiD approach.32 Importantly, it does not require that the observed characteristics of the treatment and control groups are the same; for example, individuals who are income-eligible for SNAP who do and do not participate in SNAP differ in important ways. Rather, the approach requires that the pre-period trends (i.e., slopes) in the outcomes among the treatment and control groups are similar, and that the trends would have remained parallel if the intervention had not happened (i.e., the “parallel trends assumption”). While this counterfactual cannot be directly tested, we can assess whether trends were parallel in the treatment and control groups during the pre-period prior to the expiration. Second, the model assumes there are not differential compositional changes in the treatment and control groups over time. For this assumption, we conducted a DiD analysis similar to the main model, in which each covariate was the dependent variable in the model. Similarly, since the EA expiration may have led different people to take up SNAP benefits, we examined whether there was variation in the proportion of income-eligible individuals participating in SNAP across our study period, plotting the proportion who participated in SNAP in each wave. Additional details are provided in the Appendix.14

Analysis was performed in Stata 17, and code review was performed on all statistical code by a second analyst to ensure accuracy.

Secondary Analyses

We next assessed whether the effect of the expiration was different by income or race/ethnicity, given existing evidence that SNAP EAs showed differential effects by income and race/ethnicity.19,20 To do so, we conducted subgroup analyses by income and race/ethnicity. We included a triple interaction term between whether an individual was in each subgroup, whether an individual reported participating in SNAP, and whether the observation was after EA expiration. Additional details are provided in the Appendix.14

We also performed a falsification test using individuals income-ineligible for SNAP as the treatment group, given we would not expect these individuals to be impacted by the SNAP EA expiration. Additional details are provided in the Appendix.14

While states differed slightly in the exact date of final EA issuance and recent research has highlighted the importance of methods that account for staggered treatment,33 accounting for staggered timing was not possible in this study. While exact dates differed between February/March 2023, final issuances nevertheless occurred in rapid succession and the timing of HPS survey waves meant the majority occurred between the same HPS waves. We instead conducted a secondary analysis varying the survey wave at which we considered the benefits to have expired. Additional details are provided in the Appendix.14

Additional sensitivity analyses to test the robustness of results to alternative specifications, including alternative food insufficiency definitions and restricting the sample to those under 60, are provided in the Appendix.14

Ethical Approval

Ethical approval was not required as this study was performed on publicly available de-identified data.

RESULTS

Sample Characteristics

The final sample included 8,488 income-eligible non-participants and 7,137 SNAP participants (Exhibit 1). Compared to non-participants, SNAP participants were more likely to be female, Black, and unmarried, with income <$25,000 per year and lower educational attainment. At both time points, SNAP participants were more likely to report food insufficiency and use of food pantries, reported higher anxiety and depressive symptoms, and were more likely to report difficulty paying expenses and being behind on rent/mortgage (Exhibit 1).

Exhibit 1.

Characteristics of the Study Sample from Household Pulse Survey Nov. 22-July 2023

Income-eligible non-participants (N=8,448) SNAP Participants (N=7,137)
Pre-Expiration (N=4,980) Post-Expiration (N=3,468) Pre-Expiration (N=4,265) Post-Expiration (N=2,872)

Covariates % or Mean (SD) % or Mean (SD) % or Mean (SD) % or Mean (SD)

Male 32.4 32.7 17.9 19.6
Race/ethnicity
 Black 10.7 11.5 19.9 19.3
 White 53.0 52.0 48.9 48.9
 Hispanic 22.7 22.8 20.4 21.0
 Asian 7.3 6.5 2.9 2.6
 Other 6.3 7.1 7.9 8.2
Annual income
 <$25,000 57.3 57.5 72.4 72.8
 $25,000–$34,999 37.6 37.6 24.6 23.9
 $35,000+ 5.1 4.9 3.0 3.3
High school degree or below 31.1 34.3 41.9 42.8
Married 37.8 38.2 31.0 28.0
Work loss past 4 weeks 21.7 20.9 24.4 23.2
Household size 4.5 (1.6) 4.6 (1.7) 4.6 (1.6) 4.5 (1.6)
Age (years) 46.6 (16.5) 48.2 (16.7) 44.7 (13.1) 46.1 (13.8)

Outcomes

Household food insufficient 68.5 67.6 70.9 78.0
Use of food pantries 14.0 14.5 23.8 26.5
Anxiety symptoms score (GAD-2) 2.5 (2.1) 2.3 (2.1) 2.9 (2.2) 2.8 (2.2)
Depressive symptoms score (PHQ-2) 2.1 (2.0) 2.0 (2.0) 2.5 (2.1) 2.3 (2.1)
Somewhat/very difficult to pay expenses 60.8 59.4 72.9 72.9
Behind on rent/mortgage 17.3 15.3 26.6 24.0

SOURCE: Authors’ calculations based on data drawn from US Census Bureau Household Pulse Survey, November 2022 – July 2023 waves.

NOTES: N=15,585. Abbreviations: Supplemental Nutrition Assistance Program (SNAP); Generalized Anxiety Disorder 2-item scale (GAD-2); Patient Health Questionnaire 2-item scale (PHQ-2).

Testing DiD Assumptions

Standard tests of DiD assumptions were reassuring, demonstrating parallel trends in outcomes for the treatment and control groups during the pre-expiration period, and minimal differential compositional changes (Exhibit 2, Appendix Exhibit A4–A714). Our falsification test among individuals income-ineligible for SNAP did not show any of the patterns observed in our primary analysis, instead finding decreases for some outcomes. This suggests that our findings are unlikely to be due to other unrelated policies or secular trends. For our secondary analysis with state SNAP eligibility, parallel trends were generally reassuring except for a minor violation for food insufficiency; results for this outcome should therefore be interpreted with caution (Appendix Exhibit A1214). Additional details are provided in the Supplement.

EXHIBIT 2:

EXHIBIT 2:

[Event study plot for effect of SNAP emergency allotment expiration on household food insufficiency]

Source/Notes: SOURCE [Authors’ calculations based on data drawn from US Census Bureau Household Pulse Survey, November 2022 –July 2023 waves.] NOTES [Note: N=15,585. Abbreviations: Supplemental Nutrition Assistance Program (SNAP); Emergency Allotment (EA); Average Treatment effect on the Treated (ATT). Model is adjusted for sex, race/ethnicity, income, marital status, household size, education, age, and work loss in the past 4 weeks. The event study specification includes fixed effects for survey week and state of residence and includes robust standard errors.]

Effect of SNAP EA Expiration

The SNAP EA expiration led to a substantial increase in household food insufficiency (8.4 percentage points [pp]; 95%CI: 5.6, 11.3), representing a 12% increase from baseline (Exhibit 3). Exhibit 2 shows the event study plot for household food insufficiency by week relative to EA expiry, demonstrating the increased food insufficiency following EA expiration. We were unable to reject the null hypothesis of no change for the other outcomes, including mental health and financial well-being.

EXHIBIT 3:

EXHIBIT 3:

[Effect of SNAP emergency allotment expiration on health and financial well-being, using federal income criteria]

Source/Notes: SOURCE [Authors’ calculations based on data drawn from US Census Bureau Household Pulse Survey, November 2022 – July 2023 waves.] NOTES [N=15,585. Abbreviations: Supplemental Nutrition Assistance Program (SNAP); Generalized Anxiety Disorder 2-item scale (GAD-2); Patient Health Questionnaire 2-item scale (PHQ-2). All models are adjusted for sex, income, marital status, household size, education, age, and work loss in the past 4 weeks fixed effects for survey week and state of residence and include robust standard errors. For binary outcomes, coefficient represents percentage point change from linear probability model.]

Using state SNAP eligibility criteria, we found EA expiration led to substantial increases in household food insufficiency (6.9pp; 95%CI: 5.3, 8.6), use of food pantries (2.1pp; 0.9, 3.3), and difficulty paying expenses (2.0pp; 0.4, 3.6) (Exhibit 4). We were unable to reject the null hypothesis of no change for other outcomes.

EXHIBIT 4:

EXHIBIT 4:

[Effect of SNAP emergency allotment expiration on health and financial well-being, using state-specific income criteria]

Source/Notes: SOURCE [Authors’ calculations based on data drawn from US Census Bureau Household Pulse Survey, November 2022 –July 2023 waves.] NOTES [Note: N=41,517. Abbreviations: Supplemental Nutrition Assistance Program (SNAP); Generalized Anxiety Disorder 2-item scale (GAD-2); Patient Health Questionnaire 2-item scale (PHQ-2). All models are adjusted for sex, race/ethnicity, income, marital status, household size, education, age, and work loss in the past 4 weeks, fixed effects for survey week and state of residence and include robust standard errors clustered by state. For binary outcomes, coefficient represents percentage point change from linear probability model.]

Secondary Analyses

There was an increase in anxiety symptoms among Black (0.47; 95%CI: 0.13, 0.80) SNAP participants post EA expiration that was statistically significantly different than the null result among White participants (p=0.01, Appendix Exhibit A1014). There was also an increase in use of food pantries among Asian (14.4pp; 95%CI: 0.2, 28.6) participants despite wide confidence intervals for this group, though this was not significantly different than for White participants (p=0.14). There were no significant differences in the impact of EA expiration between Hispanic and White SNAP participants. There were also no significant differences by income.

Results of additional sensitivity analyses were similar to the main findings and are further outlined in the Appendix.14

DISCUSSION

In this national evaluation of the expiration of SNAP EAs in March 2023, we found that discontinuation of EAs led to an 8.4 pp (12%) increase in food insufficiency. In the secondary analysis using state SNAP eligibility criteria, we found discontinuation of EAs led to a 6.9pp increase in food insufficiency, 2.1pp increase in use of food pantries, and 2.0pp increase in difficulty paying expenses. It is noteworthy that our observed increase in food insufficiency occurred after a permanent 21% increase in benefits from the TFP in October 2021.21,22 While TFP revisions likely mitigated a steeper rise in food insecurity after EAs expired,23,34 our results highlight that perhaps the TFP fell short in curbing food insufficiency in the US during this critical window. These findings highlight the persistent need for food and financial support even after the official “end” of the public health crisis, especially in the face of significant increases in food insecurity across US households and inflated food prices projected to increase by 5.8% in 2023 following increases of 9.9% seen in 2022.24,25 The observed increase in food insufficiency represents a meaningful change across the US population, given roughly 1 in 8 Americans receives SNAP benefits.3

Our findings on increased food insufficiency were robust to specification of SNAP eligibility. Our findings on use of food pantries and difficulty paying expenses were consistent in direction but only reached statistical significance using state, but not federal, SNAP eligibility criteria. This is likely because state SNAP eligibility is inclusive of larger income ranges (≤130% to 200% FPL) compared to federal income ranges (≤130% only), which increased sample size and power. It is valuable to compare the two specifications given limitations of each classification; while state eligibility criteria capture additional individuals who are eligible for SNAP, HPS data does not include all criteria necessary to estimate eligibility, which could lead to misclassification.35

Our results are complementary to research investigating the effects of EA expirations in states that discontinued them earlier.17,18,20 One found a 21% relative increase in household and child food insufficiency among SNAP recipients, while a second reported a 1.0 pp decline in food sufficiency and 1.1 pp increase in difficulty paying for household expenses.17,18 A third found early EA discontinuation increased food insufficiency, with disparities among non-Hispanic White, Hispanic, and low income survey respondents.20 Notably, our study used a different population, comparing income-eligible SNAP participants with income-eligible non-participants in states that did not end EAs early, contributing rigorous evidence to this growing knowledge base around the health effects of SNAP modifications during the pandemic.

Our study also found increased anxiety symptoms among Black SNAP participants compared with White SNAP participants. One possible explanation may be racial inequities in wealth. Black families on average have less wealth—including housing and assets—and therefore fewer buffers against economic hardship; this is true even among low-income and working-class families who comprise a substantial proportion of SNAP households.36–41 Literature has demonstrated racial and ethnic disparities in food security, financial well-being, and mental health that were exacerbated by the COVID-19 pandemic, and prior research suggested that SNAP EAs reduced disparities, for example by reducing child poverty most among Black children.19,42–48

Contrary to prior research that has found SNAP benefit increases to be linked with reduced financial insecurity and improved mental health,1,12 we did not detect an effect on mental health or financial well-being in the overall sample under federal eligibility criteria. It is possible food insufficiency may be influenced by SNAP benefits more immediately compared to mental health and financial well-being, so future work should examine longer-term impacts on these outcomes. Alternately, the coinciding of the EA expiration with tax season—and the receipt of income support from the earned income tax credit during this window of the year—may have been sufficient to offset the pressures of other household expenses in the short-term, but not for food spending.

While the SNAP EAs were intended as a temporary relief, the expiration nonetheless resulted in adverse effects on food sufficiency even in the presence of the expanded benefits from the TFP revisions. For SNAP participants, it may have been especially challenging that the expiration took place in a period of continued food and economic insecurity and high food prices and that many states did not provide an “off-ramp” for loss of extra benefits.15,24,25,49

It is worth noting that SNAP EAs were designed to address specific temporary challenges during the pandemic. In March 2020, in response to widespread income loss and the need to streamline processes for SNAP offices affected by the pandemic, SNAP EAs raised benefit allotments for all SNAP participants to the household maximum. For example, households with a non-elderly person with a disability received, on average, an extra $148.69 from SNAP EAs, while households with children received, on average, an extra $164.12 from SNAP EAs.50 These substantial increases in SNAP benefit amounts were critical in mitigating severe poverty or food-related hardship as a result of the pandemic. However, there was also concern that sustaining EAs over time will result in a large cliff effect, whereby increased employment and earnings would lead to either a larger reduction in SNAP benefits or program disqualification, thus disincentivizing employment and self-sufficiency. While the design of the temporary EAs was not a long-term solution, our results support the need for off-ramp policies (e.g., eliminating asset limits, raising income eligibility cut-offs) to help transition SNAP participating households back to the pre-pandemic norms.51

This study has several strengths. We used a large diverse national dataset and a rigorous quasi-experimental study design to assess associations between a major change in safety net benefits and health.30 Food and financial insecurity, as well as mental health remain among the top public health areas of concern and warrant increased attention in light of persistent food and financial insecurity and inflated food prices, even after the end of the public health crisis.9,10,24,47,52

This study also has several limitations. Like other national surveys, HPS suffers from a high non-response rate, so results may not be generalizable to those not included in this study.26,53 HPS is also a repeated cross-sectional survey, so we were unable to observe changes in specific individuals’ outcomes. Covariates, outcomes, and SNAP participation were self-reported and may suffer from standard reporting biases. For example, previous research has highlighted potential misclassification in self-reported receipt of safety net benefits,54 and recent evidence estimated SNAP participation was underreported by roughly one-third in the HPS survey.18 Use of administratively derived SNAP participation would be valuable in future studies, although such linkages with survey data are often infeasible due to legal barriers. As with any DiD analysis, there may also be residual confounding based on contemporaneous policy changes or other exposures that differentially affected treatment and control groups. For example, the end of the Public Health Emergency led to several other changes to SNAP (i.e. recertification process, work requirements, college student eligibility) which could make it harder to disentangle the impact of the EA expiration. To address this issue we selected a study period to minimize other policy changes, such ending our study period before many of the other changes to SNAP took effect (Appendix Exhibit A214). Finally, the SNAP EAs were designed to be a temporary relief, and results therefore may not generalize to longer-term policy changes.

Conclusion

Since the pandemic onset, SNAP has remained at the forefront of America’s COVID-19 pandemic safety net response, and recent findings have shown that expanding monthly allotments led to improvements in food insufficiency, mental health, and financial well-being among SNAP participants.12,13,19 Indeed, during the pandemic, expansions to the US safety net more generally resulted in resources for structurally marginalized families. In this study, we demonstrated that the expiration of SNAP EAs in March 2023 (reduction of at least $95/month) led to a substantial increase in food insufficiency, as well as more adverse impacts on mental health among Black families. These findings are timely and relevant for ongoing policymaking regarding changes to program funding in the wake of the COVID-19 pandemic and the upcoming Farm Bill reauthorization. This study adds evidence to a growing knowledge base regarding the importance of pandemic-era expansions to the social safety net and the negative health impacts of removing these supports.

Supplementary Material

Appendix

References

  • 1.Robert Wood Johnson Foundation. The Impact of Increasing SNAP Benefits on Stabilizing the Economy, Reducing Poverty and Food Insecurity amid COVID-19 Pandemic. Healthy Eating Research, Research Brief, 2020 April (Internet) The Robert Wood Johnson Foundation; Accessed 2024 April 16. Available from: https://healthyeatingresearch.org/wp-content/uploads/2020/04/HER-SNAP-Brief-042220.pdf [Google Scholar]
  • 2.Long C. SNAP Emergency Allotments are Ending. US Department of Agriculture (USDA) (Internet); updated 2023 Nov 22; Accessed 2024 April 16. Available from: https://www.fns.usda.gov/blog/snap-emergency-allotments-are-ending [Google Scholar]
  • 3.SNAP Data Tables: National Level Annual Summary 2022. [Internet]. Available from: https://www.fns.usda.gov/pd/supplemental-nutrition-assistance-program-snap [Google Scholar]
  • 4.Gregory CA, Deb P. Does SNAP improve your health? Food Policy. 2015;50:11–9. [Google Scholar]
  • 5.Berkowitz SA, Seligman HK, Rigdon J, Meigs JB, Basu S. Supplemental Nutrition Assistance Program (SNAP) participation and health care expenditures among low-income adults. JAMA Intern Med. 2017;177(11):1642–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Nord M, Prell M. Food security improved following the 2009 ARRA increase in SNAP benefits. USDA Economic Research Service, Economic Research Report, 116. April, 2011. Accessed 2024 April 16. Available from: https://www.ers.usda.gov/webdocs/publications/44837/7469_err116.pdf?v=366.9 [Google Scholar]
  • 7.Smith TA, Gregory CA. Food Insecurity in the United States: Measurement, Economic Modeling, and Food Assistance Effectiveness. Annu Rev Resour Econ. 2023;15. [Google Scholar]
  • 8.Jackson KE, Yeb J, Gosliner W, Fernald LCH, Hamad R. Characterizing the Landscape of Safety Net Programs and Policies in California during the COVID-19 Pandemic. Int J Env Res Public Health. 2022;8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Ettman CK, Abdalla SM, Cohen GH, Sampson L, Vivier PM, Galea S. Low assets and financial stressors associated with higher depression during COVID-19 in a nationally representative sample of US adults. J Epidemiol Community Health. 2021;75(6):501–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Fang D, Thomsen MR, Nayga RM. The association between food insecurity and mental health during the COVID-19 pandemic. BMC Public Health. 2021;21(1):1–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Schanzenbach D, Pitts A. How much has food insecurity risen? Evidence from the Census Household Pulse Survey. Inst Policy Res Rapid Res Rep. 2020;1–10. [Google Scholar]
  • 12.Jackson K, Chiang A, Hamad R. The association of increased SNAP benefits during COVID-19 with food insufficiency and anxiety among U.S. adults: a quasi-experimental study. Rev 2023; [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Bryant A, Follett L. Hunger relief: A natural experiment from additional SNAP benefits during the COVID-19 pandemic. Lancet Reg Health-Am. 2022;10:100224. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.To access the Appendix, click on the Details tab of the article online. [Google Scholar]
  • 15.Rosenbaum D, Bergh K, Hall L. Temporary Pandemic SNAP Benefits Will End in Remaining 35 States in March 2023. Center on Budget and Policy Priorities (CBPP); 2023. [Google Scholar]
  • 16.Hall L. End of SNAP’s Temporary Emergency Allotments Resulted in Substantial Benefit Cut [Internet]. Center on Budget and Policy Priorities (CBPP); Available from: https://www.cbpp.org/blog/end-of-snaps-temporary-emergency-allotments-resulted-in-substantial-benefit-cut [Google Scholar]
  • 17.Dasgupta K, Plum A. Termination of SNAP Emergency Allotments, Food Sufficiency, and Economic Hardships. Board of Governors of the Federal Reserve System, Finance and Economic Discussion Series [FEDS] July, 2023. Available from: https://www.federalreserve.gov/econres/feds/termination-of-snap-emergency-allotments-food-sufficiency-and-economic-hardships.htm. Accessed 2024, April 16. [Google Scholar]
  • 18.Richterman A, Roberto CA, Thirumurthy H. Associations Between Ending Supplemental Nutrition Assistance Program Emergency Allotments and Food Insufficiency. In American Medical Association; 2023. p. e232511–e232511. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Wheaton L, Kwon D. Effect of the Reevaluated Thrifty Food Plan and Emergency Allotments on Supplemental Nutrition Assistance Program Benefits and Poverty. Wash DC Urban Inst. 2022;500. [Google Scholar]
  • 20.Sanjeevi N, Monsivais P. Association of emergency allotment discontinuation with household food insufficiency in Supplemental Nutrition Assistance Program participants: A quasi-experimental study. Prev Med. 2023;177:107784. [DOI] [PubMed] [Google Scholar]
  • 21.Gundersen C, Seligman H. How Can We Fully Realize SNAP’s Health Benefits? N Engl J Med. 2022;386(15):1389–91. [DOI] [PubMed] [Google Scholar]
  • 22.US Department of Agriculture (USDA ). SNAP and the Thrifty Food Plan [Internet] 2023. Nov. Available from: https://www.fns.usda.gov/snap/thriftyfoodplan [Google Scholar]
  • 23.Leung CW, Wolfson JA. The impact of the 2021 Thrifty Food Plan benefit re-evaluation on SNAP participants’ short-term food security and health outcomes. Front Public Health. 2023;11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.USDA Economic Research Service. Food Price Outlook, 2023 and 2024 [Internet]. Available from: https://www.ers.usda.gov/data-products/food-price-outlook/summary-findings/ [Google Scholar]
  • 25.Food and Nutrition Service, US Department of Agriculture. ERS Household Food Security in the U.S 2022. US Department of Agriculture; [Google Scholar]
  • 26.United States Census Bureau. Household Pulse Survey: Measuring Social and Economic Impacts during the Coronavirus Pandemic [Internet]. Available from: https://www.census.gov/programs-surveys/household-pulse-survey.html [Google Scholar]
  • 27.US Department of Agriculture (USDA). Food Security in the US: Measurement [Internet]. Available from: https://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-u-s/measurement/ [Google Scholar]
  • 28.Kroenke K, Spitzer RL, Williams JB. The Patient Health Questionnaire-2: validity of a two-item depression screener. Med Care. 2003;1284–92. [DOI] [PubMed] [Google Scholar]
  • 29.Sapra A, Bhandari P, Sharma S, Chanpura T, Lopp L. Using generalized anxiety disorder-2 (GAD-2) and GAD-7 in a primary care setting. Cureus. 2020;12(5). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Dimick JB, Ryan AM. Methods for evaluating changes in health care policy: the difference-in-differences approach. Jama. 2014;312(22):2401–2. [DOI] [PubMed] [Google Scholar]
  • 31.Basu S, Meghani A, Siddiqi A. Evaluating the health impact of large-scale public policy changes: classical and novel approaches. Annu Rev Public Health. 2017;38:351–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Cunningham S. Causal inference: The mixtape. Yale university press; 2021. [Google Scholar]
  • 33.Roth J, Sant’Anna PH, Bilinski A, Poe J. What’s trending in difference-in-differences? A synthesis of the recent econometrics literature. J Econom. 2023; 235:2218–44. [Google Scholar]
  • 34.Gundersen C. A proposal to reconstruct the Supplemental Nutrition Assistance Program (SNAP) into a universal basic income program for food. Food Policy. 2021;101:102096. [Google Scholar]
  • 35.U.S. Department of Agriculture. Broad-Based Categorical Eligibility (BBCE) [Internet]. 2024. Jan. Available from: https://www.fns.usda.gov/snap/broad-based-categorical-eligibility [Google Scholar]
  • 36.Bhutta N, Chang AC, Dettling LJ, Hsu J. “Disparities in Wealth by Race and Ethnicity in the 2019 Survey of Consumer Finances,” FEDS Notes. [Serial on the Internet] Washington: Board of Governors of the Federal Reserve System, 2020. September 28. Accessed 2024 April 16. Available from: 10.17016/2380-7172.2797 [DOI] [Google Scholar]
  • 37.Derenoncourt E, Kim CH, Kuhn M, Schularick M. Wealth of two nations: The US racial wealth gap, 1860–2020. National Bureau of Economic Research; 2022. [Google Scholar]
  • 38.Sullivan L, Meschede T, Dietrich L, Shapiro T. The racial wealth gap. Institue Assests Soc Policy Brand Univ DEMOS. 2015; [Google Scholar]
  • 39.Taylor P, Kochhar R, Fry R, Velasco G, Motel S. Wealth gaps rise to record highs between Whites, Blacks and Hispanics. Vol. 37. Pew Research Center; Washington, DC; 2011. [Google Scholar]
  • 40.Kochhar R, Moslimani M. How wealth and wealth gaps vary by income. 2023; [Google Scholar]
  • 41.Addo FR, Darity WA Jr. Disparate recoveries: Wealth, race, and the working class after the Great Recession. Ann Am Acad Pol Soc Sci. 2021;695(1):173–92. [Google Scholar]
  • 42.Altman CE, Dondero M, Heflin CM, Nusbaum D. Current and future food insufficiency during COVID-19: examining disparities by race/ethnicity and recent work loss. J Racial Ethn Health Disparities. 2021;1–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Feng A, Schwabish J, Spievack N. Racial and Ethnic Disparities in Food Insufficiency Persist during the Pandemic. Wash DC Urban Inst Urban Wire Retrieved June. 2020;16:2021. [Google Scholar]
  • 44.Odoms-Young A, Bruce MA. Examining the Impact of Structural Racism on Food Insecurity: Implications for Addressing Racial/Ethnic Disparities. Fam Community Health. 2018;41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Armstrong-Mensah E, Patel H, Parekh P, Lee C. Mental health inequities and disparities among African American adults in the United States: The role of Race. Res Health Sci. 2020;5(3):23–37. [Google Scholar]
  • 46.McKnight-Eily LR, Okoro CA, Strine TW, Verlenden J, Hollis ND, Njai R, et al. Racial and ethnic disparities in the prevalence of stress and worry, mental health conditions, and increased substance use among adults during the COVID-19 pandemic—United States, April and May 2020. Morb Mortal Wkly Rep. 2021;70(5):162. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Daniels GE Jr, Morton MH. COVID-19 recession: Young adult food insecurity, racial disparities, and correlates. J Adolesc Health. 2023;72(2):237–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Thomeer MB, Moody MD, Yahirun J. Racial and ethnic disparities in mental health and mental health care during the COVID-19 pandemic. J Racial Ethn Health Disparities. 2023;10(2):961–76. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.O’Connell-Domenech A. Pandemic SNAP benefits just ended. Here’s how some states are making up for it. The Hill; 2023. Mar. [Google Scholar]
  • 50.Food and Nutrition Service, US Department of Agriculture. Research Brief: Early Months of the COVID-19 Pandemic in Fiscal Year 2020: Characteristics of Supplemental Nutrition Assistance Program Households [Internet] 2022. Nov. Available from: https://fns-prod.azureedge.us/sites/default/files/resource-files/Characteristics2020-COVID-19-Companion.pdf [Google Scholar]
  • 51.de Cuba SE. Cliff Effects and the Supplemental Nutrition Assistance Program. Federal Reserve Bank of Boston; 2017. Jan. [Google Scholar]
  • 52.Nagata JM, Ganson KT, Whittle HJ, Chu J, Harris OO, Tsai AC, et al. Food insufficiency and mental health in the US during the COVID-19 pandemic. Am J Prev Med. 2021;60(4):453–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.US Census Bureau. Nonresponse Bias Report for the 2020 Household Pulse Survey. [Google Scholar]
  • 54.Celhay PA, Meyer BD, Mittag N. Errors in reporting and imputation of government benefits and their implications. National Bureau of Economic Research; 2021. [Google Scholar]

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