Post-Pandemic Inflation and Compensatory Changes: Perception, Stress, and Difficulties by Race, Ethnicity, and Those Recovering from COVID-19 Infection

Abstract

Price increases following the COVID-19 pandemic have disproportionately impacted lower-income households and historically underrepresented racial and ethnic groups—those populations who were also disproportionately impacted by COVID-19. This study examined reported economic struggles among Black, White, and Hispanic Americans and evaluated the differential experiences of those infected with COVID-19. Using data from the Census Bureau’s Household Pulse Survey collected between July 2022 and 2023, logistic regression assessed the likelihood of concern about price increases, stress from price changes, and difficulty paying their expenses between racial, ethnic, and sex subgroups who had been infected with COVID-19. Poisson models assessed differences in the compensatory coping strategies used by each group. Relative to White respondents, Black (concern OR = 1.7139, CI = 1.6522,1.7755; stress OR = 1.1627, CI = 1.068, 1.2573; difficulty OR = 1.321, CI = 1.321, 1.322), Hispanic (concern OR = 1.8708, CI = 1.7712, 1.9704; stress OR = 1.5385, CI = 1.451, 1.6261; difficulty OR = 1.343, CI = 1.342, 1.343), and Asian, any other race alone, or race in combination (concern OR = 1.9434, CI = 1.8645, 2.0223; stress OR = 1.4236, CI = 1.3471, 1.5001; difficulty OR = 1.221, CI = 1.22, 1.222) adults were more likely to be concerned about price increases, experience stress from increased prices, and have difficulty paying expenses. Individuals previously infected with COVID-19 (ME = 0.35, CI = 0.30, 0.39) reported making more changes to cope with price increases compared to those who had not been infected with COVID-19, particularly Black adults (ME = 0.01, CI = 0.08, 0.11). Black and Hispanic adults, particularly those who were infected with COVID-19, were more likely to report financial strain, experience difficulties, and use twice as many resources to meet their needs, suggesting that the COVID recovery likely exacerbated post-pandemic financial strain.

Introduction

Beyond the racial disparities in COVID-19 clinical outcomes, many vulnerable population groups experienced significant financial distress during the pandemic (Wilson, 2020). However, the post-pandemic financial and economic well-being is relatively unexplored. Financial and economic well-being is critically important as the US emerges from the COVID-19 pandemic. More specifically, even prior to the pandemic, Black and Hispanic workers, as well as workers from other vulnerable population groups, experienced a substantial wage gap (Gould, 2020; Mora & Dávila, 2018; Wilson & Rodgers III, 2016) lower household incomes (Darity Jr et al., 2018; Rothstein, 2017) compared to White workers. Therefore, concerns have emerged related to post-pandemic economic well-being among most Americans but particularly those from racially minoritized backgrounds.

The first cases of the novel coronavirus (SARS-CoV-2) were reported in Wuhan, China, in December 2019, leading the World Health Organization (WHO) to declare a Public Health Emergency of International Concern on January 30, 2020 (Liu et al., 2021). By March 11, 2020, the virus had spread worldwide, prompting the WHO to officially declare a global pandemic (Jebril, 2020). The pandemic’s height spanned 2020 and 2021, marked by widespread lockdowns, strained healthcare systems, and significant economic disruption. During this time, surges in cases were driven by the emergence of variants like Delta and Omicron (Tai et al., 2022). In 2021, vaccines became widely available, offering a critical tool in mitigating severe illness and mortality (Abba-Aji et al., 2022). By 2022, many nations transitioned from emergency responses to managing COVID-19 as an endemic disease, reflecting a shift in strategy as the acute phase subsided.

During the height of the pandemic, Blacks, Hispanics, and workers from other vulnerable populations were more likely to be essential workers in combination with being most likely to lose their jobs (Goldman et al., 2021; Jason et al., 2023; Wilson, 2020). Similarly, minority-owned businesses were hit particularly hard during the pandemic; for example, 40% of Black business owners reported they were closed in April 2020, which was double the rate of white business owners (17%) (Fairlie, 2020). These disparities are significant given that less than 10% of all businesses are Black-owned (Fairlie, 2020). More importantly, the aforementioned combination of factors quickly translated into racial and socioeconomic inequalities that varied greatly by race and ethnicity (Abedi et al., 2021; Lopez et al., 2020; Sanchez et al., 2022). The synergistic combination of these negative financial factors resulted in financial challenges, which ultimately translated into financial struggles for necessities during the pandemic that also emerged as substantial stress for minoritized and vulnerable populations.

The COVID-19 pandemic caused significant disruption to the U.S. economy. The National Bureau of Economic Research (NBER), the official arbiter of U.S. recessions, declared that the country entered a recession in February 2020, marking the sharpest economic contraction since the Great Depression. However, the pandemic-induced recession was notably brief, ending in April 2020, as government interventions such as stimulus payments, expanded unemployment benefits, and the Paycheck Protection Program mitigated some of the economic fallout (Vernengo & Nabar-Bhaduri, 2020).

Despite the relatively short duration of the official recession, the recovery has been uneven, echoing disparities seen during the Great Recession of 2008. Historically, racial, and ethnic minorities have faced slower economic recoveries due to systemic inequities in employment opportunities, wealth accumulation, and access to capital. For example, Black and Hispanic communities experienced disproportionately high rates of unemployment during the Great Recession and were slower to regain pre-crisis employment levels (Fazzari & Needler, 2021). Similarly, during the pandemic, these groups were overrepresented in low-wage, front-line jobs that were most vulnerable to layoffs and health risks, further exacerbating their economic challenges (McLaren, 2021).

However, unlike the housing market collapse that precipitated the Great Recession, the pandemic recession was driven by an abrupt halt in economic activity due to public health measures (Naseer et al., 2023). The recovery was also fueled by unprecedented federal intervention, which helped buffer income losses for many families, including racialized minorities (Danielli et al., 2021). Yet, structural inequities persisted. Black and Hispanic households faced higher rates of housing and food insecurity during the pandemic, reflecting ongoing disparities in economic resilience and potentially exacerbating the already existing racial wealth gap (Abraham et al., 2021).

Stress levels among Americans were reported higher during the pandemic for a variety of socioeconomic reasons (Canady, 2021). Studies have shown that the prolonged stress associated with the pandemic translated into reduced resilience and greater reports of mental health issues (Manchia et al., 2022). However, even post-pandemic, financial stress among Americans has been reported due to constantly rising inflation. During the pandemic, supply chain issues caused by global shortages of goods and services were directly linked to inflation (Santacreu & LaBelle, 2022). However, post-pandemic inflation rates have persisted due to strong labor markets in the context of minimal wage growth (Bernanke & Blanchard, 2023a, 2023b). In 2023, 70% of Americans viewed inflation as a major problem. Many Americans report high levels of stress associated with inflation as evidenced by a recent study that reported inflation as a significant source of stress, particularly among women and low-income socioeconomically vulnerable populations (Wu et al., 2023).

To date, the interrelationship between the economic challenges, observed inflation, and stress among COVID-19 survivors has not been explored post-pandemic despite the global impact of the pandemic. Similarly, it is unclear how stress impacts different racial-ethnic groups, particularly given the combined racial-ethnic COVID-19 and socioeconomic disparities. To address these consequences among vulnerable populations, particularly those who were infected with acute COVID-19, we explore disparities in their concerns of increasing prices, financial stress, and difficulty paying expenses and acknowledge that multiple nested domains of inequity interact in a mutually interdependent system to influence these responses to post-pandemic inflation.

Methods

Data

Data for this study were drawn from the Household Pulse Survey (Fields et al., 2020) (HHPS)—a quick deployment data collection instrument designed to collect data on a range of ways in which people’s lives have been impacted by the COVID-19 pandemic—collected between June 1, 2022, through October 17, 2022. The result of a collaboration between the US Census Bureau and other federal agencies, the HHPS began on April 23, 2020, and continues to measure how the COVID-19 pandemic is impacting households across the country from a social and economic perspective. The current study employed Phase 3.6 which included new questions on the ability to carry out day-to-day activities due to experiencing COVID-19 as well as COVID-19 vaccinations, education, employment, food sufficiency, household spending, physical and mental health, social assistance, and core demographic household characteristics. The survey instrument utilized an overlapping weekly panel of respondents, each of whom was surveyed once weekly for three weeks before being replaced by a new panel.

In total, the survey sampled roughly 108,000 responses per week, stratified by race, ethnicity, sex, and age to ensure a representative sample. Furthermore, the educational attainment of the responding adult in each household was collected to align the final weighted distribution with the 2018 American Community Survey estimates of the adult population’s educational attainment. While HHPS addresses a variety of topics, this analysis only includes items related to acute COVID-19 infection, perceived price inflation, stress over price increases, and difficulty paying usual expenses. These survey items are discussed in greater detail below.

Financial, Economic, Inflationary Concerns

While some content varied between the phases of the HHPS, this study utilized a newly added instrument evaluating the prevalence of individuals’ perceptions of inflation, stress caused by inflation, and difficulty paying expenses. The question text and answer choices are listed in Appendix 1. Additional questions then asked respondents to indicate methods they had used to meet their spending needs and changes they have made to cope with price increases. A variety of options were listed for each question, and respondents were instructed to select all that apply. The question text and response options are listed in Appendix 2. All resources used to meet spending needs were summed for each respondent to indicate their total number of resources utilized. Similarly, all changes indicated by the respondent were summed to indicate their total number of changes made to cope with price increases.

COVID-19 Infection and Vaccination

Individuals indicated whether they have ever tested positive for COVID-19 using a rapid point-of-care test, self-test, or laboratory test. Respondents indicated whether they have received the COVID-19 vaccine. While subsequent questions concern the type and number of vaccines, this analysis uses only the binary yes/no survey item.

Demographic, Household Characteristics

Respondents indicated their sex at birth which was used to create a binary indicator of female sex. Individuals classified their race as White only (N = 519,642 75.11%), Black only (N = 51,922 7.50%), Asian only (N = 31,316 4.53%), or other race/any combination (N = 28,111 4.06%). The disparity in sample sizes between different racial and ethnic groups, limits the statistical power of to draw reliable conclusions about those smaller groups; this can lead to unreliable results when comparing differences across racial/ethnic categories (Bilheimer & Klein, 2010). Therefore, Asian was combined with other race/any combination. Additionally, they classified themselves as Hispanic, Latino, or Spanish origin (N = 60,886, 8.80%). To account for heterogeneity within the sample, age, household size, region of residence, and residing in a metropolitan statistical area (MSA) were also included in the analysis.

Statistical Analysis

Mean and frequency values were calculated for the total sample as well as racial and ethnic subgroups. Between group differences were tested with F and chi-square tests. Three empirical regression models were estimated. Logistic regression modeled the relative likelihood of price concern, price-related stress, and difficulty paying expenses. The regression models included age, race, ethnicity, sex, region of residence, marital status, vaccination status, and an indicator of previous COVID-19 infection. Interactions between prior COVID-19 infection and race/ethnicity tested for differential likelihood between groups. Odds ratios were calculated for all parameters. Poisson regression modeled differences in the number of spending resources used to pay expenses and the number of strategies used to cope with price increases and model covariates were those used in the logistic specification. Marginal effects were calculated for all covariates. All models accounted for clustering of respondents within states and response rate differences between survey weeks. All estimates were weighted to reflect a nationally representative sample.

Results

Table 1 lists full sample and subsample descriptive statistics. Respondents were on average 49 (SD = 16.03) years old and lived in two to three-person households (mean-2.71, SD = 1.40). Most respondents were White (75.1%), with smaller percentages of Black (7.5%), Asian, any other race alone, or race in combination (8.6%), and Hispanic (8.8%) adults. Over half (51.31%) were female and married (56.5%). Respondents from all four geographic regions had robust representation (Northeast 14.1%, South 32.5%, Midwest 21.8%, West 31.3%). About half (53.1%) of the sample had tested positive for COVID and most (87.2%) had received at least one dose of a COVID-19 vaccine. Only 18.2% had an income below $35,000 annually with 41.2% earning between $35,000 and $99,999 and 40.6% earning $100,000 and above.

Table 1.

Sample characteristics and response frequencies

	Full Sample (691,877)			White (519,642, 75.1%)		Black (51,922, 7.5%)		Asian, any other race alone, or race in combination (59,427, 8.6%)		Hispanic (60,886, 8.8%)		Between group difference
	Mean	Std Dev	Range	Mean	Std Dev	Mean	Std Dev	Mean	Std Dev	Mean	Std Dev	F	P-Value
Age	49.05	16.03	15–86	50.25	16.13	48.35	14.53	44.50	15.12	43.83	15.40	3654	< .0001
Household size	2.71	1.48	1–10	2.61	1.40	2.83	1.62	2.98	1.60	3.18	1.73	2738	< .0001
Total price coping strategies	5.05	3.52	1–18	5.02	3.47	4.65	3.52	5.31	3.67	5.46	3.71	902	< .0001
Total spending resources	1.78	0.96	1–11	1.74	0.92	1.90	1.09	1.86	1.04	1.94	1.11	1331	< .0001
	N	%		N	%	N	%	N	%	N	%	χ 2	P-Value
Price concern	508,761	78.16		378,541	76.72	38,642	82.79	44,541	80.24	47,037	85.01	2844.58	< .0001
Price stress	406,779	69.21		296,819	67.19	32,751	75.24	35,961	70.92	41,248	79.66	4311.781	< .0001
Difficulty with expenses	203,853	31.48		140,408	28.59	20,978	45.38	18,658	33.82	23,809	43.33	9758.946	< .0001
Married	390,990	56.51		306,459	58.98	19,838	38.21	33,698	56.7	30,995	50.91	9140.927	< .0001
Male	300,991	43.5		230,318	44.32	16,717	32.2	28,812	48.48	25,144	41.3	3562.862	< .0001
Female	390,886	56.5		289,324	55.68	35,205	67.8	30,615	51.52	35,742	58.7
Vaccinated	596,913	87.15		446,948	86.9	44,966	87.36	52,936	89.87	52,063	86.45	447.7952	< .0001
Had COVID-19	361,007	53.14		272,960	53.46	22,765	44.77	30,779	52.68	34,503	57.95	2010.771	< .0001
Northeast	99,694	14.41		78,806	15.17	5920	11.4	7482	12.59	7486	12.3	37,020.65	< .0001
South	224,975	32.52		157,184	30.25	31,894	61.43	16,561	27.87	19,336	31.76
Midwest	150,586	21.76		127,320	24.5	8149	15.69	8243	13.87	6874	11.29
West	216,622	31.31		156,332	30.08	5959	11.48	27,141	45.67	27,190	44.66
Less than $35,000	102,727	18.2		70,645	16.28	12,010	32.02	8314	17.58	11,758	25.75	10,638.9	< .0001
$35,000 to $99,999	232,419	41.19		179,069	41.28	16,095	42.91	17,298	36.57	19,957	43.71
$100,000 and above	229,165	40.61		184,129	42.44	9407	25.08	21,685	45.85	13,944	30.54

Estimates are unweighted

Analyses showed several significant differences between the racial and ethnic groups. A larger proportion of Whites tested positive for COVID than other groups (χ² = 2010.8, p < 0.0001), but Blacks and Asian, any other race alone, or race in combination were more likely to have been vaccinated for COVID (χ² = 447.8, p < 0.0001). Additionally, a larger proportion of Blacks and Hispanic had price concerns (Blacks 82.8%, Hispanics 85%), price-related stress (Blacks 75.2%, Hispanics 79.7%), and difficulty with expenses (Blacks 45.4%, Hispanics 43.3%) compared to Whites (price concerns 76.7%, price stress 67.2%, difficulty with expenses 28.6%) and Asian, any other race alone, or race in combination (price concerns 80.2%, price stress 70.9%, difficulty with expenses 33.8%) (price concerns χ² = 2844.5795 p < 0.0001; price stress χ² = 4311.8, p < 0.0001; difficulty with expenses χ² = 9758.9, p < 0.0001). These groups also showed significant variation in the type of spending resources (F = 1331.14, p < 0.0001) and price coping strategies (F = 901.67, p < 0.0001) they reported.

Table 2 lists results from the logistic regression estimating the relative likelihood of reporting concerns of rising prices. Females (OR = 1.314, CI = 1.314, 1.314) and Asian, any other race alone, or race in combination (OR = 1.9434, CI = 1.8645, 2.0223), Black (Or = 1.7139, CI = 1.6522, 1.7755), and Hispanic (OR = 1.8708, CI = 1.7712, 1.9704) respondents had a significantly higher likelihood of reporting concerns about price increases relative to males and White adults, respectively. While few regional variations were observed, households with incomes between $35,000 and $99,999 (OR = 2.271, CI = 2.188, 2.357) and below $35,000 (OR = 2.983, CI = 3.303, 3.1387) were more likely to be concerned than individuals in higher income households. Compared to their counterparts who had not been infected with COVID-19, Asian, any other race alone, or race in combination (OR = 1.9659, CI = 1.904, 2.0277), Black (OR = 1.8872, CI = 1.7946, 1.9798), and Hispanic (OR = 2.1559, CI = 2.0379, 2.2739) individuals were more likely to be concerned over future price increases.

Table 2.

Likelihood of price concern, price stress, and difficulty paying usual expenses

	Likelihood of reporting concern that prices will increase						Likelihood of reporting stress due to price increases						Likelihood of reporting difficulty paying usual expenses
	Estimates model the likelihood of price concern = 1						Estimates model the likelihood of price stress = 1						Estimates model the likelihood of difficulty with expenses = 1
		Std Err	p-value	Odds ratio				Std Err	p-value	Odds ratio				Std Err	p-value	Odds ratio
					95% CI						95% CI						95% CI
Intercept	1.63	0.13	< .0001				2.06	0.11	< .0001				− 1.61	0.14	< .0001
Married	0.00	0.02	0.91	1.00	0.97	1.04	− 0.01	0.02	0.67	1.00	0.96	1.04	− 0.10	0.02	< .0001	0.91	0.88	0.94
Age	− 0.15	0.03	< .0001	0.86	0.81	0.91	− 0.46	0.03	< .0001	0.64	0.61	0.68	0.01	0.04	0.82	1.02	0.95	1.09
Female	0.27	0.02	< .0001	1.31	1.31	1.31	0.25	0.02	< .0001	1.28	1.24	1.32	0.05	0.01	< .0001	1.05	1.03	1.08
Vaccinated	− 0.77	0.04	< .0001	0.48	0.44	0.51	− 0.67	0.04	< .0001	0.51	0.47	0.54	− 0.57	0.02	< .0001	0.57	0.54	0.59
Had COVID	0.05	0.01	< .0001	1.14	1.08	1.21	0.01	0.02	0.68	1.08	1.00	1.17	0.04	0.01	0.00	1.07	1.03	1.11
Asian, Any other race alone, or race in combination	0.16	0.05	0.00	1.94	1.86	2.02	0.11	0.03	0.00	1.42	1.35	1.50	0.21	0.04	< .0001	1.22	1.22	1.22
Black, Alone	0.07	0.04	0.04	1.71	1.65	1.78	0.12	0.05	0.01	1.16	1.07	1.26	0.29	0.04	< .0001	1.32	1.32	1.32
Hispanic	0.09	0.04	0.03	1.87	1.77	1.97	0.26	0.05	< .0001	1.54	1.45	1.63	0.29	0.04	< .0001	1.34	1.34	1.34
Had COVID*Asian, Any other race alone, or race in combination	− 0.03	0.04	0.41	1.97	1.90	2.03	− 0.05	0.04	0.24	0.36	0.28	0.44	− 0.01	0.05	0.82	0.22	0.22	0.22
Had COVID*Black, Alone	0.12	0.05	0.02	1.89	1.79	1.98	0.22	0.06	0.00	1.40	1.29	1.51	0.05	0.10	0.05	1.41	1.40	1.41
Had COVID*Hispanic	0.23	0.08	0.01	2.16	2.04	2.27	0.07	0.11	0.51	1.66	1.46	1.86	0.01	0.05	0.85	1.33	1.33	1.33
Midwest	− 0.08	0.05	0.10	0.92	0.83	1.02	− 0.13	0.05	0.01	0.88	0.80	0.96	− 0.14	0.03	< .0001	0.86	0.81	0.92
South	0.10	0.04	0.02	1.10	1.02	1.19	0.04	0.04	0.31	1.04	0.96	1.13	− 0.03	0.03	0.30	0.97	0.92	1.03
West	− 0.03	0.04	0.42	0.98	0.91	1.05	− 0.07	0.04	0.04	0.92	0.85	1.00	− 0.06	0.03	0.09	0.95	0.88	1.02
Household Size	0.39	0.01	< .0001	1.48	1.44	1.52	0.52	0.02	< .0001	1.69	1.63	1.76	0.54	0.01	< .0001	1.71	1.67	1.76
$35,000 to $99,999	0.82	0.02	< .0001	2.27	2.19	2.36	0.95	0.02	< .0001	2.60	2.51	2.68	1.14	0.02	< .0001	3.12	3.01	3.24
Less than $35,000	1.14	0.03	< .0001	2.98	3.30	3.14	1.48	0.02	< .0001	4.39	4.16	4.63	1.88	0.02	< .0001	6.56	6.28	6.85

Estimates weighted to reflect nationally representative population

Indicates significant at 95% confidence interval

Reference group: Marital status (not married), Sex (male), Vaccination (not vaccinated), COVID-19 (not infected), Race (White, non-Hispanic), Region (Northeast), Income (≥ $100,000)

Table 2 lists results from the logistic regression estimating the relative likelihood of reporting price-related stress. Older individuals (OR = 0.6436, CI = 0.6052, 0.6845) and those who had been vaccinated for COVID (OR = 0.505, CI = 0.469, 0.543 =) were less likely to report stress regarding price increases compared to their counterparts. Relative to White respondents, Asian, any other race alone, or race in combination (OR = 1.4236, CI = 1.3471, 1.5001), Black (OR = 1.1627, CI = 1.068, 1.2573), and Hispanic (OR = 1.5385, CI = 1.451, 1.6261) respondents were more likely to report high levels of stress as were individuals in larger households (OR = 1.6896, CI = 1.6258, 1.7559). Black (OR = 1.402, CI = 1.2892, 1.5149) and Hispanic (OR = 1.6604, CI = 1.4648, 1.856) adults who had previously been infected with COVID were also significantly more likely than those who had not been infected with COVID to report significant price-related stress. Results for females and income groups mirror those reported above.

Table 2 lists results from the logistic regression estimating the relative likelihood of reporting difficulty paying usual expenses. Female (OR = 1.053, CI = 1.027, 1.08), those who had been infected with COVID (OR = 1.068, CI = 1.029, 1.108) and individuals in lower-income households (OR = 3.12, CI = 3.008, 3.235; OR = 6.559, CI = 6.279, 6.851) had relatively higher likelihood of reporting difficulty paying their usual expenses. While Asian, any other race alone, or race in combination (OR = 1.221, CI = 1.22, 1.222), Blacks (OR = 1.321, CI = 1.321, 1.322), and Hispanics (OR = 1.343, CI = 1.342, 1.343) had higher relative difficulty with expenses compared to Whites, only the differential likelihood among Blacks infected with COVID (OR = 1.405, CI = 1.404, 1.406) was significantly greater than their counterparts.

Tables 3 and 4 list results from the Poisson models estimating differences in the strategies used to deal with rising prices and spending resources used in the past week. As expected, females indicated a higher number of changes made to cope with increasing prices (ME = 0.16, CI = 0.12, 0.20) while those who were married (ME = − 0.06, CI = − 0.11, − 0.01) and vaccinated (ME = − 0.51, CI = − 0.58, − 0.45) reported fewer. Relative to White respondents, Black (ME = − 0.72, CI = − 0.79, − 0.65) and Hispanic (ME = − 0.34, CI = − 0.41, − 0.26) respondents reported making slightly fewer changes on average. However, Black individuals who had COVID (ME = 0.01, CI = − 0.08, 0.11) reported a greater number of price coping changes. Also, individuals in the South (ME = 0.08, CI = 0.01, 0.14) and West (ME = 0.30, CI = 0.23, 0.37) reported more strategies were used to cope with price changes compared to those in the Northeast.

Table 3.

Poisson estimation of changes make to cope with price increases

	Estimate	Std Err	95% Confidence limits		Z	Pr >|Z|	Marginal effects
							Mean	95% CI
Intercept	2.49	0.04	2.41	2.57	61.26	< .0001
Married	− 0.01	0.00	− 0.01	0.00	− 1.38	0.1662	− 0.06	− 0.11	− 0.01
Age	− 0.28	0.01	− 0.30	− 0.26	− 24.45	< .0001	− 1.45	− 1.51	− 1.39
Female	0.03	0.00	0.02	0.03	7.28	< .0001	0.16	0.12	0.20
Vaccinated	− 0.09	0.01	− 0.10	− 0.08	− 17.35	< .0001	− 0.51	− 0.58	− 0.45
Had COVID	0.06	0.00	0.05	0.06	13.09	< .0001	0.35	0.30	0.39
Asian, Any other race alone, or race in combination	0.02	0.01	0.00	0.03	2.11	0.0352	0.03	− 0.05	0.11
Black, Alone	− 0.18	0.02	− 0.22	− 0.15	− 9.97	< .0001	− 0.72	− 0.79	− 0.65
Hispanic	− 0.08	0.01	− 0.11	− 0.06	− 7.65	< .0001	− 0.34	− 0.41	− 0.26
Had COVID*Asian, Any other race alone, or race in combination	− 0.01	0.01	− 0.03	0.02	− 0.55	0.5857	− 0.60	− 0.70	− 0.49
Had COVID*Black, Alone	0.07	0.02	0.04	0.10	4.46	< .0001	0.01	0.08	0.11
Had COVID*Hispanic	− 0.03	0.02	− 0.06	0.00	− 2.24	0.0249	− 0.24	− 0.34	− 0.14
Midwest	0.01	0.02	− 0.02	0.04	0.68	0.4942	0.29	0.22	0.35
South	0.05	0.02	0.02	0.09	3.13	0.0018	0.08	0.01	0.14
West	0.06	0.01	0.03	0.09	4.18	< .0001	0.30	0.23	0.37
Household Size	0.08	0.01	0.07	0.09	11.99	< .0001	0.40	0.35	0.45
$35,000 to $99,999	0.23	0.00	0.22	0.24	48.36	< .0001	0.80	0.73	0.86
Less than $35,000	0.23	0.01	0.20	0.25	18.72	< .0001	0.98	0.93	1.03
N	467,674

Dependent Variable: Number of changes made/will make to cope with the increase in prices

Range: 1–18

Dependent Variable: How stressful has the increase in prices in the last two months been for you (1 = Very stressful, Moderately stressful; 0 = A little stressful, Not at all stressful)

Estimates model the likelihood of price stress = 1

Estimates weighted to reflect nationally representative population

Indicates significant at 95% confidence interval

Reference group: Marital status (not married), Sex (male), Vaccination (not vaccinated), COVID-19 (not infected), Race (White, non-Hispanic), Region (Northeast), Income (≥ $100,000)

Table 4.

Poisson estimation of resources used to meet spending needs

	Estimate	Std Err	95% Confidence limits		Z	Pr >|Z|	Marginal effects
							Mean	95% CI
Intercept	1.25	0.03	1.20	1.30	45.8	< .0001
Married	− 0.04	0.00	− 0.05	− 0.04	− 12.27	< .0001	− 0.10	− 0.11	− 0.08
Age	− 0.23	0.01	− 0.24	− 0.21	− 32.37	< .0001	− 0.41	− 0.43	− 0.40
Female	0.05	0.00	0.05	0.06	19.12	< .0001	0.10	0.09	0.12
Vaccinated	− 0.03	0.01	− 0.04	− 0.02	− 6.29	< .0001	− 0.07	− 0.08	− 0.05
Had COVID	0.05	0.00	0.04	0.06	13.42	< .0001	0.09	0.08	0.11
Asian, Any other race alone, or race in combination	0.03	0.01	0.01	0.05	2.49	0.0126	0.08	0.05	0.10
Black, Alone	0.03	0.01	0.01	0.05	3.21	0.0013	0.04	0.02	0.06
Hispanic	− 0.02	0.01	− 0.04	0.00	− 1.85	0.0645	0.00	− 0.02	0.02
Had COVID*Asian, Any other race alone, or race in combination	− 0.01	0.01	− 0.03	0.00	− 1.74	0.0813	0.03	0.00	0.06
Had COVID*Black, Alone	0.01	0.01	0.01	0.04	2.02	0.0309	0.09	0.06	0.12
Had COVID*Hispanic	0.02	0.01	0.00	0.04	2.35	0.0186	0.02	− 0.01	0.05
Midwest	− 0.04	0.01	− 0.05	− 0.02	− 4.3	< .0001	− 0.05	− 0.07	− 0.03
South	− 0.03	0.01	− 0.04	− 0.01	− 3.43	0.0006	− 0.06	− 0.08	− 0.05
West	0.00	0.01	− 0.01	0.02	0.56	0.5736	0.01	− 0.01	0.03
Household size	0.14	0.01	0.13	0.15	25.36	< .0001	0.25	0.23	0.27
$35,000 to $99,999	0.12	0.00	0.11	0.12	42.14	< .0001	0.27	0.25	0.29
Less than $35,000	0.17	0.01	0.16	0.19	21.07	< .0001	0.19	0.18	0.20
N	518,425

Dependent Variable: Number of sources used to meet spending need in the last week

Range: 1–11

Dependent Variable: How stressful has the increase in prices in the last two months been for you (1 = Very stressful, Moderately stressful; 0 = A little stressful, Not at all stressful)

Estimates model the likelihood of price stress = 1

Estimates weighted to reflect nationally representative population

Indicates significant at 95% confidence interval

Reference group: Marital status (not married), Sex (male), Vaccination (not vaccinated), COVID-19 (not infected), Race (White, non-Hispanic), Region (Northeast), Income (≥ $100,000)

More spending resources were used by households earning between $35,000 and $99,999 (ME = 0.27, CI = 0.25, 0.29) and less than $35,000 (ME = 0.19, CI = 0.18, 0.20) compared to household earning over $100,000. However, households in the Midwest (ME = − 0.05, CI = − 0.07, − 0.03) and South (ME = − 0.06, CI = − 0.08, − 0.05) used fewer than those in the Northeast. Black individuals (ME = 0.04, CI = 0.02, 0.06) had to utilize more resources than White adults to meet their spending needs, but there was no significant difference between those who had been diagnosed with COVID and those who had not. Females (ME = 0.10, CI = 0.09, 0.12) and those in larger households (ME = 0.25, CI = 0.23, 0.27) used more spending resources while those who were older (ME = − 0.41, CI = − 0.43, − 0.40) and married (ME = − 0.10, CI = − 0.11, − 0.08) used fewer than their counterparts (Figs. 1 and 2).

Fig. 1.

Number of sources used to meet spending needs

Fig. 2.

Count of changes made to cope with price increases

Discussion

The key outcome of this study designed to explore concerns about inflation and financial stress was that Blacks and Hispanics were significantly more likely to report financial stress and difficulties after the pandemic compared to Whites. Similarly, women were more likely to report financial stress and more likely to report a higher number of changes needed to cope with rising prices. These findings mirror a recent study of the general population, which also showed Blacks, Hispanics, and women reported higher inflation-related stress (Wu et al., 2023). In addition, an American Psychiatric Association (APA) Healthy Minds survey noted that nearly 90% of Americans reported feeling anxious or very anxious about inflation in June 2022 which was an increase over the previous month (American Psychiatric Association, n.d.). We discuss these findings in the context of the growing literature related to the longer-term consequences of the COVID-19 pandemic and specifically highlight approaches that COVID-19 survivors utilized to address persisting inflation. The key study findings are summarized in below:

Measure	Predictors
Concerns about price increases	Race/ethnicity (Black; Hispanic; Asian, any other race alone, or race in combination), sex, low income, COVID infection
Price-related stress	Race/ethnicity (Black; Hispanic; Asian, any other race alone, or race in combination), COVID infection
Difficulty paying usual expenses	Race/ethnicity (Black; Hispanic; Asian, any other race alone, or race in combination), low income
Strategies to address rising prices	Race/ethnicity (White), sex
Spending resources	Race/ethnicity (Black)

Concerns About Price Increases

In this study Blacks, Hispanics, and Asian, any other race alone, or race in combination were more likely to report concerns about prices increases than Whites. Additionally, Blacks and Hispanics who had previously been infected by COVID-19 were also more likely to report concerns about price increases than those who had not been infected by COVID-19. Women were also more likely to report concern than men and individuals from families with lower household incomes were more likely to report concern over those with higher incomes. While the observations of greater concern among those from lower household incomes appears straightforward, the issue of greater concern among individuals from racially minoritized backgrounds and women is less clear.

Price-Related Stress

Blacks, Hispanics, and Asian, any other race alone, or race in combination were more likely to report stress about prices increases than Whites. Similar to concerns about price increases, Blacks and Hispanics who had previously been infected by COVID-19 were also more likely to report price-related stress than those who had not been infected by COVID-19. Finally, older adults and those who had been vaccinated were also more likely to report stress about prices increases. Financial stressors can be related to insufficient emergency savings, rising prices, rising interest rates and lack of stable income.

Concerns about price increases are disproportionately higher among racially minoritized groups and women, reflecting deeply entrenched economic and social inequities (Hooijer & King, 2022). Scholars such as Lisa Adkins (2017) and Silvia Federici (1984) provide a framework for understanding these disparities through the lens of economic precarity, debt dependency, and the undervaluation of labor.

Historically, racially minoritized groups and women have faced systemic barriers to economic stability. These barriers manifest in wage disparities, limited access to wealth-building opportunities, and overrepresentation in lower-wage, precarious jobs (Danielli et al., 2021; Flynn et al., 2017; Montani et al., 2022). For instance, Black and Latina women earn significantly less than White men, exacerbating their financial vulnerability to cost-of-living increases (Coffey et al., 2018). This economic precarity means that even small increases in the price of necessities, such as food and housing, can disproportionately strain their budgets.

Women, in particular, are more likely to shoulder the financial management of households, a role that heightens their sensitivity to price changes. Federici (2020) emphasizes that women’s unpaid labor in caregiving and domestic work is systematically undervalued, forcing many to rely on precarious employment or high interest debt to meet family needs. This reliance on credit, coupled with limited financial resources, leaves women and racially minoritized groups more exposed to the cascading effects of economic instability. Debt dependency further compounds these challenges. Women, especially those from marginalized racial and ethnic groups, are disproportionately targeted by predatory lending practices and are more likely to incur debt to cover basic expenses (2018). This dependence creates a vicious cycle: rising prices increase reliance on debt, which in turn becomes harder to service under conditions of inflation or economic downturns.

Intergenerational wealth disparities also play a critical role. Centuries of structural inequities, such as redlining, exclusion from wealth-building programs, and labor market discrimination, have left racially minoritized groups with fewer financial safety nets. Federici (2020) highlights how these structural disadvantages intersect with women’s roles in the care economy, further exacerbating economic precarity.

Most Americans report stress financial related stress however, there are some differences by sociodemographic background. Price-related stress among minoritized adults likely begins the longstanding inequality in income (Bhutta et al., 2020). Minoritized adults not only receive lower wages, but they also suffer from less access to stable jobs, good wages, tax advantaged savings, and retirement benefits (Center for American Progress, 2023; Bhutta et al., 2020). Consequently, during recessions, minoritized adults face greater financial burden and associated stress resulting from longstanding wage gaps (Wu et al., 2023). In general wealth or the measure of a family’s financial net worth makes it easier to transition through economic downturn or emergency situations by making simple monetary adjustments (Center for American Progress, 2023). This does not occur among Americans with the lowest incomes thereby creating stress associated with inflation-based price changes and wealth is used to pay bills and respond to changes in the economy (Center for American Progress, 2023). Additionally, the wage gap can increase dramatically during economic downturns and have a differential impact on impact minoritized families.

Difficulty Paying Usual Expenses and Strategies to Address Rising Prices

Blacks, Hispanics, and Asian, any other race alone, or race in combination were more likely to report difficulty paying usual expenses as well as women compared to men. Those who had been infected and lower-income households also reported having difficulty paying usual expenses. In contrast to previous measures, Blacks and Hispanics were less likely to report changes to cope with rising prices compared to Whites. Additionally, women were more likely to report changes to cope with rising prices compared to men. The difficulties of paying usual expenses and strategies to address rising prices noted in this study can be attributed to the longstanding racial wage gap that exists in the US (Bhutta et al., 2020; Hanks et al., 2018). Reports show that price increases associated with inflation are more likely to negatively impact families from racially minoritized backgrounds and contribute to food insecurity and overall debt (Martinchek et al., 2023). Families from racially minoritized backgrounds are more likely to struggle with repaying debt and turn to credit, high interest loans, and borrowing from family and friends (Martinchek et al., 2023). In summary, families from racially minoritized backgrounds frequently face greater difficulty dealing with higher and more volatile inflation (Lee, 2022). These issues were magnified during the pandemic and particularly among those who were financially impacted during the COVID-19 pandemic. According to the Federal Reserve Bank, Black households in general experience higher and significantly more volatile inflation in consumer goods when compared to White households (Lee, 2022). Consequently, Black households consume goods at a disproportionate rate than White households when prices are volatile (Lee, 2022). The negative effects of the pandemic magnified this same consumption of goods and possibly at a more disproportionate rate than usual.

The lower likelihood of racial minorities and women to report changes to cope with rising prices compared to their counterparts can be understood through two interrelated dimensions: discrimination in financial markets and pre-existing reliance on limited coping mechanisms (Henry, 2014). Historical and systemic discrimination in the financial product market restricts access to high-quality financial tools for marginalized groups. Black and Hispanic communities, as well as women, have faced exclusionary practices such as redlining and higher interest rates, which limit their access to equitable credit and savings options (Dymski, 2013). Women, particularly single mothers, often face additional barriers, as financial institutions have undervalued their economic roles, further restricting their financial agency (Adkins, 2018). These inequities result in an overreliance on suboptimal financial products like payday loans, which exacerbate financial precarity and limit the ability to adapt to rising costs.

Simultaneously, many Black and Hispanic households, along with women, already employ a variety of strategies to manage financial constraints, such as informal savings networks or extended family support. These groups also allocate a larger share of their income to non-discretionary expenses, including housing, food, and childcare, leaving little flexibility to adjust spending when prices rise (Wladis et al., 2024). This reliance on existing coping mechanisms leaves fewer options available for further adaptation, intensifying the impact of economic pressures. The interplay of these factors—discrimination in financial markets and constrained behavioral options—creates a dual burden (Gandy, 2016). Marginalized groups not only face systemic barriers to accessing quality financial products but also operate within tighter economic margins that limit their capacity to adjust.

Those who had a previous COVID-19 infection and lower-income households also reported having difficulty paying usual expenses. Individuals with a previous Covid-19 infection may be impacted by prolonged COVID-19 symptoms, which can impair their ability to work, contributing to financial distress. These challenges are particularly pronounced for minoritized populations, who were disproportionately affected by the pandemic due to intersecting vulnerabilities. People of color, women, and immigrants are overrepresented in low-wage service industry positions, many of which were classified as “essential” during the pandemic. These roles, often lacking adequate health benefits or job security, exposed workers to greater health-related hazards, including heightened risk of COVID-19 infection, hospitalization, and death.

Minoritized communities also faced compounded economic hardships due to historical and structural inequities. Insufficient emergency savings, rising prices, rising interest rates, and lack of stable income disproportionately affected these groups, exacerbating pre-existing disparities (Bennett, Rene Bennett, n.d.). For example, Black and Hispanic households were more likely to report difficulty paying expenses during the pandemic, reflecting systemic barriers to wealth accumulation and access to resources. Furthermore, many individuals with a previous COVID-19 infection in these groups may have been essential workers, a significant number of whom experienced reduced hours, layoffs, or workplace closures.

The combined COVID-19 pandemic and racial reckoning highlighted the intersectional nature of these challenges, as minoritized populations were not only at higher risk for COVID-19 but also for the economic fallout associated with the pandemic. The relative stagnation of wages for low-wage workers, coupled with the rising cost-of-living, underscored systemic inequities in labor markets that disproportionately affect women and people of color (Department of Labor, 2023). These realities demonstrate the need for targeted policy interventions that address the intersectionality of health and economic vulnerabilities to promote equitable recovery.

A recent analysis of data from the Household Pulse Survey found that employees in states with a minimum wage of at least $12 had less difficulty paying for food (Raifman et al., 2021). Notably, we observed that individuals in the South employed more strategies to adjust to the rising prices, and the South also happens to be the region with more states without a minimum wage (Federal rate of $7.25 applies) or minimum wages below the Federal minimum (Georgia $5.15) (Brown-Podgorski et al., 2023). State minimum wage increases could be a lever to counter the rising financial stress, albeit some economists worry that minimum wage increases could exacerbate racial pay gaps (Assari, 2018a, 2018b; Brown-Podgorski et al., 2023; Dougherty et al., 2021).

In contrast with our findings about price concerns and related stress, Blacks and Hispanics were less likely to report changes to cope with rising prices compared to Whites. Additionally, women were more likely to report changes to cope with rising prices compared to men.

Spending Resources

Also, we observed that Blacks utilized more resources to meet their spending needs compared to Whites. According to Charron-Chenier et al. (2017), additionally, racial disparities in spending can exist independently of other disparities and contribute to overall racial inequality. Therefore, in this study Blacks were more likely to utilize a range of spending resources to meet their spending needs. Prior studies have shown that low-income Blacks spend 80% of their income on housings, utilities, groceries, transportation, health care and entertainment compared to low-income White households spending on 65% of their income on the same categories (Charron-Chénier et al., 2017). Taken together with persistent pay inequalities and higher percentage of income used to meet monthly needs, Black individuals were likely already financially burdened prior to the pandemic, and rising prices now require more spending resources to meet these needs. Although consumption patterns are traditionally believed to be a matter of preference, an examination of data from the Consumer Expenditure Surveys found that Black households frequently have lower levels of spending regardless of income level than their White counterparts. The overall findings of the study that Black households utilized a greater range of resources (regular income sources, credit cards/loans, selling assets or possessions, withdrawal from retirement accounts, unemployment insurance, government assistance programs, etc.) to address their needs likely is due to racial differences in family wealth. The racial wealth gap is directly related to the delayed accumulation of resources over multiple generations experienced by African Americans due to the systematic exclusion from wealth-building opportunities.

Strengths and Limitations

This study faced several limitations that should be considered when interpreting these findings. First, while assessment mechanisms in HPS are identical to those in the National Health Interview Survey and the Behavioral Risk Factor Surveillance System, HPS employed a different data collection format and sampling framework. Therefore, results may not be generalizable outside of the context in which they were collected. Second, the data represented here were self-reported. Self-reported answers may be exaggerated; respondents may be too embarrassed to reveal private details; various biases, like social desirability or recall, may affect the results. Third, all studies that rely on survey data face potential error from unobserved and undetectable non-response and miscoding bias. Finally, while the questionnaire items used in this study may closely align with measures of economic hardship, variation in the syntactical structure of HPS survey items, may present challenges when comparing rates to other studies. Finally, our analysis provides a cross-sectional ‘snapshot’ of racial economic disparities that may be exacerbated by the recent pandemic but cannot establish causality. The study design accounts for the sampling procedures to yield a population representative sample, but individuals without access to home or mobile phone, or email, could be underrepresented in the study. Strengths include data from across all 50 U.S. states and the timing of the data collection, two years into the pandemic, provides insights about ongoing repercussions of the pandemic.

Conclusion

The findings of this study highlight the greater non-health implications of COVID-19 and the persisting racially different financial implications. Pandemic-related data showed that Black and Hispanic individuals were not only more likely to be infected by the COVID-19 virus, but they were also more likely to report greater financial strain and difficulties than White individuals. These findings highlight the need to explore the longer-term impact of the pandemic on minoritized populations, particularly as they relate to the widening health-wealth gap that emerged post-pandemic.

Appendix 1

• Price Concern: In the area you live and shop, how concerned are you, if at all, that prices will increase in the next 6 months? [Very concerned, Somewhat concerned, A little concerned, Not at all concerned]

• Price-related stress: How stressful, if at all, has the increase in prices in the last two months been for you? [Very stressful, Moderately stressful, A little stressful, Not at all stressful]

• Difficulty paying expenses: In the last 7 days, how difficult has it been for your household to pay for usual household expenses, including but not limited to food, rent or mortgage, car payments, medical expenses, student loans, and so on? [Not at all difficult, A little difficult, Somewhat difficult, Very difficult]

Appendix 2

• Spending resources: Thinking about your experience in the last 7 days, which of the following did you or your household members use to meet your spending needs? [Regular income sources, Credit cards or loans, Money from saving or selling assets or possessions (including withdrawal from retirement accounts), Borrowing from friends or family, Unemployment insurance (UI) benefit payments, Money saved from deferred or forgiven payments (to meet your spending needs, Supplemental Nutrition Assistance Program (SNAP), Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), School meal debit/EBT cards, Government rental assistance]

• Strategies to cope with rising prices: What changes, if any, have you made or do you plan to make to cope with the increase in prices? [Shop at stores that offer lower prices, look for sales, and/or use coupons, Switch from name brand to generic products, Purchase less fresh produce and/or meat, Go out to eat less often or order food for delivery less often, Cancel or reduce subscription services (e.g., streaming services, meal delivery services, cell phone plan), Cancel or decrease plans to attend events, Drive less or change mode of transportation (e.g., bike or take metro instead of drive), Delay major purchases (e.g., home repair/renovation, vacations, vehicles, home appliances, cell phone or computer), Delay medical treatment (e.g., refill prescription, surgery), Work additional job(s)/shift(s) to supplement income, Contribute less to savings and/or retirement accounts, Increase use of credit cards, loans, and/or pawnshops, Decrease use of utilities (e.g., cooling, heating, water, electricity), Move to less expensive housing, Ask friends and/or family for help, Change or reduce plans for childcare arrangements to save money, Utilize benefits from charities]

Data Availability

Data are publicly available from sources provided in the manuscript.