Abstract
Objectives. To describe food insecurity in the United States in December 2020 and examine associations with underuse of medical care during the COVID-19 pandemic.
Methods. We fielded a nationally representative Web-based survey in December 2020 (n = 8318). Multivariable logistic regression models and predicted probabilities were used to evaluate factors associated with food insecurity and compare the likelihood of delaying or forgoing medical care because of cost concerns by food security status.
Results. In December 2020, 18.8% of US adults surveyed reported experiencing food insecurity. Elevated odds of food insecurity were observed among non-Hispanic Black, Hispanic, and low-income respondents. Experiencing food insecurity was significantly associated with a greater likelihood of forgoing any type of medical care as a result of cost concerns.
Conclusions. Food insecurity during the COVID-19 pandemic disproportionately affected non-White and low-income individuals. Experiencing food insecurity was a significant risk factor for delaying or forgoing medical care, an association that could have cumulative short- and long-term health effects.
Public Health Implications. Comprehensive policies that target the most at-risk groups are needed to address the high rates of food insecurity in the United States and mitigate its adverse health effects. (Am J Public Health. 2022;112(5):776–785. https://doi.org/10.2105/AJPH.2022.306724)
The COVID-19 pandemic has quickly become one of the most profound public health crises of modern times. Since the first reported COVID-19 infection in the United States in January 2020, the virus has resulted in more than 43 million infections and 700 000 deaths across the country (as of October 1, 2021).1 Throughout the pandemic, burdens on the health care system caused by overcrowded emergency rooms, insufficient medical staff, and efforts to prevent COVID-19 transmission have led to delays in medical procedures and rationing of care.2
In addition to the direct impact the pandemic has had on morbidity and mortality in the United States, COVID-19 also created significant economic challenges that have threatened the health and livelihoods of people across the country. Economic shutdowns caused by COVID-19 resulted in increasing unemployment rates, from 3.6% in December 2019 (before the first case of COVID-19 was reported in the United States) to as high as 14.8% during the first wave of COVID-19 cases in April 2020.3 Early reports indicated that, by April 2020, 43% of adults in the United States had lost a job or a portion of their income because of the COVID-19 pandemic. The significant health and economic effects of the pandemic have been especially devastating for US racial and ethnic minority groups, with rates of job or income loss because of the pandemic4 and COVID-19--related hospitalizations and deaths being disproportionately higher among non-Hispanic Black and Hispanic Americans than among Whites.5
Food insecurity, defined by the US Department of Agriculture (USDA) as “limited or uncertain availability of nutritionally adequate and safe foods, or limited or uncertain ability to acquire acceptable foods in socially acceptable ways,”6 is strongly connected to income and disproportionately affects non-Hispanic Black and Hispanic households.7–9 Food insecurity is also associated with numerous adverse health effects including a greater likelihood of chronic medical conditions,10 psychological distress,11,12 cost-related medication and health care underuse,13 and poor disease management.14,15
Despite earlier surveys suggesting a sharp rise in food insecurity in the United States during the first year of the COVID-19 pandemic,16,17 the USDA’s report on household food security in the United States in 20207 showed that the overall prevalence of food insecurity during the pandemic had remained stable at 10.5%, unchanged from 2019. However, the report did reveal that food insecurity had increased significantly in certain household subgroups such as non-Hispanic Black households (from 19.1% in 2019 to 21.7% in 2020), and food insecurity was significantly higher in households in which a reference person identified as being non-Hispanic Black or Hispanic, having a low income, or being unable to work because of the pandemic.
Food insecurity can directly harm health by creating nutritional deficiencies or promoting intake of cheap, heavily processed foods that have been associated with a greater likelihood of developing certain chronic diseases.10 Another pathway by which food insecurity can contribute to negative health outcomes is by forcing people to choose between buying food to eat and affording medical care.13
The relationship between food insecurity and cost-related medical care underuse has been well documented13,18 but may be especially important to examine during the pandemic, when insufficient medical care use might contribute to exacerbation of chronic health conditions that have been strongly associated with hospitalizations and deaths caused by COVID-19.5,19 In addition, although the longer-term health effects of food insecurity experienced during the pandemic may take years to observe, conceptual models and prior evidence suggest that these effects could contribute to a greater burden of chronic disease, increased stress and mental health challenges, and widening health disparities among low-income and minority households well beyond the pandemic.16,20
In this study, we sought to describe patterns of food insecurity in the United States in December 2020 and to evaluate associations between food insecurity and delaying or forgoing medical care as a result of cost concerns. Data were collected as part of the Johns Hopkins Pandemic Pulse project, in which multiple cross-sectional surveys have been conducted during the pandemic to measure inequities and health effects related to COVID-19. The December 2020 wave was the first in which food insecurity was assessed.
Previous evidence suggests there may be longer-term health and economic effects of the COVID-19 pandemic,21,22 and food insecurity could be a critical early indicator of populations at risk for worse health outcomes. Therefore, understanding who is at most risk of experiencing food insecurity and identifying how food insecurity is affecting use of medical care during the pandemic are important in better directing public health policies and programs. To our knowledge, this is the first study of its kind to examine the relationship between food insecurity and delaying or forgoing medical care because of cost concerns amid the COVID-19 pandemic in a large, nationally representative US sample.
METHODS
We fielded a nationally representative Web-based survey in partnership with Dynata, a first-party data platform that maintains a panel of 62 million users. Dynata panels have been used previously to conduct state- and nationally representative surveys.23 The survey participants, who were randomly selected from a nationally representative group of adults (aged 18 years or older) living in the United States, were recruited by Dynata via e-mail. The sample was matched to the 2019 US census with respect to age, race, gender, income, and census division. The survey was fielded from December 15 to 23, 2020, and yielded 10 107 responses. A total of 8481 respondents provided consent and completed the survey. Respondents were compensated by Dynata for completing the survey. We reviewed responses with incomplete or missing data for our primary indicators and excluded participants who refused to indicate whether they had lost a job or more than 50% of their income during the pandemic (n = 128) and those who identified their gender as “other” (n = 35). Our final sample consisted of 8318 participants.
Measures
We used the USDA’s Household Food Security Module 6-item short form to assess adult food security status in the preceding 30 days. This scale derives a sum score, based on the number of affirmative responses to the 6 food security questions, that corresponds to 1 of 3 levels of food security: high or marginal (raw score = 0–1), low (raw score = 2–4), and very low (raw score = 5–6).24 Adults with low or very low food security were classified as food insecure. Evidence suggests that Internet-based surveys can overestimate food insecurity,25 so we employed an income screen as part of our food insecurity measure. We were unable to screen based on federal poverty level; thus, consistent with methods described in prior literature,26 we classified households with incomes above $50 000 as food secure regardless of how they responded to the food security questions. This income threshold was selected because it approximates 185% of the federal poverty level for a household of 4 and has been shown in earlier literature to produce consistent, if slightly conservative, food security estimates relative to estimates that include a federal poverty level screen.26
Cost-related medical care effects were assessed by asking participants whether they had delayed any type of medical care because of cost concerns in the past month and whether they had skipped or delayed specific types of medical care (e.g., filling a medical prescription) since the beginning of the pandemic. We included covariates that might be associated with food insecurity and cost-related medical care effects such as sex, race/ethnicity, age, education, current employment status, income, number of chronic health conditions, health insurance coverage, state of residence, and loss of a job or more than 50% of one’s income as a result of COVID-19.13,27,28
Statistical Analysis
Post hoc survey weights for age and race/ethnicity by census division were generated from the 2019 US census and applied to our sample to produce nationally representative estimates. We used weighted cross tabulations and the χ2 test to describe unadjusted characteristics of the survey sample overall and by food security status. We then used multivariable logistic regression to estimate associations between the covariates just mentioned and food insecurity. To examine the effect of food insecurity on delaying or forgoing medical care, we created multivariable logistic regression models adjusted for the included covariates to estimate the odds of delaying or forgoing any medical care in the preceding month and experiencing each type of cost-related medical care outcome at any point during the pandemic; in our analyses, we compared people classified as food insecure with those who were food secure.
Post-estimation margins were used to generate predicted probabilities of delaying or forgoing medical care because of cost concerns among those with food insecurity versus those who were food secure. Stata version 16.1 (StataCorp LP, College Station, TX) was used in conducting our analyses. All tests were 2-sided, and the significance level was set at a P level of less than .05.
RESULTS
Weighted descriptive characteristics of the study sample by adult food insecurity status are shown in Table 1. Overall, we found that in December 2020 18.8% of US adults had experienced food insecurity in the preceding 30 days, with 8.7% experiencing low food security and 10.1% experiencing very low food security. Adults with food insecurity were more likely to be non-Hispanic Black or Hispanic, to be younger, to have a low income, to lack health insurance, to have 2 or more chronic medical conditions, to be working part time, to be unemployed, and to have COVID-19 job or income disruptions (all Ps < .001).
TABLE 1—
Weighted Characteristics of the Study Sample, Overall and by Adult Food Insecurity Status: United States, 2020
| Overall, No.a (%) | High/Marginal Food Security, No.a (%) | Low Food Security, No.a (%) | Very Low Food Security, No.a (%) | P | |
| Total | 8318 (100.0) | 6665 (100.0) | 782 (100.0) | 850 (100.0) | |
| Sex | < .001 | ||||
| Male | 4127 (48.6) | 3553 (50.6) | 286 (43.4) | 278 (36.8) | |
| Female | 4191 (51.4) | 3112 (49.4) | 496 (56.6) | 572 (63.2) | |
| Race/ethnicity | < .001 | ||||
| Non-Hispanic White | 5123 (63.5) | 4420 (67.2) | 293 (42.5) | 399 (51.9) | |
| Non-Hispanic Black | 1100 (11.8) | 706 (9.9) | 213 (22.8) | 173 (17.2) | |
| Hispanic | 1412 (16.4) | 992 (14.7) | 202 (24.4) | 216 (22.9) | |
| Otherb | 683 (8.3) | 547 (8.2) | 74 (10.3) | 62 (8.1) | |
| Age, y | < .001 | ||||
| 18–24 | 1094 (11.7) | 630 (8.6) | 268 (30.0) | 186 (19.5) | |
| 25–34 | 1312 (17.9) | 921 (16.0) | 187 (26.5) | 203 (26.1) | |
| 35–44 | 1472 (16.4) | 1192 (16.1) | 114 (15.2) | 162 (19.7) | |
| 45–54 | 1563 (16.1) | 1269 (16.0) | 116 (13.9) | 176 (18.9) | |
| 55–64 | 1383 (16.5) | 1213 (17.9) | 70 (9.7) | 98 (11.6) | |
| ≥ 65 | 1494 (21.4) | 1440 (25.4) | 27 (4.9) | 25 (4.1) | |
| Education | < .001 | ||||
| High school or less | 1630 (19.9) | 997 (15.4) | 298 (38.7) | 325 (38.4) | |
| Associate degree | 894 (10.7) | 656 (9.7) | 129 (16.8) | 109 (13.0) | |
| Some college | 1649 (20.0) | 1189 (18.3) | 191 (23.6) | 263 (31.2) | |
| Bachelor’s degree | 2408 (29.1) | 2187 (32.9) | 115 (14.9) | 104 (12.2) | |
| Graduate degree | 1737 (20.3) | 1636 (23.7) | 49 (6.0) | 49 (5.3) | |
| Current employment status | < .001 | ||||
| Working full-time | 3808 (43.9) | 3297 (46.9) | 238 (31.0) | 263 (31.0) | |
| Working part-time or hours reduced | 956 (11.2) | 647 (9.6) | 164 (20.1) | 144 (16.2) | |
| Unemployed, seeking work, or furloughed | 628 (7.5) | 331 (4.9) | 130 (17.2) | 164 (19.7) | |
| Out of labor force | 2926 (37.4) | 2390 (38.6) | 250 (31.6) | 279 (33.1) | |
| Lost job or > 50% of income because of COVID-19 | 1792 (21.2) | 1038 (15.3) | 285 (37.9) | 464 (54.3) | < .001 |
| Income, $ | < .001 | ||||
| < 10 000 | 661 (7.6) | 216 (3.1) | 199 (25.3) | 246 (28.2) | |
| 10 000–29 999 | 1265 (15.4) | 606 (9.6) | 314 (39.9) | 345 (41.2) | |
| 30 000–49 999 | 1250 (15.4) | 783 (12.2) | 234 (30.7) | 233 (27.6) | |
| 50 000–69 999 | 1046 (13.2) | 1046 (16.3) | . . . | . . . | |
| 70 000–99 999 | 1335 (16.3) | 1335 (20.1) | . . . | . . . | |
| 100 000–149 999 | 1332 (16.0) | 1332 (19.8) | . . . | . . . | |
| ≥ 150 000 | 986 (11.0) | 986 (13.5) | . . . | . . . | |
| Not reported | 430 (5.1) | 360 (5.4) | 35 (4.1) | 26 (3.0) | |
| US region | .02 | ||||
| Midwest | 1741 (21.5) | 1389 (21.2) | 158 (21.6) | 190 (23.3) | |
| Northeast | 1513 (18.6) | 1267 (19.3) | 112 (15.2) | 127 (16.0) | |
| South | 3112 (36.7) | 2436 (36.2) | 337 (41.4) | 334 (37.6) | |
| West | 1952 (23.2) | 1573 (23.4) | 175 (21.8) | 199 (23.1) | |
| No. of chronic medical conditions | .1 | ||||
| 0 | 5036 (60.5) | 4084 (61.0) | 469 (58.9) | 483 (57.2) | |
| 1 | 2113 (25.5) | 1678 (25.2) | 209 (27.5) | 226 (26.1) | |
| ≥ 2 | 1148 (14.1) | 903 (13.8) | 104 (13.6) | 141 (16.8) | |
| Health insurance coverage | < .001 | ||||
| Private | 4218 (49.2) | 3753 (54.0) | 223 (28.3) | 242 (28.7) | |
| Public | 2736 (35.2) | 2107 (34.2) | 248 (32.8) | 381 (44.8) | |
| No coverage | 1004 (11.7) | 591 (8.8) | 236 (29.5) | 173 (20.1) | |
| Don’t know or refused to answer | 343 (3.9) | 214 (3.0) | 75 (9.4) | 54 (6.4) |
Weighted to produce nationally representative estimates.
American Indian or Alaska Native, Asian or Pacific Islander, prefer not to say, or other (all other races/ethnicities not stated).
The prevalence of medical care underuse differed according to food insecurity status (Table 2). Overall, 7.4% of people reported that they had delayed or skipped some type of medical care in the past month because of cost concerns, but this percentage was substantially higher among those with low (11.6%) and very low (15.8%) food security (P < .001). Delaying dental care (18.2%) was the most prevalent of the other cost-related medical care effects experienced during the pandemic; however, skipping a prescription (8.8%), medical test (8.8%), or doctor-recommended treatment (9.9%) or follow-up (9.1%) and not seeing a doctor (9.1%) or specialist (6.1%) when a medical problem warranted it were reported as well.
TABLE 2—
Prevalence of Medical Care Underuse Because of Cost Concerns, Overall and by Adult Food Insecurity Status: United States, 2020
| Overall, No.a (%) | High/Marginal Food Security, No.a (%) | Low Food Security, No.a (%) | Very Low Food Security, No.a (%) | P | |
| Total | 8318 (100.0) | 6665 (100.0) | 782 (100.0) | 850 (100.0) | |
| Delayed any medical care in past month | 628 (7.4) | 400 (5.9) | 92 (11.6) | 136 (15.8) | < .001 |
| Skipped filling a medical prescription | 759 (8.8) | 461 (6.6) | 127 (16.2) | 171 (20.0) | < .001 |
| Skipped a medical test recommended by a doctor | 757 (8.8) | 538 (7.8) | 140 (17.2) | 173 (20.5) | < .001 |
| Skipped a treatment recommended by a doctor | 853 (9.9) | 473 (6.9) | 140 (17.9) | 142 (16.6) | < .001 |
| Skipped a follow-up recommended by a doctor | 784 (9.1) | 511 (7.4) | 102 (12.9) | 169 (19.8) | < .001 |
| Had a medical problem but did not go to a doctor or a clinic | 785 (9.1) | 455 (6.6) | 120 (14.4) | 209 (24.5) | < .001 |
| Did not see a specialist when you or your doctor thought you needed one | 522 (6.1) | 311 (4.6) | 78 (9.6) | 133 (15.6) | < .001 |
| Delayed or did not get dental care | 1529 (18.2) | 1053 (15.6) | 169 (21.9) | 306 (36.5) | < .001 |
| Delayed or did not get vision care | 900 (10.9) | 580 (8.7) | 124 (16.4) | 194 (23.8) | < .001 |
Weighted to produce nationally representative estimates.
The adjusted logistic regression model for food insecurity status (Table 3) identified several factors associated with greater odds of food insecurity. Respondents identifying as non-Hispanic Black (odds ratio [OR] = 1.92; 95% confidence interval [CI] = 1.57, 2.36; P < .001), Hispanic (OR = 1.53; 95% CI = 1.26, 1.86; P < .001), or a member of another racial/ethnic group (OR = 1.56; 95% CI = 1.19, 2.05; P = .001) had significantly higher odds of experiencing food insecurity than non-Hispanic White respondents. The odds of experiencing food insecurity were greatest among those in the youngest age group (18–24 years; OR = 14.12; 95% CI = 9.70, 20.55; P < .001) and decreased for each subsequent age category.
TABLE 3—
Adjusted Adult Food Insecurity Status Logistic Model: United States, 2020
| OR (95% CI) | |
| Sex | |
| Male (Ref) | 1 |
| Female | 1.67 (1.44, 1.93) |
| Race/ethnicity | |
| Non-Hispanic White (Ref) | 1 |
| Non-Hispanic Black | 1.92 (1.57, 2.36) |
| Hispanic | 1.53 (1.26, 1.86) |
| Othera | 1.56 (1.19, 2.05) |
| Age, y | |
| 18–24 | 14.12 (9.70, 20.55) |
| 25–34 | 11.08 (7.64, 16.07) |
| 35–44 | 9.08 (6.25, 13.20) |
| 45–54 | 8.09 (5.63, 11.61) |
| 55–64 | 4.52 (3.12, 6.55) |
| ≥ 65 (Ref) | 1 |
| Education | |
| High school or less | 5.41 (4.09, 7.14) |
| Associate degree | 4.17 (3.06, 5.68) |
| Some college | 3.87 (2.93, 5.10) |
| Bachelor’s degree | 1.50 (1.14, 1.99) |
| Graduate degree (Ref) | 1 |
| Employment | |
| Working full time (Ref) | 1 |
| Working part time or hours reduced | 1.31 (1.04, 1.64) |
| Unemployed, seeking work, or furloughed | 1.70 (1.34, 2.15) |
| Out of labor force | 1.26 (1.04, 1.52) |
| Lost job or > 50% of income because of COVID-19 | |
| No (Ref) | 1 |
| Yes | 3.50 (3.00, 4.09) |
| No. of chronic medical conditions | |
| 0 (Ref) | 1 |
| 1 | 1.39 (1.18, 1.65) |
| ≥ 2 | 1.51 (1.22, 1.86) |
| Health insurance coverage | |
| Private (Ref) | 1 |
| Public | 2.76 (2.30, 3.31) |
| No coverage | 2.61 (2.13, 3.20) |
| Don’t know or refused to answer | 1.91 (1.40, 2.60) |
Note. CI = confidence interval; OR = odds ratio. The logistic model of adult food insecurity (low or very low food security vs high or marginal food security) adjusted for sex, race/ethnicity, age, education, employment status, loss of job or income because of COVID-19, number of chronic medical conditions, health insurance status, and state of residence. Data were weighted to produce nationally representative estimates.
American Indian or Alaska Native, Asian or Pacific Islander, prefer not to say, or other (all other races/ethnicities not stated).
Lower educational attainment, being unemployed or furloughed, and having lost a job or more than 50% of one’s income because of COVID-19 were also associated with greater odds of experiencing food insecurity. In addition, the odds of food insecurity were greater among those with 2 or more chronic medical conditions (OR = 1.51; 95% CI = 1.22, 1.86; P < .001) and those with public health insurance (OR = 2.76; 95% CI = 2.30, 3.31; P < .001) or no health insurance (OR = 2.61; 95% CI = 2.13, 3.20; P < .001).
Table 4 shows adjusted odds and predictive probabilities of delaying or forgoing different types of medical care because of cost among adults experiencing food insecurity and those with food security. Experiencing food insecurity significantly increased a person’s odds of having delayed any type of medical care in the past 30 days (OR = 2.17; 95% CI = 1.52, 3.12; P < .001) because of cost concerns. Those experiencing food insecurity were also significantly more likely to have skipped or delayed medical care because of cost at any point between March and December 2020.
TABLE 4—
Adjusted Odds and Predictive Probabilities of Delaying or Forgoing Medical Care Because of Cost Concerns Among Adults Experiencing Food Insecurity (FI) and Adults With Food Security (FS): United States, 2020
| No.a | OR (95% CI) | Probability (FS), %b | Probability (FI), %c | |
| Delayed any medical care in past month | 628 | 2.17 (1.52, 3.12) | 6.2 | 11.5 |
| Skipped filling a medical prescriptiond | 759 | 2.96 (2.09, 4.20) | 6.9 | 15.2 |
| Skipped a medical test recommended by a doctord | 757 | 3.28 (2.39, 4.49) | 7.8 | 19.4 |
| Skipped a treatment recommended by a doctord | 853 | 3.50 (2.48, 4.94) | 6.8 | 17.9 |
| Skipped a follow-up recommended by a doctord | 784 | 2.27 (1.69, 3.05) | 7.6 | 14.9 |
| Had a medical problem but did not go to a doctor or a clinicd | 785 | 2.54 (1.92, 3.36) | 7.1 | 15.5 |
| Did not see a specialist when you or your doctor thought you needed oned | 522 | 2.58 (1.82, 3.65) | 4.8 | 11.1 |
| Delayed or did not get dental cared | 1529 | 1.81 (1.49, 2.20) | 8.9 | 18.9 |
| Delayed or did not get vision cared | 900 | 2.47 (1.92, 3.19) | 16.3 | 25.6 |
Note. CI = confidence interval; OR = odds ratio. Logistic models of delaying or forgoing medical care (yes or no) adjusted for food security status, sex, race/ethnicity, age, education, employment status, income, loss of job or income because of COVID-19, number of chronic medical conditions, health insurance status, and state of residence.
Number of adults in sample responding yes.
Post-estimation predicted marginal probability among individuals with high or marginal food security.
Post-estimation predicted marginal probability among individuals with food insecurity (low or very low food security).
At any point during March through December 2020.
In addition, individuals with food insecurity had higher odds of skipping a medical prescription (OR = 2.96; 95% CI = 2.09, 4.20; P < .001); skipping a doctor-recommended medical test (OR = 3.28; 95% CI = 2.39, 4.49; P < .001), treatment (OR = 3.50; 95% CI = 2.48, 4.94; P < .001), or follow-up (OR = 2.27; 95% CI = 1.69, 3.05; P < .001); having a medical problem but not going to a doctor or a clinic (OR = 2.54; 95% CI = 1.92, 3.36; P < .001); not going to a doctor-recommended specialist (OR = 2.58; 95% CI = 1.82, 3.65; P < .001); and delaying or skipping dental care (OR = 1.81; 95% CI = 1.49, 2.20; P < .001) or vision care (OR = 2.47; 95% CI = 1.92, 3.19; P < .001). Individuals experiencing food insecurity were more likely than those with food security to have forgone any type of medical care in the preceding 30 days or at any point during the pandemic. Those experiencing food insecurity were most likely to delay or skip dental care (25.6%), skip a doctor-recommended medical test (19.4%), delay or skip vision care (18.9%), or skip a doctor-recommended treatment (17.9%).
DISCUSSION
The results of our nationally representative, cross-sectional survey show that, amid the COVID-19 pandemic in December 2020, food insecurity disproportionately affected racial/ethnic minority and low-income populations. Furthermore, we found that adults experiencing food insecurity were significantly more likely than their food-secure counterparts to delay or forgo medical care because of cost concerns. In contrast with the most recent USDA household food security report,29 according to which the prevalence of household food insecurity in 2020 was 10.5% (unchanged from 2019), we estimated that 18.8% of US adults experienced food insecurity in December 2020. This difference in estimates could be due to differing food insecurity measurement units (adult vs household food insecurity), survey methodologies (online 6-item survey vs 10 questions fielded via interviews), and time frames (experiences in the past month vs over an entire year).
Both the USDA report and our study reaffirm that food insecurity is unevenly distributed in the United States, with adults and household reference persons who identify as non-Hispanic Black or Hispanic and as having a low income being more likely to experience food insecurity. Food insecurity is closely tied to economic indicators, and previous work has shown that economic shocks can cause food insecurity to rise.30 In this study, we found that losing a job or at least 50% of one’s income during the pandemic was associated with significantly greater odds of food insecurity. There is evidence that the groups with the highest odds of food insecurity in our study—namely, members of minority groups, younger people, and low-income individuals—are also most likely to lose a job or income because of COVID-19.4 This suggests that the disproportionate effects of the COVID-19 pandemic on these populations could have significant economic and public health consequences.
Data from early in the pandemic suggest that approximately 2 in 5 US adults reported forgoing medical care between March and mid-July 202031; to our knowledge, however, ours is the first study to explore the association between food insecurity and underuse of medical care during the COVID-19 pandemic specifically because of cost concerns. Even after adjustment for several demographic, economic, and health-related variables, food insecurity was associated with significantly higher odds of delaying one or more forms of medical care.
The relationship between food insecurity and delaying or forgoing medical care is multilevel, with overlapping pathways that tend to be mutually reinforcing.16 The overarching driver of health consequences related to food insecurity is the significant economic constraints that underlie its presence, which can limit resources available to access nutritionally appropriate diets,10,30 contribute to stress and poor mental health,12 and force people to make difficult decisions between affording food and medical care.13 The impact of food insecurity on medical care use may have been further compounded during the COVID-19 pandemic as millions of people in the United States lost their jobs and incomes, medical systems were repeatedly strained owing to the influx of COVID-19 patients, and disruptions in the food supply chain left grocery stores bare and food assistance programs scrambling to meet rapidly growing demand.16
Unlike other reasons for delaying or forgoing medical care during the pandemic, such as deprioritizing nonessential procedures or fear of contracting COVID-19, experiencing food insecurity could lead to trade-offs that increase the risk of developing chronic diseases and result in poorer disease management well beyond the pandemic.16 Because the economic recovery from COVID-19 may take many years, the long-term health consequences of food insecurity brought on by the pandemic deserve careful consideration to avoid and mitigate distal worsening of chronic disease outcomes, particularly among socioeconomically disadvantaged populations.
Efforts to alleviate food insecurity in response to the COVID-19 pandemic must address the immediate need to provide adequate nourishment to at-risk individuals and households while also incorporating longer-term strategies that more comprehensively cope with systemic factors that limit access to basic needs such as food and contribute to health disparities among people of color and other groups that have been marginalized. In the early months of the pandemic, the Supplemental Nutrition Assistance Program (SNAP) quickly expanded its caseload by more than 6 million, and food banks scrambled to meet unprecedented demand.17
The American Rescue Plan increased federal contributions to unemployment benefits and increased access to SNAP as well as SNAP benefit amounts.32 Although these policy changes were temporary, the Thrifty Food Plan, on which SNAP benefits are based, was also recently revised by the USDA, with SNAP benefits being permanently increased by an average of 27% above prepandemic levels.33 These new higher benefit levels are an important step in addressing food insecurity, but more research is needed to understand the impact of such policies, especially in the context of rising prices and cost of living. It is critical that government and public health agencies increase opportunities for people to access food assistance and free meals, for example by continuing to support expanded access to SNAP, increasing funding for public schools and community colleges to provide free meals to families in need, and connecting farm surplus areas with low-income communities.
Ensuring access to affordable medical care and high-quality and affordable health insurance is also essential to addressing potential trade-offs between food and medical care that households experiencing food insecurity may make. Access to health insurance is a key factor in decreasing the burden of health care costs, and thus it is critical to increase access to Medicaid, particularly in states that have not yet chosen to expand Medicaid. Investigating the effects of Medicaid expansion on food insecurity and delaying or forgoing medical care because of cost concerns may be a fruitful area for future research.
A small but growing number of politicians have endorsed the idea of providing some form of guaranteed income for US families,34 which could help offset the cost of healthy food and other basic needs. Policymakers and public health advocates must also recognize that persistent disparities in food insecurity in the United States are rooted in structural racism,9 and an intensified focus is needed to more holistically address oppression and discrimination that socially and economically disadvantage people of color. Our results suggest that adequately addressing food insecurity now and investing in more comprehensive and equitable approaches to improving access to healthy, affordable food among those most at risk can have substantial benefits for public health in the pandemic and beyond, as trade-offs between food and medical needs can be avoided.
Limitations
The limitations of this study include its cross-sectional design, which prevented us from determining causation or measuring the cumulative effects of food insecurity on cost-related medical care outcomes at different points in the pandemic. Food insecurity was measured in the past 30 days; however, measures of delaying specific types of medical care referred to any point during the pandemic, which may have overestimated the odds of the effects because they could have preceded the onset of food insecurity. Although we were able to control for many measures commonly associated with experiencing food insecurity and delaying medical care, other competing factors that could be associated with food insecurity and medical care use, such as housing stability, household size, child care, living arrangements, and other financial support, were not measured in this study.
Using online surveys to measure food insecurity also has limitations, including the tendency to overestimate food insecurity prevalence25 and differences in how younger adults may interpret and respond to food insecurity questions.35 However, the income screening approach could potentially misclassify food security status and underestimate the prevalence of food insecurity in our sample, especially among respondents living in locations with higher costs of living.
In addition, all our measures were self-reported and could be subject to recall bias and social desirability bias. The survey required a computer or smart phone, which could have excluded respondents with lower incomes or those who were less tech savvy. The survey was also conducted in English only and thus excluded non-English-speaking respondents. Both latter factors could have led to underestimates of food insecurity and low representation among groups at higher risk of food insecurity.
Public Health Implications
In this study, we examined sociodemographic factors associated with food insecurity in December 2020, 9 months after the start of the COVID-19 pandemic in the United States. We also assessed the ways in which experiencing food insecurity was associated with increased odds of delaying or forgoing needed medical care during the pandemic. Understanding more about the populations most at risk for food insecurity and potential effects on health care use can assist policymakers in generating more targeted and effective solutions to reduce food insecurity and mitigate its adverse health impacts over the short and long term, especially among groups that have been marginalized.
ACKNOWLEDGMENTS
This work was supported by the Johnson & Johnson Foundation COVID Inequities Project (principal investigator: A. Labrique). S. M. Sundermeir is supported by a National Institutes of Health T32 training grant (award T32DK062707). J. A. Wolfson is supported by the National Institutes of Diabetes and Digestive and Kidney Diseases (award K01DK119166).
Note. The funder had no role in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; the preparation or review of the article; or the decision to submit the article for publication.
CONFLICTS OF INTEREST
The authors have no conflicts of interest to disclose.
HUMAN PARTICIPANT PROTECTION
This study was approved by the institutional review board of the Johns Hopkins Bloomberg School of Public Health. Participants provided informed consent via a question at the beginning of the survey.
POST PUBLICATION UPDATE
5/23/22: When originally published, the categories in Table 1 and Table 2 listed “Food Insecurity” instead of “Food Security” for the “High/Marginal,” “Low,” and “Very Low” categories. An erratum has since been issued indicating the change. This PDF has been updated to include the correction.
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