HIGHLIGHTS
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This study analyzed nationally representative cross-sectional data in the U.S.
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Food insecurity unequally affected socioeconomically disadvantaged populations.
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Food insecurity was independently associated with positive COVID-19 infection.
Keywords: Food insecurity, COVID-19 infection, National Health Interview Survey, disparities
Abstract
Introduction
The purpose of this study was to examine the sociodemographic and health-related factors associated with food insecurity and the association between food insecurity and COVID-19 infection using a nationally representative sample in the U.S.
Methods
Cross-sectional data of 61,050 adults (aged ≥18 years) from the 2020 and 2021 National Health Interview Survey were analyzed. Food insecurity was measured by the 10-item U.S. Department of Agriculture Food Security Survey Module. Weighted multivariable logistic regression models were used to estimate associations with food insecurity.
Results
A total of 6.8% of the National Health Interview Survey participants lived in food-insecure households, and 18.9% tested positive for COVID-19 infection. Young (aged 18–34 years) or middle (aged 35–64 years) age, female sex, minor race/ethnicity (Hispanic/non-Hispanic Black/non-Hispanic Asian/others), education level less than high school, unmarried status, unemployment, poverty (below the federal poverty level), having no health insurance, a larger number of adults and children in the household, poorer self-reported health status, and the presence of chronic conditions were significantly associated with food insecurity (AOR ranged from 1.20 to 3.15, all p<0.0001). Food insecurity was independently associated with positive COVID-19 infection (AOR=1.25, 95% CI=1.11, 1.40), controlling for sociodemographic and health-related factors. The greatest magnitude of the association was observed for the non-Hispanic Black participants (AOR=1.47, 95% CI=1.15, 1.88), female participants (AOR=1.44, 95% CI=1.20, 1.71), and those below the federal poverty level (AOR=1.39, 95% CI=1.12, 1.73) across all the subgroups.
Conclusions
Food insecurity disproportionately affected vulnerable subgroups such as young adults, female individuals, minority race/ethnicity groups, and those with lower socioeconomic status, and was associated with positive COVID-19 infection. Policies addressing food insecurity may help to reduce the likelihood of COVID-19 infection, especially for those vulnerable subgroups.
INTRODUCTION
Food insecurity, measured by the U.S. Department of Agriculture (USDA), is characterized by limited or uncertain access to adequate food.1 The unprecedented coronavirus disease 2019 (COVID-19) pandemic that began in 2020 in the U.S. and its associated economic and social impacts (e.g., high rates of unemployment, stay-at-home orders, closures of schools and businesses) have contributed to increased food insecurity at the beginning of the pandemic and may have the potential to exacerbate the existing disparities in food insecurity.2 The national estimate of household food insecurity has risen from 11% to 38.3% in March 2020.3 On the basis of reports from USDA, 10.5% (13.8 million) of all U.S. households were food insecure at least some time in 2020.4 Although the prevalence of food insecurity for all households in 2020 remained unchanged from that of 2019, subgroups such as households with children and households with Black members experienced increases in food insecurity since the pandemic's onset.4 Significantly higher prevalence of food insecurity than the national average (10.5%) was observed in subgroups such as female-headed households (27.7%), households with children (14.8%), households with Hispanic (17.2%) or non-Hispanic Black persons (21.7%), households with unemployed members (20.4%), and low-income households (28.6%).4 Younger adults were also vulnerable to food insecurity during the pandemic (e.g., the RR of food insufficiency [often the most extreme form of food insecurity] decreased by 23% with every 10-year increase in age).5
Food insecurity has been linked to adverse health outcomes such as diabetes, cardiovascular disease, and mental problems such as anxiety and depression disorders.6,7 Food-insecure adults may also be more vulnerable to COVID-19 infection than their food-secure counterparts owing to weakened immune function and less engagement in COVID-19−protective behaviors. Poorer diet quality and inadequate nutrients associated with food insecurity could contribute to an impaired immune system, which may increase the susceptibility to virus infection and permit severer symptoms.8,9 Besides, food-insecure individuals were less likely to work from home, practice physical distancing in public, and take preventive actions to reduce their exposure to COVID-19 (e.g., stocking up on essentials at a grocery store or pharmacy, washing hands more regularly, filling prescriptions, avoiding crowds or a larger gathering, and avoiding touching face) than food-secure individuals.10 So far, only 1 cross-sectional study has reported that household food insecurity was associated with a 32%–73% greater likelihood of COVID-19 infection, but the evidence was limited to older U.S. adults (aged ≥50 years) from a random subsample of Health and Retirement Study.11 Few studies have focused on the association between food insecurity and COVID-19 infection in the overall U.S. population and communities that are vulnerable to food insecurity such as young adults, female people, unemployed people, and households with children.
Using the nationally representative data from the 2020 and 2021 National Health Interview Survey (NHIS), this study aimed to examine (1) the sociodemographic and health-related factors associated with food insecurity during the COVID-19 pandemic and (2) the association between food insecurity and COVID-19 infection in the overall U.S. adults (aged ≥18 years) and subgroups vulnerable to food insecurity, including young people (aged 18–34 years), female individuals, Hispanic and non-Hispanic Black persons, low-income households, households with children, and unemployed individuals. Identifying disparities in food insecurity could inform disadvantaged food-insecure communities during the pandemic crisis. Understanding the association between food insecurity and COVID-19 infection may provide new insights into the prevention and management of COVID-19 infection.
METHODS
Study Sample
Data used in this study were derived from the 2020 and 2021 NHIS, an ongoing cross-sectional and nationally representative survey that aims to monitor the trends in health, illness, and disability in the U.S. civilian non-institutionalized population. With stratified clustering sampling methods, NHIS randomly selected roughly 30,000 households from the randomly selected clusters within 1,689 originally defined geographic areas. Sample adults were then randomly selected from each household. NHIS collected data on both the household level (such as household demographics and food insecurity) and the individual level (such as health conditions and behaviors, healthcare access and utilization, and functioning and disability). The 2020 and 2021 NHIS also covered COVID-19−related data such as self-reported diagnosis and symptoms of COVID-19 infection. Owing to the impact of the COVID-19 pandemic, the 2020 and 2021 NHIS predominantly collected data using telephone interviews rather than through regular in-person visits, which resulted in relatively low response rates during this period compared with previous years (response rates: 50.7% for sampled households and 48.9% for sampled adults in 2020 NHIS, 52.8% for sampled households, and 50.9% for sampled adults in 2021 NHIS).12 Quality controls were conducted by monthly checks on response or completion rates, item response times or nonresponse, telephone usage rates, and other data quality indicators.
In this study, 61,050 adults (aged ≥18 years) were included. The final analytic sample was weighted with 2-year sampling weights (2-year weight=annual sampling weights/2) to account for complex survey design (clustering and stratification), nonresponse bias, and multiple cycles (weighted n=244,351,834). Details about the survey design, data set, and sampling weights were available on the Center for Disease Control and Prevention website: https://www.cdc.gov/nchs/nhis/data-questionnaires-documentation.htm. IRB review was not required because the study relied on the publicly available data set. Analyses were conducted in 2022.
Measures
Food insecurity was measured by the 10-item USDA Food Security Survey Module with a 30-day look-back window.12,13 Participants were asked questions such as In the past 30 days, did you or others in your family ever cut the size of the meals or skip meals because there was not enough money for food? or In the past 30 days, did you or other adults in your family worry that the food would run out before you got money to buy more? A full list of the 10-item module is provided in Appendix Table 1 (available online). On the basis of the number of affirmative answers, food security status was categorized into 4 levels: high food security (0 item affirmed), marginal food security (1–2 items affirmed), low food security (3–5 items affirmed), and very low food security (6–10 items affirmed).13 Participants with high or marginal food security were considered food secure, and participants with low or very low food security were considered food insecure.13 Self-reported diagnosis of COVID-19 infection was assessed by asking the participants whether they have tested positive for COVID-19 infection.12 Participants who answered yes were considered to have positive COVID-19 infection.
Sociodemographic and health-related factors associated with food insecurity and COVID-19 infection were selected as covariates. Sociodemographic factors included age (18–34 years, 35–64 years, ≥65 years), sex (male, female), race/ethnicity (Hispanic, non-Hispanic White, non-Hispanic Black, and others), education (high school or less, higher than high school), marital status (married, unmarried), employment (no, yes), poverty (<100% federal poverty line, ≥100% federal poverty line), and the number of adults (1–2, ≥3) and children (0, ≥1) in the household. Considering that the presence of chronic conditions was associated with food insecurity and severity or mortality of COVID-19 infection,14,15 we also adjusted for health-related factors, including self-reported health status (good or above, fair or poor) and chronic health conditions (yes, no). Participants were asked whether they have been told by a doctor or other healthcare professionals that they had the following chronic conditions: asthma, chronic obstructive pulmonary disease, arthritis, diabetes, hypertension, coronary heart disease, stroke, and disability.
Statistical Analysis
Characteristics of participants were compared between those with food insecurity and those without using Pearson's chi-square tests. Weighted multivariable logistic regression models were used to estimate associations with food insecurity, controlling for sociodemographic (including age, sex, race/ethnicity, education, marital status, employment, poverty, and the number of adults and children in households) and health-related factors (including self-reported health status and presence of chronic health conditions). AORs with corresponding CIs were reported. To assess the association between food insecurity and COVID-19 infection in vulnerable subgroups, interactions between food insecurity and age, sex, race/ethnicity, unemployment, federal poverty level, and the number of children were added to the adjusted logistic regression model, and the association between food insecurity and COVID-19 infection by age, sex, race/ethnicity, unemployment, federal poverty level, and the number of children was reported additionally. Multiple imputations (imputation number=20) for variables with missing data were conducted using the PROC MI procedure in SAS software.16 Pooled estimates of multiply imputed data were reported. As a sensitivity analysis, we also reported results from data without imputation (Appendix Tables 3 and 4, available online). All analyses were conducted using SAS software (Version 9.4; SAS Institute Inc., Cary, NC).
RESULTS
This study included 61,050 non-institutionalized adults with an average age of 48.1 years. In the weighted sample (n=252,604,899), 6.8% of the participants lived in food-insecure households, and 18.9% tested positive for COVID-19 infection. The prevalence of food insecurity and COVID-19 infection for subgroups was also reported (Appendix Figure 1, available online). Across all the subgroups, the prevalence of food insecurity was highest for participants below the poverty line (24.7%), uninsured participants (15.6%), and non-Hispanic Black participants (13.8%). The prevalence of positive COVID-19 infection was highest for Hispanic participants (27.3%), uninsured participants (26.1%), and those with ≥3 adults in the household (25.5%) among all the subgroups.
Table 1 presents the characteristics of participants by food insecurity. Results of the univariate analyses showed that age, sex, race/ethnicity, education, marital status, employment, federal poverty level, the number of adults and children in the household, self-reported health status, and presence of chronic conditions were significantly associated with food insecurity (all p<0.0001). Results of the adjusted logistic regression models in Table 2 further indicated that young (aged 18–34 years) or middle (aged 35–64 years) age, female sex, minority race/ethnicity (Hispanic/non-Hispanic Black/non-Hispanic Asian/others), education level less than high school, unmarried status, unemployment, federal poverty level, having no health insurance, having a larger number of children in the household, poorer self-reported health status, and presence of chronic conditions were significantly associated with food insecurity (AOR ranged from 1.20 to 3.15, all p<0.001). We also reported the sociodemographic and health-related characteristics of participants by COVID-19 infection status in Appendix Table 2 (available online). Participants with positive COVID-19 infection were more likely to be young (ages 18–34 years) or middle aged (ages 35–64 years), Hispanic, less educated (high school or lower), married, below the federal poverty level, uninsured, having a greater number of adults and children in the household, having poor self-reported health status, and living with chronic conditions (all p<0.05).
Table 1.
Sociodemographic and Health-Related Characteristics of Participants by Food Insecurity, 2020–2021 NHIS Sample
| Variables | Total | Food secure | Food insecure | p-Value |
|---|---|---|---|---|
| Age (years) | ||||
| 18–34 | 29.2 (0.3) | 29.0 (0.3) | 32.6 (1.1) | <0.0001 |
| 35–64 | 40.3 (0.3) | 39.9 (0.3) | 44.9 (1.1) | |
| ≥65 | 30.5 (0.3) | 31.1 (0.3) | 22.5 (0.8) | |
| Sex | ||||
| Male | 48.3 (0.2) | 48.8 (0.3) | 41.6 (1.1) | <0.0001 |
| Female | 51.7 (0.2) | 51.2 (0.3) | 58.4 (1.1) | |
| Race/ethnicity | ||||
| Hispanic | 16.8 (0.7) | 16.3 (0.6) | 25.0 (1.4) | <0.0001 |
| NH White | 62.8 (0.8) | 64.3 (0.8) | 42.7 (1.4) | |
| NH Black | 11.7 (0.4) | 10.9 (0.4) | 23.0 (1.2) | |
| Others | 8.6 (0.4) | 8.5 (0.3) | 9.3 (1.3) | |
| Education | ||||
| High school or lower | 39.3 (0.4) | 37.8 (0.4) | 60.1 (1.1) | <0.0001 |
| Higher than high school | 60.7 (0.4) | 62.2 (0.4) | 39.9 (1.1) | |
| Marital status | ||||
| Married | 51.6 (0.3) | 52.9 (0.3) | 33.5 (1.0) | <0.0001 |
| Unmarried | 48.4 (0.3) | 47.1 (0.3) | 66.5 (1.0) | |
| Employment | ||||
| Yes | 61.6 (0.3) | 62.7 (0.3) | 45.2 (1.1) | <0.0001 |
| No | 38.4 (0.3) | 37.3 (0.3) | 54.8 (1.1) | |
| Federal poverty level | ||||
| <100% | 9.9 (0.2) | 8.1 (0.2) | 35.1 (1.2) | <0.0001 |
| ≥100% | 90.1 (0.2) | 91.9 (0.2) | 64.9 (1.2) | |
| Health insurance | ||||
| Yes | 91.2 (0.3) | 92.0 (0.2) | 80.1 (1.1) | <0.0001 |
| No | 8.8 (0.3) | 8.0 (0.2) | 19.9 (1.1) | |
| Number of children in the household | ||||
| 0 | 67.1 (0.3) | 67.6 (0.3) | 59.9 (1.1) | <0.0001 |
| ≥1 | 32.9 (0.3) | 32.4 (0.3) | 40.1 (1.1) | |
| Number of adults in the household | ||||
| 1–2 | 86.3 (0.3) | 13.8 (0.3) | 13.0 (0.9) | 0.429 |
| ≥3 | 13.7 (0.3) | 86.2 (0.3) | 87.0 (0.9) | |
| Self-reported health status | ||||
| Good or above | 86.3 (0.2) | 87.7 (0.2) | 65.7 (1.0) | <0.0001 |
| Fair or poor | 13.7 (0.2) | 12.3 (0.2) | 34.3 (1.0) | |
| Chronic conditions | ||||
| No | 47.8 (0.3) | 48.3 (0.3) | 40.7 (1.1) | <0.0001 |
| Yes | 52.2 (0.3) | 51.7 (0.3) | 59.3 (1.1) | |
| Positive COVID-19 infection | ||||
| Yes | 18.9 (0.4) | 18.9 (0.4) | 23.1 (1.5) | <0.0001 |
| No | 81.1 (0.4) | 81.1 (0.4) | 76.9 (1.5) |
Note: Values were expressed as % (SEs). All percentages (%) and SEs were calculated on the basis of the weighted sample.
NH, non-Hispanic; NHIS, National Health Interview Survey.
Table 2.
Sociodemographic and Health-Related Factors Associated With Food Insecurity, 2020–2021 NHIS Sample
| Variables | Unadjusted ORa (95% CI) | AORb (95% CI) |
|---|---|---|
| Age (years) | ||
| ≥65 | ref | ref |
| 18–34 | 1.57 (1.39, 1.77) | 2.23 (1.88, 2.64) |
| 35–64 | 1.56 (1.4, 1.73) | 2.14 (1.85, 2.47) |
| Sex | ||
| Male | ref | ref |
| Female | 1.23 (1.47, 1.47) | 1.20 (1.08, 1.32) |
| Race/ethnicity | ||
| NH White | ref | ref |
| Hispanic | 2.32 (2.06, 2.61) | 1.44 (1.25, 1.65) |
| NH Black | 3.26 (2.92, 3.65) | 2.11 (1.85, 2.39) |
| Others | 1.62 (1.25, 2.1) | 1.54 (1.24, 1.92) |
| Education | ||
| >Higher than high school | ref | ref |
| High school or lower | 2.49 (2.28, 2.72) | 1.51 (1.36, 1.66) |
| Marital status | ||
| Married | ref | ref |
| Unmarried | 2.21 (2.01, 2.42) | 1.64 (1.48, 1.82) |
| Employment | ||
| Yes | ref | ref |
| No | 2.06 (1.89, 2.25) | 1.61 (1.44, 1.79) |
| Federal poverty level | ||
| ≥100% | ref | ref |
| <100% | 6.14 (5.56, 6.79) | 3.15 (2.79, 3.55) |
| Health insurance | ||
| Yes | ref | ref |
| No | 2.85 (2.5, 3.24) | 2.00 (1.71, 2.33) |
| Number of adults in the household | ||
| 1–2 | ref | ref |
| ≥3 | 0.93 (0.8, 1.08) | 1.31 (1.10, 1.56) |
| Number of children in the household | ||
| 0 | ref | ref |
| ≥1 | 1.4 (1.28, 1.54) | 1.20 (1.07, 1.36) |
| Self-reported health status | ||
| Good or above | ref | ref |
| Fair or poor | 3.76 (3.43, 4.13) | 2.63 (2.35, 2.95) |
| Chronic conditions | ||
| No | ref | ref |
| Yes | 1.36 (1.24, 1.49) | 1.46 (1.28, 1.66) |
Unadjusted ORs, AORs, and 95% CIs were calculated on the basis of the weighted sample.
The association between each sociodemographic or health-related factor and food insecurity was adjusted for the remaining factors. All the associations were significant at p<0.001.
NH, non-Hispanic; NHIS, National Health Interview Survey.
Table 3 provides the association between food insecurity and COVID-19 infection in the overall population and subgroups. Multicollinearity was checked by correlation coefficients (absolute value of all correlation coefficients<0.31) and values of variance inflation factor (ranged from 1.01 to 1.76, all p<10). Food insecurity was significantly associated with positive COVID-19 infection in the overall population, adjusting for sociodemographic and health-related factors (AOR=1.25, 99% CI=1.11, 1.40). Noticeably, the greatest magnitude of the association was observed for non-Hispanic Black participants (AOR=1.20, 99% CI=1.19, 1.20), female participants (AOR=1.29, 99% CI=1.28, 1.30), and low-income households (below the federal poverty level) (AOR=1.21, 99% CI=1.21, 1.22) across all the groups. However, we did not observe any significant interaction between food insecurity and age, sex, race/ethnicity, employment, federal poverty level, or the number of children.
Table 3.
The Association Between Food Insecurity and COVID-19 Infection Among the Overall Population and Subgroups, 2020–2021 NHIS Sample
| Groups | AORa (95% CI) | Interaction p-valueb |
|---|---|---|
| Overall | 1.25 (1.11, 1.40) | |
| Age (years) | 0.981 | |
| 18–34 | 1.33 (1.06, 1.68) | |
| 35–64 | 1.32 (1.08, 1.61) | |
| ≥65 | 1.29 (1.00, 1.66) | |
| Sex | 0.112 | |
| Male | 1.20 (0.99, 1.46) | |
| Female | 1.44 (1.20, 1.71) | |
| Race/ethnicity | 0.151 | |
| Hispanic | 1.26 (0.99, 1.59) | |
| NH White | 1.08 (0.90, 1.31) | |
| NH Black | 1.47 (1.15, 1.88) | |
| Others | 1.49 (0.99, 2.25) | |
| Employment | 0.945 | |
| Employed | 1.31 (1.08, 1.59) | |
| Unemployed | 1.32 (1.09, 1.59) | |
| Federal poverty level | 0.363 | |
| ≥100% | 1.24 (1.05, 1.46) | |
| <100% | 1.39 (1.12, 1.73) | |
| With children | 0.791 | |
| No | 1.29 (1.05, 1.59) | |
| Yes | 1.34 (1.12, 1.59) |
AORs and 95% CIs were calculated on the basis of the weighted sample. Participants without food insecurity were set as the reference group (AOR=1). Age, sex, race/ethnicity, education, marital status, employment, federal poverty level, the number of adults and children in the household, self-reported health status, and chronic health conditions were adjusted.
p-Value for interactions between food insecurity and age, sex, race/ethnicity, employment, federal poverty level, or the number of children.
NH, non-Hispanic; NHIS, National Health Interview Survey.
DISCUSSION
Overall, 6.8% of the participants lived in food-insecure households, and 18.9% tested positive for COVID-19 infection. Young (aged 18–34 years) or middle (aged 35–64 years) age, female sex, minority race/ethnicity (Hispanic/non-Hispanic Black/non-Hispanic Asian/others), education level less than high school, unmarried status, unemployment, living below the federal poverty level, having no health insurance, having a larger number of adults and children in the household, poorer self-reported health status, and presence of chronic conditions were significantly associated with food insecurity. Food insecurity was independently associated with positive COVID-19 infection, controlling for sociodemographic and health-related factors. The magnitude of the association was greatest for the non-Hispanic Black participants, female participants, and those below the poverty level across all the groups.
Sociodemographic and health-related factors associated with food insecurity highlight vulnerable communities that should be considered when allocating food resources and benefits during the pandemic. Our results were consistent with those of a cross-sectional study that examined sociodemographic disparities in food insufficiency (the most extreme form of food insecurity) during the pandemic (October 2020) with participants from the U.S. Census Household Pulse Survey.5 Although overall food insecurity in the U.S. has improved during the past decades, socially and economically disadvantaged groups such as female, Hispanic, non-Hispanic Black, and low-income populations are still more vulnerable to food insecurity than other groups.17,18 The widespread COVID-19 pandemic that began in 2020 has substantially affected the same disadvantaged populations.19 For example, pandemic-induced unemployment unequally affected employment sectors such as restaurants, public transportation, personal services, and retails, which had a high percentage of young, female, Hispanic, and non-Hispanic Black people, and those with lower socioeconomic status.20 Disrupted food supply chains and food benefits such as the National School Lunch Program and continuously rising food prices also placed vulnerable communities such as households with children at an increased risk of food insecurity.21,22
Food insecurity was associated with positive COVID-19 infection. The results were consistent with those of a cross-sectional study using a random subsample of 3,212 older participants from the Health and Retirement Study. Older adults with household food insecurity had significantly higher odds of reporting positive COVID-19 infection within their households (AOR=1.73, 95% CI=1.03, 2.90) and among their acquaintances (AOR=1.32, 95% CI=1.05, 1.65).11 Besides, we observed the highest magnitude of the association between food insecurity and COVID-19 infection for non-Hispanic Black people, female individuals, and low-income households. Being vulnerable to both food insecurity and COVID-19 infection may account for the relatively higher magnitudes of the association in those subgroups. For example, our data suggested that the prevalence of food insecurity was highest in those below the federal poverty level (24.7%) across all groups and was higher in the non-Hispanic Black (13.8%) and female (7.7%) populations than in the overall population (Appendix Figure 1A, available online). The prevalence of positive COVID-19 infection was also higher for female participants (18.4%) and low-income communities (22.4%) than the overall level (Appendix Figure 1B, available online).
Food insecurity may be associated with COVID-19 infection through (1) poorer diet quality and insufficient nutrient intake and (2) less practicing physical distance in public or taking preventive actions. Individuals with household food insecurity had significantly lower Healthy Eating Index scores than food-secure individuals, a measure of diet quality (difference in score= −2.22 unit, 95% CI= −3.35, −1.08).23,24 Food insecurity was also associated with less consumption of fruit, vegetables, dairy products, and whole grains and a lower intake of vitamins A and B6, calcium, magnesium, and zinc.25,26 Nutrients such as vitamins, calcium, magnesium, and zinc are important for supporting immune systems (e.g., providing energy, regulating immune cell metabolism, functioning as antibacterial or antiviral products, and being substrates for the intestinal microbiota).27, 28, 29 Weakened immune system due to a lack of essential nutrients and its associated inflammation, oxidative stress, and gut dysbiosis may further contribute to poorer defense against pathogens, increased susceptibility to virus infection, and severer disease symptoms.30 The other explanation that may account for the observed association between food insecurity and COVID-19 infection is that the food-insecure population may be less likely to practice physical social distancing in public and take protective actions than the food-secure population. For example, food-insecure individuals were less likely than food-secure individuals to comply with public health recommendations to stock up on 2 weeks of food to avoid excess trips and practice social distancing.31 Our results suggested that food-insecure individuals were more likely to have lower socioeconomic status than food-secure individuals. Studies have shown that lower SES (e.g., lower income or education level) was significantly associated with less engagement in COVID-19−protective behaviors such as avoiding leaving home, hand washing, cleaning, or disinfecting.32 Besides, food-insecure adults were more likely to report challenges in getting medications or having needed health care during the pandemic.31 Individuals with poorer health status due to unmet healthcare needs may be more vulnerable to COVID-19 infection and experience disease symptoms compared with those with better health conditions.33,34
Our study was strengthened by using a nationally representative sample from the NHIS. To the best of our knowledge, this is the first study to examine the association between food insecurity and COVID-19 infection in the overall U.S. adults and communities vulnerable to food insecurity. The results have practical implications for policymakers and future pandemic prevention. Allocations of food benefits such as nutrient assistance programs should prioritize disadvantaged communities such as female individuals, Hispanic and non-Hispanic Black people, and those with lower socioeconomic status. Policies addressing food insecurity may help to reduce the likelihood of COVID-19 infection, especially for vulnerable subgroups such as young, female, and non-Hispanic Black persons.
Limitations
There were a few limitations of this study. First, the cross-sectional study design prevents causality inference. Food insecurity was measured with a 30-day look-back window, and the temporal relationship between food insecurity and COVID-19 infection could not be determined. Therefore, reverse causality should not be excluded. Poorer health conditions may alternatively increase vulnerability to food insecurity by affecting the employment or income status and adding additional financial burden.14 Second, COVID-19 infection status and health-related covariates were self-reported, thus being subject to recall bias. Positive COVID-19 infection was possibly underestimated because the asymptomatic populations were not tested. Although sampling weights have been applied to account for nonresponse bias, the prevalence of food insecurity and positive COVID-19 infection may still be under-represented owing to lower response rates during the pandemic. Finally, the association between food insecurity and symptoms or severity of COVID-19 infection was not analyzed owing to the limited sample size of positive cases. Unmeasured factors associated with food insecurity and COVID-19 infection may still exist and confound the association.
CONCLUSIONS
Food insecurity unequally affected vulnerable groups and was associated with positive COVID-19 infection. Policies addressing food insecurity may help to reduce the likelihood of COVID-19 infection and improve public health. Allocation of food resources during the pandemic should target the most disadvantaged groups such as young people, female people, minority race/ethnicity groups, and those with lower socioeconomic status. Screening of health conditions and providing affordable health resources are also necessary for food-insecure populations.
Acknowledgments
ACKNOWLEDGMENTS
Declaration of interest: none.
CRediT AUTHOR STATEMENT
Jiahui Cai: Conceptualization, Formal analysis, Methodology, Software, Writing - original draft, Writing – review & editing.
Footnotes
Supplementary material associated with this article can be found in the online version at doi:10.1016/j.focus.2023.100069.
Appendix. Supplementary materials
REFERENCES
- 1.Definitions of food security. U.S. Department of Agriculture, Economic Research Service. https://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-u-s/definitions-of-food-security/. Accessed April 22, 2022.
- 2.Niles MT, Bertmann F, Belarmino EH, Wentworth T, Biehl E, Neff R. The early food insecurity impacts of COVID-19. Nutrients. 2020;12(7):2096. doi: 10.3390/nu12072096. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Fitzpatrick KM, Harris C, Drawve G, Willis DE. Assessing food insecurity among U.S. adults during the COVID-19 pandemic. J Hunger Environ Nutr. 2021;16(1):1–18. doi: 10.1080/19320248.2020.1830221. [DOI] [Google Scholar]
- 4.Coleman-Jensen A, Rabbitt MP, Gregory CA, Singh A. Economic Research Service, U.S. Department of Agriculture; Washington, DC: Published September 2021. Household food security in the United States in 2020.https://www.ers.usda.gov/webdocs/publications/102076/err-298.pdf?v=9765.7 Accessed April 22, 2022. [Google Scholar]
- 5.Nagata JM, Ganson KT, Whittle HJ, et al. Food insufficiency and mental health in the U.S. during the COVID-19 pandemic. Am J Prev Med. 2021;60(4):453–461. doi: 10.1016/j.amepre.2020.12.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Te Vazquez J, Feng SN, Orr CJ, Berkowitz SA. Food insecurity and cardiometabolic conditions: a review of recent research. Curr Nutr Rep. 2021;10(4):243–254. doi: 10.1007/s13668-021-00364-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Polsky JY, Gilmour H. Food insecurity and mental health during the COVID-19 pandemic. Health Rep. 2020;31(12):3–11. doi: 10.25318/82-003-x202001200001-eng. [DOI] [PubMed] [Google Scholar]
- 8.Jia J, Fung V, Meigs JB, Thorndike AN. Food insecurity, dietary quality, and health care utilization in lower-income adults: a cross-sectional study. J Acad Nutr Diet. 2021;121(11):2177–2186.e3. doi: 10.1016/j.jand.2021.06.001. [DOI] [PubMed] [Google Scholar]
- 9.Foolchand A, Ghazi T, Chuturgoon AA. Malnutrition and dietary habits alter the immune system which may consequently influence SARS-CoV-2 virulence: a review. Int J Mol Sci. 2022;23(5):2654. doi: 10.3390/ijms23052654. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Men F, Tarasuk V. Food insecurity amid the COVID-19 pandemic: food charity, government assistance, and employment. Can Public Policy. 2021;47(2):202–230. doi: 10.3138/cpp.2021-001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Choi SL, Men F. Food insecurity associated with higher COVID-19 infection in households with older adults. Public Health. 2021;200:7–14. doi: 10.1016/j.puhe.2021.09.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Centers for Disease Control and Prevention . Centers for Disease Control and Prevention; Atlanta, GA: Published September 2021. 2020 National Health Interview Survey (NHIS) survey description.https://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/NHIS/2020/srvydesc-508.pdf Accessed April 19, 2022. [Google Scholar]
- 13.Keenan DP, Olson C, Hersey JC, Parmer SM. Measures of food insecurity/security. J Nutr Educ. 2001;33(suppl 1):S49–S58. doi: 10.1016/s1499-4046(06)60069-9. [DOI] [PubMed] [Google Scholar]
- 14.Tarasuk V, Mitchell A, McLaren L, McIntyre L. Chronic physical and mental health conditions among adults may increase vulnerability to household food insecurity. J Nutr. 2013;143(11):1785–1793. doi: 10.3945/jn.113.178483. [DOI] [PubMed] [Google Scholar]
- 15.Wang X, Fang X, Cai Z, et al. Comorbid chronic diseases and acute organ injuries are strongly correlated with disease severity and mortality among COVID-19 patients: a systemic review and meta-analysis. Research (Wash D C) 2020;2020 doi: 10.34133/2020/2402961. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Yuan YC. Multiple imputation for missing data: concepts and new development (version 9.0). Rockville, MD: SAS Institute Inc. https://support.sas.com/rnd/app/stat/papers/multipleimputation.pdf. Published 2010. Accessed May 20, 2022.
- 17.Morales DX, Morales SA, Beltran TF. Racial/ethnic disparities in household food insecurity during the COVID-19 pandemic: a nationally representative study. J Racial Ethn Health Disparities. 2021;8(5):1300–1314. doi: 10.1007/s40615-020-00892-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Coats JV, Humble S, Johnson KJ, et al. Employment loss and food insecurity - race and sex disparities in the context of COVID-19. Prev Chronic Dis. 2022;19:E52. doi: 10.5888/pcd19.220024. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Johnson-Agbakwu CE, Ali NS, Oxford CM, Wingo S, Manin E, Coonrod DV. Racism, COVID-19, and health inequity in the USA: a call to action. J Racial Ethn Health Disparities. 2022;9(1):52–58. doi: 10.1007/s40615-020-00928-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Perry BL, Aronson B, Pescosolido BA. Pandemic precarity: COVID-19 is exposing and exacerbating inequalities in the American heartland. Proc Natl Acad Sci U S A. 2021;118(8) doi: 10.1073/pnas.2020685118. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Stephens EC, Martin G, van Wijk M, Timsina J, Snow V. Editorial: Impacts of COVID-19 on agricultural and food systems worldwide and on progress to the sustainable development goals. Agric Syst. 2020;183 doi: 10.1016/j.agsy.2020.102873. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Poole MK, Fleischhacker SE, Bleich SN. Addressing child hunger when school is closed - considerations during the pandemic and beyond. N Engl J Med. 2021;384(10):e35. doi: 10.1056/NEJMp2033629. [DOI] [PubMed] [Google Scholar]
- 23.Dietary guidelines for Americans. 2015-2020. https://www.dietaryguidelines.gov/sites/default/files/2019-05/2015-2020_Dietary_Guidelines.pdf. Accessed February 7, 2023.
- 24.Leung CW, Tester JM. The association between food insecurity and diet quality varies by race/ethnicity: an analysis of national health and nutrition examination survey 2011–2014 results. J Acad Nutr Diet. 2019;119(10):1676–1686. doi: 10.1016/j.jand.2018.10.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Jimenez Rincon S, Dou N, Murray-Kolb LE, et al. Daily food insecurity is associated with diet quality, but not energy intake, in winter and during COVID-19, among low-income adults. Nutr J. 2022;21(1):19. doi: 10.1186/s12937-022-00768-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Hanson KL, Connor LM. Food insecurity and dietary quality in U.S. adults and children: a systematic review. Am J Clin Nutr. 2014;100(2):684–692. doi: 10.3945/ajcn.114.084525. [DOI] [PubMed] [Google Scholar]
- 27.Christian VJ, Miller KR, Martindale RG. Food insecurity, malnutrition, and the microbiome. Curr Nutr Rep. 2020;9(4):356–360. doi: 10.1007/s13668-020-00342-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Calder PC. Nutrition and immunity: lessons for COVID-19. Nutr Diabetes. 2021;11(1):19. doi: 10.1038/s41387-021-00165-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.James PT, Ali Z, Armitage AE, et al. The role of nutrition in COVID-19 susceptibility and severity of disease: a systematic review. J Nutr. 2021;151(7):1854–1878. doi: 10.1093/jn/nxab059. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Butler MJ, Barrientos RM. The impact of nutrition on COVID-19 susceptibility and long-term consequences. Brain Behav Immun. 2020;87:53–54. doi: 10.1016/j.bbi.2020.04.040. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Wolfson JA, Leung CW. Food insecurity and COVID-19: disparities in early effects for U.S. adults. Nutrients. 2020;12(6):1648. doi: 10.3390/nu12061648. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Capasso A, Kim S, Ali SH, Jones AM, DiClemente RJ, Tozan Y. Employment conditions as barriers to the adoption of COVID-19 mitigation measures: how the COVID-19 pandemic may be deepening health disparities among low-income earners and essential workers in the United States. BMC Public Health. 2022;22(1):870. doi: 10.1186/s12889-022-13259-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Ssentongo P, Ssentongo AE, Heilbrunn ES, Ba DM, Chinchilli VM. Association of cardiovascular disease and 10 other pre-existing comorbidities with COVID-19 mortality: a systematic review and meta-analysis. PLoS One. 2020;15(8) doi: 10.1371/journal.pone.0238215. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Shahid Z, Kalayanamitra R, McClafferty B, et al. COVID-19 and older adults: what we know. J Am Geriatr Soc. 2020;68(5):926–929. doi: 10.1111/jgs.16472. [DOI] [PMC free article] [PubMed] [Google Scholar]
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