The food insecurity rate in the United States was 11.8% in 2020. Explore a map of hunger statistics in the United States at the state and local level.

The Current Population Survey Food Security Supplement (CPS-FSS) is the source of national and State-level statistics on food insecurity used in USDA's annual reports on household food security. The CPS is a monthly labor force survey of about 50,000 households conducted by the Census Bureau for the Bureau of Labor Statistics. Once each year, after answering the labor force questions, the same households are asked a series of questions (the Food Security Supplement) about food security, food expenditures, and use of food and nutrition assistance programs. Food security data have been collected by the CPS-FSS each year since 1995. Four data sets that complement those available from the Census Bureau are available for download on the ERS website. These are available as ASCII uncompressed or zipped files. The purpose and appropriate use of these additional data files are described below: 1) CPS 1995 Revised Food Security Status data--This file provides household food security scores and food security status categories that are consistent with procedures and variable naming conventions introduced in 1996. This includes the "common screen" variables to facilitate comparisons of prevalence rates across years. This file must be matched to the 1995 CPS Food Security Supplement public-use data file. 2) CPS 1998 Children's and 30-day Food Security data--Subsequent to the release of the April 1999 CPS-FSS public-use data file, USDA developed two additional food security scales to describe aspects of food security conditions in interviewed households not captured by the 12-month household food security scale. This file provides three food security variables (categorical, raw score, and scale score) for each of these scales along with household identification variables to allow the user to match this supplementary data file to the CPS-FSS April 1998 data file. 3) CPS 1999 Children's and 30-day Food Security data--Subsequent to the release of the April 1999 CPS-FSS public-use data file, USDA developed two additional food security scales to describe aspects of food security conditions in interviewed households not captured by the 12-month household food security scale. This file provides three food security variables (categorical, raw score, and scale score) for each of these scales along with household identification variables to allow the user to match this supplementary data file to the CPS-FSS April 1999 data file. 4) CPS 2000 30-day Food Security data--Subsequent to the release of the September 2000 CPS-FSS public-use data file, USDA developed a revised 30-day CPS Food Security Scale. This file provides three food security variables (categorical, raw score, and scale score) for the 30-day scale along with household identification variables to allow the user to match this supplementary data file to the CPS-FSS September 2000 data file. Food security is measured at the household level in three categories: food secure, low food security and very low food security. Each category is measured by a total count and as a percent of the total population. Categories and measurements are broken down further based on the following demographic characteristics: household composition, race/ethnicity, metro/nonmetro area of residence, and geographic region. The food security scale includes questions about households and their ability to purchase enough food and balanced meals, questions about adult meals and their size, frequency skipped, weight lost, days gone without eating, questions about children meals, including diversity, balanced meals, size of meals, skipped meals and hunger. Questions are also asked about the use of public assistance and supplemental food assistance. The food security scale is 18 items that measure insecurity. A score of 0-2 means a house is food secure, from 3-7 indicates low food security, and 8-18 means very low food security. The scale and the data also report the frequency with which each item is experienced. Data are available as .dat files which may be processed in statistical software or through the United State Census Bureau's DataFerret http://dataferrett.census.gov/. Data from 2010 onwards is available below and online. Data from 1995-2009 must be accessed through DataFerrett. DataFerrett is a data analysis and extraction tool to customize federal, state, and local data to suit your requirements. Through DataFerrett, the user can develop an unlimited array of customized spreadsheets that are as versatile and complex as your usage demands then turn those spreadsheets into graphs and maps without any additional software. Resources in this dataset:Resource Title: December 2014 Food Security CPS Supplement. File Name: dec14pub.zipResource Title: December 2013 Food Security CPS Supplement. File Name: dec13pub.zipResource Title: December 2012 Food Security CPS Supplement. File Name: dec12pub.zipResource Title: December 2011 Food Security CPS Supplement. File Name: dec11pub.zipResource Title: December 2010 Food Security CPS Supplement. File Name: dec10pub.zip

Historical dataset showing U.S. hunger statistics by year from 2001 to 2022.

https://map.feedingamerica.org/Every community in the country is home to people who struggle with hunger. Since federal nutrition programs don’t reach everyone in need, food banks help fill the gap. Learn more about local food insecurity by exploring data from Feeding America’s annual Map the Meal Gap study. When we better understand hunger, we can help end hunger.What is food insecurity and what does it look like in America?Food insecurity refers to USDA’s measure of lack of access, at times, to enough food for an active, healthy life for all household members and limited or uncertain availability of nutritionally adequate foods. Food-insecure households are not necessarily food insecure all the time. Food insecurity may reflect a household’s need to make trade-offs between important basic needs, such as housing or medical bills, and purchasing nutritionally adequate foods.Notes from Feeding America regarding dIfferences from previous studies:1. Beginning in 2020, we enhanced our food insecurity model through the inclusion of a disability rate variable and refining our poverty measure to reflect non-undergraduate student poverty. The details surrounding this changed are discussed in our technical brief. Because of this methodology changes, the estimates from Map the Meal Gap 2020 are not comparable to estimates from previous years.2. In response to COVID-19, we expanded on Map the Meal Gap to include a companion study and interactive map that discuss our projections in food insecurity as a result of the pandemic. They may also be of interest to check out.

Gundersen, C., A. Dewey, E. Engelhard, M. Strayer & L. Lapinski. Map the Meal Gap 2020: A Report on County and Congressional District Food Insecurity and County Food Cost in the United States in 2018. Feeding America, 2020.

According to the Global Hunger Index 2024, which was adopted by the International Food Policy Research Institute, Somalia was the most affected by hunger and malnutrition, with an index of 44.1. Yemen and Chad followed behind. The World Hunger Index combines three indicators: undernourishment, child underweight, and child mortality. Sub-Saharan Africa most affected The index is dominated by countries in Sub-Saharan Africa. In the region, more than one fifth of the population is undernourished . In terms of individuals, however, South Asia has the highest number of undernourished people. Globally, there are 735 million people that are considered undernourished or starving. A lack of food is increasing in over 20 countries worldwide. Undernourishment worldwide The term malnutrition includes both undernutrition and overnutrition. Undernutrition occurs when an individual cannot maintain normal bodily functions such as growth, recovering from disease, and both learning and physical work. Some conditions such as diarrhea, malaria, and HIV/AIDS can all have a negative impact on undernutrition. Rural and agricultural communities can be especially susceptible to hunger during certain seasons. The annual hunger gap occurs when a family’s food supply may run out before the next season’s harvest is available and can result in malnutrition. Nevertheless, the prevalence of people worldwide that are undernourished has decreased over the last decades, from 18.7 percent in 1990-92 to 9.2 percent in 2022, but it has slightly increased since the outbreak of COVID-19. According to the Global Hunger Index, the reduction of global hunger has stagnated over the past decade.

Historical dataset showing North America hunger statistics by year from 2001 to 2022.

This dataset measures food availability and access for 76 low- and middle-income countries. The dataset includes annual country-level data on area, yield, production, nonfood use, trade, and consumption for grains and root and tuber crops (combined as R&T in the documentation tables), food aid, total value of imports and exports, gross domestic product, and population compiled from a variety of sources. This dataset is the basis for the International Food Security Assessment 2015-2025 released in June 2015. This annual ERS report projects food availability and access for 76 low- and middle-income countries over a 10-year period. Countries (Spatial Description, continued): Democratic Republic of the Congo, Ecuador, Egypt, El Salvador, Eritrea, Ethiopia, Gambia, Georgia, Ghana, Guatemala, Guinea, Guinea-Bissau, Haiti, Honduras, India, Indonesia, Jamaica, Kenya, Kyrgyzstan, Laos, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Moldova, Mongolia, Morocco, Mozambique, Namibia, Nepal, Nicaragua, Niger, Nigeria, North Korea, Pakistan, Peru, Philippines, Rwanda, Senegal, Sierra Leone, Somalia, Sri Lanka, Sudan, Swaziland, Tajikistan, Tanzania, Togo, Tunisia, Turkmenistan, Uganda, Uzbekistan, Vietnam, Yemen, Zambia, and Zimbabwe. Resources in this dataset:Resource Title: CSV File for all years and all countries. File Name: gfa25.csvResource Title: International Food Security country data. File Name: GrainDemandProduction.xlsxResource Description: Excel files of individual country data. Please note that these files provide the data in a different layout from the CSV file. This version of the data files was updated 9-2-2021

More up-to-date files may be found at: https://www.ers.usda.gov/data-products/international-food-security.aspx

Please find attached the zip file to access the data.

For the eleventh consecutive year, Feeding America conducted our annual Map the Meal Gap study to improve our understanding of food insecurity and food costs at the local level. The most recent release is based on data from 2019. In response to COVID-19, we also released a companion study and interactive map that illustrate the projected impact of the pandemic on local food insecurity in 2020 and 2021. To better assess the current and future state of local food insecurity, it is critical to understand historical variations prior to the pandemic. Only then can we develop effective strategies to reach people at risk of hunger.

This data section provides information about publicly available national surveys that include questions from the U.S. Food Security Survey Module. Information on each survey and directions for accessing data files are available in the documentation.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Web Page For complete information, please visit https://data.gov.

Historical dataset showing Latin America & Caribbean hunger statistics by year from 2001 to 2022.

According to the Global Hunger Index 2024, hunger worldwide decreased since 2000, but the pace of the reduction has slowed since 2016. In the Middle East and North Africa, for instance, the hunger index value was the same in 2024 as in 2016, and it had even increased marginally in Latin America and the Caribbean. In 2024, Somalia had the highest index score worldwide, meaning it was the country where hunger was most prevalent. The World Hunger Index combines four indicators: undernourishment, child stunting, child wasting, and child mortality.

Abstract

Sustainable Development Goal (SDG) target 2.1 commits countries to end hunger, ensure access by all people to safe, nutritious and sufficient food all year around. Indicator 2.1.2, “Prevalence of moderate or severe food insecurity based on the Food Insecurity Experience Scale (FIES)”, provides internationally-comparable estimates of the proportion of the population facing difficulties in accessing food. More detailed background information is available at https://www.fao.org/measuring-hunger/en.

The FIES-based indicators are compiled using the FIES survey module, containing eight questions. Two indicators can be computed: 1. The proportion of the population experiencing moderate or severe food insecurity (SDG indicator 2.1.2), 2. The proportion of the population experiencing severe food insecurity.

These data were collected by FAO through the Gallup World Poll. General information on the methodology can be found here: https://www.gallup.com/178667/gallup-world-poll-work.aspx. National institutions can also collect FIES data by including the FIES survey module in nationally representative surveys.

Microdata can be used to calculate the indicator 2.1.2 at national level. Instructions for computing this indicator are described in the methodological document available in the downloads tab. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error.

Geographic coverage

National

Analysis unit

Individuals

Universe

Non-institutionalized adult population (15 years of age or older) living in households with access to landline and/or mobile phones.

Kind of data

Sample survey data [ssd]

Sampling procedure

With some exceptions, all samples are probability based and nationally representative of the resident adult population. The coverage area is the entire country including rural areas, and the sampling frame represents the entire civilian, non-institutionalized, aged 15 and older population. For more details on the overall sampling and data collection methodology, see the World poll methodology attached as a resource in the downloads tab. Specific sampling details for each country are also attached as technical documents in the downloads tab. Exclusions: NA Design effect: 1.37

Mode of data collection

Computer-Assisted Telephone Interviewing [CATI]

Cleaning operations

Statistical validation assesses the quality of the FIES data collected by testing their consistency with the assumptions of the Rasch model. This analysis involves the interpretation of several statistics that reveal 1) items that do not perform well in a given context, 2) cases with highly erratic response patterns, 3) pairs of items that may be redundant, and 4) the proportion of total variance in the population that is accounted for by the measurement model.

Sampling error estimates

The margin of error is estimated as 3.6 percentage points. By adding and subtracting this value to the result, the confidence interval at 95% level is obtained. The margin of error was calculated assuming a reported outcome of 50% (giving the maximum sampling variability for that sample size) and takes into account the design effect.

The Older Adult food insecurity rate in the United States was 11.9% in 2022. Explore a map of older adult hunger statistics in the United States at the state and local level.

The food insecurity rate in the United States was in 2019. Explore a map of hunger statistics in the United States at the state and local level.

NOTE: Due to resource constraints, Team Rubicon is no longer updating operational status of Food Banks. The Feeding America nationwide network of food banks secures and distributes 4.3 billion meals each year through food pantries and meal programs throughout the United States and leads the nation to engage in the fight against hunger.What is a food bank?A food bank is a non-profit organization that collects and distributes food to hunger-relief charities. Food banks act as food storage and distribution depots for smaller front line agencies; and usually do not themselves give out food directly to people struggling with hunger.Food banks in the U.S. are very diverse – from small operations serving people spread out across large rural areas to very large facilities that store and distribute many millions of pounds of food each year, and everything in between. A variety of factors impact how food banks work, from the size of the facility to the number of staff members. But, one thing all food banks have in common is that they rely on donors and volunteers to carry out their day-to-day operations.Data Source: https://www.feedingamerica.org/find-your-local-foodbank

This map includes New Mexico County data from 2021.Data was obtained from Feeding America. Overall (all ages) Hunger & Poverty in the United States | Map the Meal Gap (feedingamerica.org)

Abstract

Sustainable Development Goal (SDG) target 2.1 commits countries to end hunger, ensure access by all people to safe, nutritious and sufficient food all year around. Indicator 2.1.2, “Prevalence of moderate or severe food insecurity based on the Food Insecurity Experience Scale (FIES)”, provides internationally-comparable estimates of the proportion of the population facing difficulties in accessing food. More detailed background information is available at https://www.fao.org/measuring-hunger/en.

The FIES-based indicators are compiled using the FIES survey module, containing eight questions. Two indicators can be computed: 1. The proportion of the population experiencing moderate or severe food insecurity (SDG indicator 2.1.2), 2. The proportion of the population experiencing severe food insecurity.

These data were collected by FAO through the Gallup World Poll. General information on the methodology can be found here: https://www.gallup.com/178667/gallup-world-poll-work.aspx. National institutions can also collect FIES data by including the FIES survey module in nationally representative surveys.

Microdata can be used to calculate the indicator 2.1.2 at national level. Instructions for computing this indicator are described in the methodological document available in the downloads tab. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error.

Geographic coverage

National

Analysis unit

Individuals

Universe

Non-institutionalized adult population (15 years of age or older) living in households with access to landline and/or mobile phones.

Kind of data

Sample survey data [ssd]

Sampling procedure

With some exceptions, all samples are probability based and nationally representative of the resident adult population. The coverage area is the entire country including rural areas, and the sampling frame represents the entire civilian, non-institutionalized, aged 15 and older population. For more details on the overall sampling and data collection methodology, see the World poll methodology attached as a resource in the downloads tab. Specific sampling details for each country are also attached as technical documents in the downloads tab. Exclusions: NA Design effect: 1.37

Mode of data collection

Computer-Assisted Telephone Interviewing [CATI]

Cleaning operations

Statistical validation assesses the quality of the FIES data collected by testing their consistency with the assumptions of the Rasch model. This analysis involves the interpretation of several statistics that reveal 1) items that do not perform well in a given context, 2) cases with highly erratic response patterns, 3) pairs of items that may be redundant, and 4) the proportion of total variance in the population that is accounted for by the measurement model.

Sampling error estimates

The margin of error is estimated as 3.6 percentage points. By adding and subtracting this value to the result, the confidence interval at 95% level is obtained. The margin of error was calculated assuming a reported outcome of 50% (giving the maximum sampling variability for that sample size) and takes into account the design effect.

In 2023, the rate of undernourishment worldwide was 9.1 percent. The region with the largest share of undernourished people was Sub-Saharan Africa, with 23.2 percent. Undernourished people worldwideSouthern Asia and Sub-Saharan Africa have some of the highest numbers of undernourished people in the world, totaling 281 million and 278 million, respectively, in 2023. Based on the World Hunger Index 2024, Somalia and Yemen were among the most affected countries by hunger and malnutrition. Worldwide, about 733.4 million people were suffering from malnutrition in 2023. MalnutritionMalnutrition occurs when a person’s diet consists of too little or too much of certain nutrients. Undernutrition occurs when a person does not intake enough calories, protein, or micronutrients. One of the primary causes of malnutrition is due to limited or a lack of accessibility to affordable, nutritious foods. Malnutrition is considered to contribute to over a third of child deaths globally. In Asia, an estimated 77 million cases of stunting, which is the primary effect of malnutrition, were recorded for children under the age of five in 2022. The FAO reports that food security and nutrition commitments by national governments are essential in eradicating the world hunger problem. Agricultural productivity, accessibility to land, services, and markets, rural development strategies, and social protection are needed to ensure a reduction in malnutrition.

During the school year, many children receive free and reduced-price breakfast and lunch through the School Breakfast and National School Lunch Programs. What happens when school lets out? Hunger is one of the most severe roadblocks to the learning process. Lack of nutrition during the summer months may set up a cycle for poor performance once school begins again. Hunger also may make children more prone to illness and other health issues. The Summer Food Service Program is designed to fill that nutrition gap and make sure children can get the nutritious meals they need. This data set contains information on summer food service participation, meals served and cash payments provided by state.

Abstract

Sustainable Development Goal (SDG) target 2.1 commits countries to end hunger, ensure access by all people to safe, nutritious and sufficient food all year around. Indicator 2.1.2, “Prevalence of moderate or severe food insecurity based on the Food Insecurity Experience Scale (FIES)”, provides internationally-comparable estimates of the proportion of the population facing difficulties in accessing food. More detailed background information is available at https://www.fao.org/measuring-hunger/en.

The FIES-based indicators are compiled using the FIES survey module, containing eight questions. Two indicators can be computed: 1. The proportion of the population experiencing moderate or severe food insecurity (SDG indicator 2.1.2), 2. The proportion of the population experiencing severe food insecurity.

These data were collected by FAO through the Gallup World Poll. General information on the methodology can be found here: https://www.gallup.com/178667/gallup-world-poll-work.aspx. National institutions can also collect FIES data by including the FIES survey module in nationally representative surveys.

Microdata can be used to calculate the indicator 2.1.2 at national level. Instructions for computing this indicator are described in the methodological document available in the downloads tab. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error.

Geographic coverage

National

Analysis unit

Individuals

Universe

Non-institutionalized adult population (15 years of age or older) living in households.

Kind of data

Sample survey data [ssd]

Sampling procedure

With some exceptions, all samples are probability based and nationally representative of the resident adult population. The coverage area is the entire country including rural areas, and the sampling frame represents the entire civilian, non-institutionalized, aged 15 and older population. For more details on the overall sampling and data collection methodology, see the World poll methodology attached as a resource in the downloads tab. Specific sampling details for each country are also attached as technical documents in the downloads tab. Exclusions: Transnistria (Prednestrovie) excluded for safety of interviewers. The excluded area represents approximately 13% of the population. Design effect: 1.22

Mode of data collection

Face-to-Face [f2f]

Cleaning operations

Statistical validation assesses the quality of the FIES data collected by testing their consistency with the assumptions of the Rasch model. This analysis involves the interpretation of several statistics that reveal 1) items that do not perform well in a given context, 2) cases with highly erratic response patterns, 3) pairs of items that may be redundant, and 4) the proportion of total variance in the population that is accounted for by the measurement model.

Sampling error estimates

The margin of error is estimated as 3.4 percentage points. By adding and subtracting this value to the result, the confidence interval at 95% level is obtained. The margin of error was calculated assuming a reported outcome of 50% (giving the maximum sampling variability for that sample size) and takes into account the design effect.