The Child food insecurity rate in the United States was 14.6% in 2019. Explore a map of child 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

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.

Virgin Islands (U.S.) hunger statistics for was 0.00%, a 0% increase from .

<ul style='margin-top:20px;'>

<li>Virgin Islands (U.S.) hunger statistics for was <strong>0.00%</strong>, a <strong>0% increase</strong> from .</li>
<li>Virgin Islands (U.S.) hunger statistics for was <strong>0.00%</strong>, a <strong>0% increase</strong> from .</li>
<li>Virgin Islands (U.S.) hunger statistics for was <strong>0.00%</strong>, a <strong>0% increase</strong> from .</li>
</ul>Population below minimum level of dietary energy consumption (also referred to as prevalence of undernourishment) shows the percentage of the population whose food intake is insufficient to meet dietary energy requirements continuously. Data showing as 5 may signify a prevalence of undernourishment below 5%.

Central America hunger statistics for was 0.00%, a 0% increase from .

<ul style='margin-top:20px;'>

<li>Central America hunger statistics for was <strong>0.00%</strong>, a <strong>0% increase</strong> from .</li>
<li>Central America hunger statistics for was <strong>0.00%</strong>, a <strong>0% increase</strong> from .</li>
<li>Central America hunger statistics for was <strong>0.00%</strong>, a <strong>0% increase</strong> from .</li>
</ul>Population below minimum level of dietary energy consumption (also referred to as prevalence of undernourishment) shows the percentage of the population whose food intake is insufficient to meet dietary energy requirements continuously. Data showing as 5 may signify a prevalence of undernourishment below 5%.

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.

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

American Samoa hunger statistics for was 0.00%, a 0% increase from .

<ul style='margin-top:20px;'>

<li>American Samoa hunger statistics for was <strong>0.00%</strong>, a <strong>0% increase</strong> from .</li>
<li>American Samoa hunger statistics for was <strong>0.00%</strong>, a <strong>0% increase</strong> from .</li>
<li>American Samoa hunger statistics for was <strong>0.00%</strong>, a <strong>0% increase</strong> from .</li>
</ul>Population below minimum level of dietary energy consumption (also referred to as prevalence of undernourishment) shows the percentage of the population whose food intake is insufficient to meet dietary energy requirements continuously. Data showing as 5 may signify a prevalence of undernourishment below 5%.

The food insecurity rate in the United States was 13.5% in 2022. Explore a map of hunger statistics in the United States at the state and local level.

The food insecurity rate in the United States was 12.5% in 2017. Explore a map of hunger statistics in the United States at the state and local level.

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.

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.

Financial overview and grant giving statistics of Action Against Hunger Usa

The Current Population Survey Food Security Supplement (CPS-FSS) is a nationally representative dataset created by the U.S. Census Bureau under sponsorship by the U.S. Department of Agriculture (USDA) Economic Research Service (ERS). It has been collected annually since 1995 as a supplement to the monthly CPS, which surveys approximately 50,000 households on labor force and socioeconomic topics. The dataset measures food security, including indicators like food expenditure, access to food, quality, safety, and participation in federal food assistance programs. It uses a standardized 18-item module to assess household-level food insecurity severity. Key features include state-level estimates (since 1998) and alignment with USDA’s annual reports on food security. Its primary purpose is to monitor hunger and food insecurity trends in the U.S., informing policy decisions and programs like SNAP (Supplemental Nutrition Assistance Program). Researchers and policymakers use it to analyze disparities by demographic factors (e.g., income, race, geography) and evaluate the impact of economic or public health crises (e.g., the COVID-19 pandemic). Unique aspects include its longitudinal consistency, integration with labor force data, and public accessibility via platforms like the USDA ERS and Census Bureau, enabling robust analyses of food insecurity’s social and economic determinants. (Source: USDA ERS, Census Bureau, and academic analyses cited in search results.)

Change in undernourished children and population at risk of hunger in 2030 from faster productivity growth.

Data are provided in this collection on labor force activity for the week prior to the survey. Comprehensive data are available on the employment status, occupation, and industry of persons 15 years old and older. Also shown are personal characteristics such as age, sex, race, marital status, veteran status, household relationship, educational background, and Hispanic origin. The Food Security Supplement was conducted by the Bureau of the Census for the Food and Consumer Service of the United States Department of Agriculture. Supplement questions were asked of all interviewed households, as appropriate. Questions included expenditure for food, whether the household had enough food and had the kinds of food they wanted, and whether the household was running short of money and trying to make their food or food money go further. Additional questions dealt with getting food from food pantries or soup kitchens, cutting the size of or skipping meals, and losing weight because there wasn't enough food. The supplement was intended to research the full range of the severity of food insecurity and hunger as experienced in United States households and was used by the supplement sponsor to produce a scaled measure of food insecurity. Responses to individual items in this supplement are not meaningful measures of food insufficiency and should not be used in such a manner.

Data are provided in this collection on labor force activity for the week prior to the survey. Comprehensive data are available on the employment status, occupation, and industry of persons 15 years old and older. Also shown are personal characteristics such as age, sex, race, marital status, veteran status, household relationship, educational background, and Hispanic origin. The Food Security Supplement was conducted by the Bureau of the Census for the Food and Consumer Service (FCS) of the United States Department of Agriculture. Supplement questions were asked of all interviewed households, as appropriate. Questions included expenditure for food, whether the household had enough food and had the kinds of food they wanted, and whether the household was running short of money and trying to make their food or food money go further. Additional questions dealt with getting food from food pantries or soup kitchens, cutting the size of or skipping meals, and loosing weight because there was not enough food. The supplement was intended to research the full range of the severity of food insecurity and hunger as experienced in United States households and was used by the supplement sponsor to produce a scaled measure of food insecurity. Responses to individual items in this supplement are not meaningful measures of food insufficiency and should not be used in such a manner. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR03044.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

Relative impacts of faster productivity growth on income, poverty and food security indicators: Highest-ranked crops in selected regions.

description: Led by USAID, Feed the Future is the U.S. Government?s global hunger and food security initiative, which establishes a foundation for lasting progress against global hunger. (See the individual entries to retrieve data for the country surveys.) With a focus on smallholder farmers, particularly women, Feed the Future supports partner countries in developing their agriculture sectors to spur economic growth that increases incomes and reduces hunger, poverty and undernutrition. Focus countries in the Feed the Future initiative administer interim population-based surveys in their target geographic areas (zones of influence or ZOI) to monitor country program performance across a number of standardized indicators.; abstract: Led by USAID, Feed the Future is the U.S. Government?s global hunger and food security initiative, which establishes a foundation for lasting progress against global hunger. (See the individual entries to retrieve data for the country surveys.) With a focus on smallholder farmers, particularly women, Feed the Future supports partner countries in developing their agriculture sectors to spur economic growth that increases incomes and reduces hunger, poverty and undernutrition. Focus countries in the Feed the Future initiative administer interim population-based surveys in their target geographic areas (zones of influence or ZOI) to monitor country program performance across a number of standardized indicators.

Economic surplus model results: Change in economy-wide income in 2030 from faster productivity growth, as modeled by the IMPACT model, by region.