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

The share of population who experience severe food insecurity in El Salvador was estimated at 15.8 percent between 2021 and 2023, a figure that increased in comparison to the previous periods. Additionally, the degree of moderate or severe food insecurity has slightly decreased since the previous three-year period, from 48.4 percent of the population to 46.9 percent. According to the source, a person is considered food insecure when they lack regular access to enough safe and nutritious food to lead an active and healthy life.

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.

Yemen hunger statistics for 2021 was 34.50%, a 1.5% decline from 2020.

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

<li>Yemen hunger statistics for 2020 was <strong>36.00%</strong>, a <strong>2.9% decline</strong> from 2019.</li>
<li>Yemen hunger statistics for 2019 was <strong>38.90%</strong>, a <strong>2.2% decline</strong> from 2018.</li>
<li>Yemen hunger statistics for 2018 was <strong>41.10%</strong>, a <strong>1.8% decline</strong> from 2017.</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%.

Brazil hunger statistics for 2021 was 4.70%, a 1% increase from 2020.

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

<li>Brazil hunger statistics for 2020 was <strong>3.70%</strong>, a <strong>1.2% increase</strong> from 2019.</li>
<li>Brazil hunger statistics for 2019 was <strong>2.50%</strong>, a <strong>0% increase</strong> from 2018.</li>
<li>Brazil hunger statistics for 2018 was <strong>2.50%</strong>, a <strong>0% increase</strong> from 2017.</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%.

This data package includes the underlying data files to replicate the charts presented in Food insecurity: What can the world trading system do about it?, PIIE Policy Brief 23-15.

If you use the data, please cite as: Wolff, Alan Wm., and Joseph W. Glauber. 2023. Food insecurity: What can the world trading system do about it?. PIIE Policy Brief 23-15. Washington, DC: Peterson Institute for International Economics.

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

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 http://www.fao.org/in-action/voices-of-the-hungry/fies/en/ .

The FIES-based indicators are compiled using the FIES survey module, containing 8 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 under the "DOCUMENTATION" tab above. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

Individuals of 15 years or older.

Kind of data

Sample survey data [ssd]

Sampling procedure

A sampling quota of at least 200 observations per each Administrative 1 areas is set Exclusions: NA Design effect: NA

Mode of data collection

Computer Assisted Telephone Interview [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 NA. This is calculated around a proportion at the 95% confidence level. The maximum margin of error was calculated assuming a reported percentage of 50% and takes into account the design effect.

Data appraisal

Since the population with access to mobile telephones is likely to differ from the rest of the population with respect to their access to food, post-hoc adjustments were made to control for the potential resulting bias. Post-stratification weights were built to adjust the sample distribution by gender and education of the respondent at admin-1 level, to match the same distribution in the total population. However, an additional step was needed to try to ascertain the food insecurity condition of those with access to phones compared to that of the total population.

Using FIES data collected by FAO through the GWP between 2014 and 2019, and a variable on access to mobile telephones that was also in the dataset, it was possible to compare the prevalence of food insecurity at moderate or severe level, and severe level only, of respondents with access to a mobile phone to that of the total population at national level.

Madagascar hunger statistics for 2021 was 51.00%, a 1.5% increase from 2020.

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

<li>Madagascar hunger statistics for 2020 was <strong>49.50%</strong>, a <strong>2.4% increase</strong> from 2019.</li>
<li>Madagascar hunger statistics for 2019 was <strong>47.10%</strong>, a <strong>2.4% increase</strong> from 2018.</li>
<li>Madagascar hunger statistics for 2018 was <strong>44.70%</strong>, a <strong>1.9% increase</strong> from 2017.</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%.

In 2024, it was estimated that the prevalence of severe food insecurity in Colombia amounted to about 5.7 percent of the population. It was expected that this number would decrease to 4.7 percent in 2029.

HT: Prevalence of Severe Food Insecurity in the Population: % of population data was reported at 42.400 % in 2022. This records a decrease from the previous number of 42.900 % for 2021. HT: Prevalence of Severe Food Insecurity in the Population: % of population data is updated yearly, averaging 44.050 % from Dec 2019 (Median) to 2022, with 4 observations. The data reached an all-time high of 48.800 % in 2019 and a record low of 42.400 % in 2022. HT: Prevalence of Severe Food Insecurity in the Population: % of population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Haiti – Table HT.World Bank.WDI: Social: Health Statistics. The percentage of people in the population who live in households classified as severely food insecure. A household is classified as severely food insecure when at least one adult in the household has reported to have been exposed, at times during the year, to several of the most severe experiences described in the FIES questions, such as to have been forced to reduce the quantity of the food, to have skipped meals, having gone hungry, or having to go for a whole day without eating because of a lack of money or other resources.;Food and Agriculture Organization of the United Nations (FAO);;

Mauritius MU: Prevalence of Severe Food Insecurity in the Population: % of population data was reported at 10.200 % in 2022. This records a decrease from the previous number of 10.500 % for 2021. Mauritius MU: Prevalence of Severe Food Insecurity in the Population: % of population data is updated yearly, averaging 7.550 % from Dec 2015 (Median) to 2022, with 8 observations. The data reached an all-time high of 10.500 % in 2021 and a record low of 5.200 % in 2015. Mauritius MU: Prevalence of Severe Food Insecurity in the Population: % of population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mauritius – Table MU.World Bank.WDI: Social: Health Statistics. The percentage of people in the population who live in households classified as severely food insecure. A household is classified as severely food insecure when at least one adult in the household has reported to have been exposed, at times during the year, to several of the most severe experiences described in the FIES questions, such as to have been forced to reduce the quantity of the food, to have skipped meals, having gone hungry, or having to go for a whole day without eating because of a lack of money or other resources.;Food and Agriculture Organization of the United Nations (FAO);;

Argentina AR: Prevalence of Severe Food Insecurity in the Population: % of population data was reported at 13.000 % in 2020. This records an increase from the previous number of 12.600 % for 2019. Argentina AR: Prevalence of Severe Food Insecurity in the Population: % of population data is updated yearly, averaging 11.900 % from Dec 2015 (Median) to 2020, with 6 observations. The data reached an all-time high of 13.000 % in 2020 and a record low of 5.800 % in 2015. Argentina AR: Prevalence of Severe Food Insecurity in the Population: % of population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Argentina – Table AR.World Bank.WDI: Social: Health Statistics. The percentage of people in the population who live in households classified as severely food insecure. A household is classified as severely food insecure when at least one adult in the household has reported to have been exposed, at times during the year, to several of the most severe experiences described in the FIES questions, such as to have been forced to reduce the quantity of the food, to have skipped meals, having gone hungry, or having to go for a whole day without eating because of a lack of money or other resources.;Food and Agriculture Organization of the United Nations (FAO);;

Cuba hunger statistics for 2022 was 2.50%, a 0% increase from 2021.

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

<li>Cuba hunger statistics for 2021 was <strong>2.50%</strong>, a <strong>0% increase</strong> from 2020.</li>
<li>Cuba hunger statistics for 2020 was <strong>2.50%</strong>, a <strong>0% increase</strong> from 2019.</li>
<li>Cuba hunger statistics for 2019 was <strong>2.50%</strong>, a <strong>0% increase</strong> from 2018.</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%.

ObjectiveTo explore the food insecurity experienced by the Roma population of the Valencian Community (Spain) and the effect of the COVID-19 lockdown.MethodQuantitative, cross-sectional exploratory study using a questionnaire that collected information on socioeconomic status and situations of food insecurity experienced before and during lockdown, based on the Food Insecurity Experience Scale of the United Nations Food and Agriculture Organization. The questionnaire was applied by health workers from the Roma community with people over 18 years of age. A descriptive analysis was carried out stratifying by sex, calculating Chi-square test to identify differences in the variables of the experiences of food insecurity.Results468 people participated (57.1% women/42.9% men) who expressed: worry about a lack of food (67.3%); eating the same type of food (37.2%); not being able to eat healthy foods (34.4%); feeling hungry and not being able to eat (9.6%). Around 2.1 percent stated that they could not eat for a whole day, and 65 percent reported that they had to ask for or provide help to be able to eat. When stratifying by sex, it was found that women had more experiences of food insecurity. Except in the case of having stopped eating for a full day, where the percentage remained constant, an increase was observed in the other experiences of food insecurity during lockdown.ConclusionsA large part of the Roma population studied, especially women, experienced situations of food insecurity before COVID-19 that were aggravated during lockdown. This situation was compensated for by community support networks.

The share of population who experience severe food insecurity in Guatemala was estimated at 21.1 percent between 2021 and 2023. There was an increase in moderate and severe food insecurity in Guatemala during the four time periods displayed here. According to the source, a person is considered food insecure when they lack regular access to enough safe and nutritious food to lead an active and healthy life.

Number and percentage of persons by household food security status, age group, sex, visible minority group, Indigenous group and immigration status, Canada and provinces.

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 http://www.fao.org/in-action/voices-of-the-hungry/fies/en/.

The FIES-based indicators are compiled using the FIES survey module, containing 8 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 GeoPoll. 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 documentations tab. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

Individuals of 15 years or older.

Kind of data

Sample survey data [ssd]

Sampling procedure

A Random Digit Dialling (RDD) approach was used to form a random sample of telephone numbers. Stratified phone numbers made available from telephone service providers or administrative registers were also used to integrate RDD when needed. Socio-demographic characteristics collected in the survey were then compared with the available information from recent national surveys to verify the extent to which the sample mirrored the total population structure. In case of discrepancies, post-stratification sampling weights were computed to adjust for the under-represented populations, typically using sex and education level. Exclusions: NA Design effect: NA

Mode of data collection

Computer Assisted Telephone Interview [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

Not Available.

Data appraisal

Since the population with access to mobile telephones is likely to differ from the rest of the population with respect to their access to food, post-hoc adjustments were made to control for the potential resulting bias. Post-stratification weights were built to adjust the sample distribution by gender and education of the respondent at admin-1 level, to match the same distribution in the total population. However, an additional step was needed to try to ascertain the food insecurity condition of those with access to phones compared to that of the total population.

Using FIES data collected by FAO through the GWP between 2014 and 2019, and a variable on access to mobile telephones that was also in the dataset, it was possible to compare the prevalence of food insecurity at moderate or severe level, and severe level only, of respondents with access to a mobile phone to that of the total population at national level.

Singapore SG: Prevalence of Moderate or Severe Food Insecurity in the Population: % of population data was reported at 7.700 % in 2022. This records an increase from the previous number of 6.600 % for 2021. Singapore SG: Prevalence of Moderate or Severe Food Insecurity in the Population: % of population data is updated yearly, averaging 4.550 % from Dec 2015 (Median) to 2022, with 8 observations. The data reached an all-time high of 7.700 % in 2022 and a record low of 2.800 % in 2015. Singapore SG: Prevalence of Moderate or Severe Food Insecurity in the Population: % of population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Singapore – Table SG.World Bank.WDI: Social: Health Statistics. The percentage of people in the population who live in households classified as moderately or severely food insecure. A household is classified as moderately or severely food insecure when at least one adult in the household has reported to have been exposed, at times during the year, to low quality diets and might have been forced to also reduce the quantity of food they would normally eat because of a lack of money or other resources.;Food and Agriculture Organization of the United Nations (FAO);;

In 2022, 11 percent of the global population experienced severe food insecurity, an increase from 7.7 percent in 2014. The share of people suffering from hunger increased in almost all of the world regions, but Africa is by far the region the most affected by severe food insecurity. There, prevalence of severe food insecurity increased by almost five percentage points from 2018 to 2022.