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 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

Individuals of 15 years or older 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: Transnistria (Prednestrovie) excluded for safety of interviewers. The excluded area represents approximately 13% of the population. Design effect: 1.97

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 4.4. 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.

Abstract

The FAO has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). The FAO conducted the fourth round of DIEM household survey in Cameroon between 20 March and 8 April 2023 to assess agricultural livelihoods and food security. Data was collected through computer-assisted telephone interviews conducted by Geopoll, an implementing partner, in seven of Cameroon's ten regions (Adamawa, East, Far-North, North, North-West, West and South-West). A sample of 1466 households was reached. For more information, please go to https://data-in-emergencies.fao.org/pages/monitoring

Geographic coverage

National Coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

Data was collected through computer-assisted telephone interviews conducted by Geopoll, an implementing partner, in seven of Cameroon's ten regions (Adamawa, East, Far-North, North, North-West, West and South-West). A sample of 1 466 households was reached. Data collection took place at the end of the dry season and at the start of the short rainy season in the West and North-West regions, during the dry season in the northern regions (Adamawa, North and Far-North), and at the start of the planting season in the other regions. The survey is representative at the regional level, and the sampling plan was designed with a margin of error of 8.5 per cent.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

A link to the questionnaire has been provided in the documentations tab.

Cleaning operations

The datasets have been edited and processed for analysis by the Needs Assessment team at the Office of Emergencies and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries.

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 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

Individuals of 15 years or older 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: 2.75

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 5.1. 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.

Abstract

The FAO has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). The FAO conducted a fourth round of household survey in Colombia to monitor agricultural livelihoods and food security across the rural population. The survey was conducted between 23 January and 22 February 2023 across ten priority departments: Antioquia, Arauca, Bolívar, Boyacá, Cesar, Chocó, Córdoba, La Guajira, Nariño and Putumayo. The information was collected through computer-assisted telephone interviews. For more information, please go to https://data-in-emergencies.fao.org/pages/monitoring

Geographic coverage

National Coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The information was collected through computer-assisted telephone interviews applied to a panel of informants corresponding to the third monitoring round conducted in July 2022. The final sample consisted of 2771 rural households surveyed in ten prioritized departments: Antioquia, Arauca, Bolívar, Boyacá, Cesar, Chocó, Córdoba, La Guajira, Nariño and Putumayo.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

A link to the questionnaire has been provided in the documentations tab.

Cleaning operations

The datasets have been edited and processed for analysis by the Needs Assessment team at the Office of Emergencies and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries.

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 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

Individuals of 15 years or older 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: Hermel, Baalbak, and Bint Jbeil under the strict control of Hezbollah were excluded. The excluded areas represent approximately 10% 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. 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.

Abstract

The FAO has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). The FAO Yemen Country Office, with technical support from DIEM conducted the fifth high-frequency monitoring survey, which is focused on quick-changing indicators related to shocks and food security. Data collection took place from 23 Aug – 1 Sep 2023 with 2472 households in all 22 governorates of Yemen via Computer Assisted Telephone Interviews and using Random Digit Dialing. The sample is representative at the national and governorate level. For more information, please go to https://data-in-emergencies.fao.org/pages/monitoring

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

Data collection took place from 23 Aug – 1 Sep 2023 with 2472 households in all 22 governorates of Yemen via Computer Assisted Telephone Interviews and using Random Digit Dialing. The sample is representative at the national and governorate level with a 95% confidence level and a 10% precision. This high-frequency monitoring survey is a rapid assessment of the food security situation in Yemen aimed at informing early warning systems and decision-makers. It did not collect any data on agriculture, agricultural livelihoods or needs.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

A link to the questionnaire has been provided in the documentations tab.

Cleaning operations

The datasets have been edited and processed for analysis by the DIEM team at the Office of Emergencies and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries.

Abstract

The FAO has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). The FAO launched a seventh-round survey between 3 March and 8 April 2023 to monitor agricultural livelihoods and food security in Zimbabwe. The interviews were conducted by computer-assisted telephone. This survey reached 1686 households, representative at administrative 1 level (provincial). It targeted eight out of the ten provinces in Zimbabwe, excluding Bulawayo and Harare. For more information, please go to https://data-in-emergencies.fao.org/pages/monitoring

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey reached 1 686 households, representative at administrative 1 level (provincial). Eight out of the ten provinces in Zimbabwe were targeted, excluding Bulawayo and Harare. At the provincial level, 160 agricultural households were targeted. Quotas were set following the proportion observed in the population, which resulted in 171–221 agricultural households per province. Variable targets for non-agricultural households were set following the proportion observed in the population, which resulted in 14–40 non-agricultural households per province.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

A link to the questionnaire has been provided in the documentations tab.

Cleaning operations

The datasets have been edited and processed for analysis by the DIEM team at the Office of Emergencies and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries.

The annual FAO Food Price Index* (FFPI) averaged 124.7 points in 2023, down 20 points from 2022. The highest value for the index in the past ten years was reached in 2022.

The FAO Food Price Index (FFPI) averaged 124.9 points in January 2025, down 2.1 points from December 2024. The highest value for the index in the past 23 years was reached in March 2022. However, the rate of food price increases has been decreasing since.

Food prices worldwide The annual FAO Food Price Index (FFPI) by category shows that the price of vegetable oils grew by a particularly large margin. One of the factors that influenced the spike in oil prices worldwide during 2020 and 2021 were the supply-chain disruptions during the COVID-19 pandemic. Moreover, after the war in Ukraine, shipping costs and grain prices also had a noticeable impact on global food prices. Global food prices are calculated to have increased by 3.68 percent, due to changes in shipping costs and grain prices. The European Union (EU) has experienced a particularly high increase in the annual consumer prices for food and non-alcoholic beverages, as compared to other selected countries worldwide. Inflation in Europe

The inflation rate for food in the EU grew from 0.2 percent in May 2021 to 19.2 percent in March 2023, as compared to the same month in the previous year. In the following months, the food inflation started decreasing again, reaching 1.86 percent in April 2024. The overall inflation rate in the Euro area reached its peak in December 2022 at 9.2 percent. The rate has since fallen to 2.4 percent in December 2024. As measured by the Harmonized Index of Consumer Prices (HICP), inflation rates in Europe were highest in Turkey, North Macedonia, and Romania as of December 2024.

This statistic shows the world fruit production in 2023 in million metric tons, broken down by variety. In that year, some 139 million metric tons of bananas were produced worldwide. Fruit production Fruit crops are a major part of agricultural production. Based on production quantities, the most popular fresh fruits worldwide in order are bananas, apples and grapes. Bananas and apples are grown on trees, and watermelons are grown on thick vines.For cultivation, the tropical banana plant requires a warm and humid climate and rich, dark and fertile soils. The most common banana types which are grown globally include Cavendish, Lady Fingers, and Plantains. The last variety is also known as cooking banana. Their characteristics include a drier texture and they tend to contain more starch. In many tropical countries Plantains are a staple food.According to the Food and Agricultural Organization (FAO), countries with a significant production amount include China, the United States and Turkey. Rated among the most popular apple varieties in the United States are Gala, Honeycrisp and Fuji.Fruit and vegetables are seen as a strong part of a healthy and balanced diet. The Dietary Guidelines for Americans, which are created and published every five years by the United States Department of Agriculture (USDA) and the U.S. Department of Health and Human Services (HHS), recommend increasing fruit and vegetable intake.

In the marketing year of 2024/2025, the global production volume of wheat amounted to almost 793 million metric tons. This was an increase compared to the previous marketing year. Wheat in the U.S. The United States produces a large amount of wheat each year, a great deal of which is subsequently exported. In 2022/23, the country imported about 122 million bushels of wheat, while exporting 758 million bushels. North Dakota, Kansas, and Montana were the leading U.S. states in terms of wheat production in 2023. Post Shredded Wheat Post Shredded Wheat is a brand of breakfast cereal, made from whole wheat, owned by the American company, known as Post Consumer Brands. The brand comes in many varieties, including Frosted Shredded Wheat, Original Big Biscuit, and Original Spoon Size. When surveyed in 2020, roughly six and a half million American consumers consumed between one and four portions of regular Post Shredded Wheat for breakfast over the last seven days.

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 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

Individuals of 15 years or older 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: 1.78

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 4.1. 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.

This statistic depicts the production of apricots worldwide from 2000 to 2023. According to the report, global apricot production amounted to approximately 3.73 million metric tons, a decrease from the previous year.

On 7 October 2023, two consecutive earthquakes with high macroseismic intensity categorized at 6.3 magnitude hit western Afghanistan at around 07.00 (UTC +4.30). The earthquakes mostly impacted several villages in Zindajan district, west of Herat city in Herat province, and have caused devastating loss of life and injuries across the region. The Data in Emergencies (DIEM) team at the Food and Agriculture Organization of the United Nations (FAO) examined satellite images over the period to understand the impact and published a StoryMap including recommendations on 9 October 2023 (FAO, 2023a). This StoryMap provides an update about the efforts of the FAO Representation in Afghanistan to provide response activities based on the recommendations in the October 2023 StoryMap to support the recovery from the impact of the earthquakes on agriculture and livelihoods in the affected area together with the main findings of the damages and losses assessment. This StoryMap also provides information about the needs and related responses as a powerful way of illustrating pathways from evidence to programming, and demonstrating the importance and usefulness of DIEM-Impact data.

Abstract

The agricultural survey in its current form covers all regions of the country and all 45 departments of Senegal. The agricultural survey is an annual statistical operation whose general objective is to estimate the level of the main agricultural output of family-type agricultural holdings. It also provides information on the physical characteristics of cultivated plots (geo-location, area) and major investments made in them (agricultural inputs, cultivation operations, soil management and restoration). The main indicators relate to yield levels, areas sown, production and means of production.

Following a modular approach, the 2022-2023 edition of the annual agricultural survey is characterized by the integration of the MEA module (Machines, Equipment and other Agricultural Assets). In addition, the basic module of the 50x2030 questionnaire allows the collection of data for the calculation of SDG 5.a.1.

Geographic coverage

The annual agricultural survey covers all 45 departments of Senegal. However, for reasons related to anonymization, the variable "Department" has been replaced by the variable "Agroecological Zone" which constitutes groupings in relation to the departments. The variable "Region" remains in the anonymized version of the data.

Analysis unit

Households and agricultural plots

Universe

The agricultural survey covers all households and plots in the 45 departments of Senegal.

Kind of data

Sample survey data [ssd]

Sampling procedure

The AAS was built on a two-stage survey, with census districts (CDs) as primary units (PUs) and agricultural households as secondary units (SUs), as defined during the general census of population and l'Habitat, de l'Agriculture et de l'Élevage (RGPHAE) of 2013. In line with the broadening of the scope of the survey recommended by the AGRIS approach, from this campaign onwards the sample design incorporated a first-stage stratification, induced by the second-stage stratification, to better reflect the various agricultural activities and improve the efficiency of the estimates. The choice of a first-degree stratification induced by that of the second degree, although less efficient than an independent first-degree stratification, was guided by the constraint of non-existence of relevant variables of interest in the sampling frame of the RGPHAE to discriminate against the CDs. The stratification took into account the relative importance of the main agricultural activities (in terms of household size) identified during the 2013 RGPHAE, namely rainfed agriculture, livestock and horticulture.

Thus, four strata were formed as follows:

• the "rainfed only" stratum which groups together all the households practicing only rainfed crops;
• the "livestock only" stratum for households that practice animal husbandry only;
• the "Horticulture and other crops" stratum, which includes households that mainly practice horticulture and secondarily other crops (forestry, fruit growing, etc.);
• the "Rainfed-livestock" stratum made up of households that practice both rainfed agriculture and livestock breeding.

The size of the sample of agricultural households to be surveyed was calculated by department (area of study) by setting a relative error of 10% on the variable of interest. The distribution of the sample of each department in the strata was made using the Bankier method (1988) developed in the methodological guide to the main sampling frame practices (pp. 79-81) of the Global Strategy for Agricultural and Rural Statistics (GSARS).

At the national level, the total theoretical sample is equal to 7,450 households, spread over 1,460 physical CDs, with 5 households per CD. At the end of the enumeration operation carried out in the physical sample CDs, adjustments were made to take into account the actual updated size of the CDs, which led to a final size of 7,378 households, or 1,382 CDs.

Sampling deviation

Compared to the survey plan, adjustments were made based on the response rate at each phase.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The first questionnaire collected information on census and characteristics of agricultural household plots. The second questionnaire collected information on agricultural production, machinery, equipment and agricultural productivity.

Response rate

First phase: sample of 7378 households, including 6360 surveyed, i.e. a coverage rate of 86%.

Second phase: sample of 7218 households, including 6,834 surveyed, i.e. a coverage rate of 95%.

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 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

Individuals of 15 years or older 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: 1.53

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 3.8. 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.

This statistic represents the estimated animal protein consumption worldwide in 2023, by source. In that year, the FAO estimated a volume consumption of 140 million tons of (ready to cook equivalent) poultry worldwide.

In 2024/2025, it is expected that the United States will be the largest producer of corn worldwide with a production volume amounting to about 377.6 million metric tons. China and Brazil rounded off the top corn producing countries. Corn production Corn, also known as maize, is a grain plant cultivated for food. The origin of this grain remains unknown, however, many historians believe that corn was first domesticated in Mexico's Tehuacan Valley. Types of corn include sweet corn, popcorn, pod corn, flint corn, flour corn, waxy corn and dent corn. Corn is one of the most important crops in the United States. Over the last years, the country's corn farmers experienced constant increases in annual revenues. In 2022/23, the U.S. was responsible for almost one-third of the global corn production. Iowa and Illinois were the top U.S. states based on harvested area of corn for grain in 2023. That year, Iowa's corn for grain production value amounted to approximately 11.55 million acres. In 2022/23, the United States exported around 42.5 million metric tons of corn, making the nation the world's second largest corn exporter. Mexico and China were the leading buyers of U.S. corn in 2022, purchasing approximately 662 million bushels and 579 million bushels respectively.

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 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

Individuals of 15 years or older 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: For landline RDD, excluded 12 municipalities near the nuclear power plant in Fukushima. These areas were designated as not-to-call districts due to the devastation from the 2011 disasters. The exclusion represents less than 1% of the population of Japan. Design effect: 1.39

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. 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

The variable WHLDAY was not considered in the computation of the published FAO food insecurity indicator based on FIES due to the results of the validation process. The variable WORRIED was not considered in the computation of the published FAO food insecurity indicator based on FIES due to the results of the validation process.

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 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

Individuals of 15 years or older 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: 1.34

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 3.6. 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.