The share of the population who experienced severe food insecurity in Portugal was estimated at *** percent between 2021 and 2023, a decrease from the previous three-year periods. Similarly, the degree of moderate or severe food insecurity decreased from **** percent to **** percent.

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: 1.65

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. 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.

Portugal PT: Prevalence of Moderate or Severe Food Insecurity in the Population: % of population data was reported at 12.300 % in 2022. This records a decrease from the previous number of 12.400 % for 2021. Portugal PT: Prevalence of Moderate or Severe Food Insecurity in the Population: % of population data is updated yearly, averaging 11.950 % from Dec 2015 (Median) to 2022, with 8 observations. The data reached an all-time high of 14.700 % in 2015 and a record low of 10.700 % in 2018. Portugal PT: 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 Portugal – Table PT.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);;

Portugal PT: Prevalence of Severe Food Insecurity in the Population: % of population data was reported at 3.300 % in 2022. This records a decrease from the previous number of 3.900 % for 2021. Portugal PT: Prevalence of Severe Food Insecurity in the Population: % of population data is updated yearly, averaging 3.250 % from Dec 2015 (Median) to 2022, with 8 observations. The data reached an all-time high of 4.100 % in 2015 and a record low of 2.900 % in 2018. Portugal PT: 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 Portugal – Table PT.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);;

BackgroundThe Self-Administered Food Security Survey Module for Children was developed to assess food insecurity of individual children and has not been used in Portugal. We aimed to apply the mixture item response theory model to the Self-Administered Food Security Survey Module for Children, to assess its reliability and validity, and to estimate the cut-offs of the food security status for Portuguese children.MethodsThe scale was self-administered to 2132 children of the Generation XXI birth cohort. The internal consistency was assessed using Cronbach’s alpha. We evaluated dimensionality and/or clustering, and Latent Class Analysis, Latent Trait Analysis and Mixture Latent Trait Analysis were tested. The number of classes and/or traits were defined according to the Akaike Information Criterion, Bayesian Information Criterion, Adjusted Bayesian Information Criterion, Vuong-Lo-Mendell-Rubin Likelihood Ratio Test, Bootstrapped Likelihood Ratio Test and Entropy. Construct validity was explored using socio-demographic characteristics. The classification tree was used to define cut-offs to predict cluster membership.ResultsThe best model was a Mixture Latent Trait Analysis with 1 factor and 2 classes (food security and food insecurity), assuming class variant item parameters (for items 1 and 3). Based on the estimated posterior probabilities, the food insecurity prevalence was 17.6%. Cronbach’s alpha was 0.617. A higher proportion of less-educated mothers and low-income households was observed in the food insecurity class. The classification tree showed an accuracy of 100.0% by identifying the food security and food insecurity groups.ConclusionOur results supported that the Self-Administered Food Security Survey Module for Children provides a valid and reliable measure, which allows the identification of food insecurity among Portuguese children.

Europe's prepared meal manufacturing industry is witnessing significant evolution, driven primarily by shifts in consumer preferences towards healthier, more convenient and sustainable food options. As lives get busier, many Europeans are gravitating towards ready-to-eat meals to save time, without compromising taste or nutritional value. The surge in vegetarian and vegan diets has prompted manufacturers to incorporate more plant-based options to cater to this growing demographic. This changing landscape underscores the industry’s responsiveness to consumer demands, showcasing a blend of innovation and adaptation in meeting the diverse needs of European consumers. Vegan and vegetarian meal options have seen a dramatic surge in popularity across Europe, with countries like Germany reporting a doubling of their vegan population from 2016 to 2020. The UK leads in the consumption of ready meals, highlighting an overarching trend towards convenience that spans across Europe. Furthermore, environmental sustainability has emerged as a pivotal factor influencing consumer choices, encouraging manufacturers to adopt green practices, from sustainable sourcing to eco-friendly packaging. Collectively, these trends point towards a conscious consumer base that values time, health, sustainability and inclusivity in their dietary choices. Nevertheless, the industry has been hampered by massive inflationary pressures, which have caused industry revenue to slump at an estimated compound annual rate of 3.2% over the five years through 2024, reaching €25.8 billion, including a projected 3% slump in 2024 alone. The industry’s outlook is robust, set against a backdrop of growing e-commerce and environmental consciousness. Home-delivered ready-meals are poised for growth, leveraging the power of online shopping to bring convenience and variety right to consumers' doorsteps. Additionally, the push towards sustainability is anticipated to shape the future of meal manufacturing, with companies that prioritise eco-friendly practices expected to gain a competitive edge. As the industry continues to evolve, the focus will likely remain on aligning with consumer values around health, convenience, and sustainability, ensuring that prepared meals not only satisfy hunger but also reflect the conscientious choices of a modern Europe. In all, revenue is set to recover from recent drops, growing at a projected compound annual rate of 3.3% over the five years through 2029.

This Data Set is derived from the WP4 of the AgriLink project. It is part of task T4.4 of Work Package (WP) 4 of the H2020 AgriLink project. AgriLink [Agricultural Knowledge: linking farmers, advisors and researchers to boost innovation] aims at better understanding the role of advisory services in farmers��� decision making and at boosting their contribution to innovation for sustainable development of agriculture. WP4 addresses more specifically the governance of farm advisory services. The objective of the research presented in this report is to understand the institutions that influence how farm advisory services function on the ground, and to discuss implications for the support for sustainable development innovation. Data were collected in seven European countries: the Czech Republic, France, Greece, Poland, Portugal, Spain and the UK. Data were collected for a diversity of types of innovation: Market, Technological, Process, and Social Innovation. The Data set was built based on interviews with farm advisory suppliers. In total 170 farm advisory suppliers were interviewed. The table below provides the distribution of interviews according to countries. Country Market innovation (NCRO & RETRO) Technological innovation (TECH) Process innovation (BIOP & SOIL) Social innovation (LABO & COMM) TOTAL Czech Republic 4 16 20 France 14 11 25 Greece 11 10 21 Poland 6 18 24 Portugal 11 20 31 Spain 9 29 38 UK 7 4 11 TOTAL 34 28 75 33 170 The data has two aims. First, to characterise farm advisory suppliers, in terms of (table below): what do they provide? Who is in control of the supplier? What do they provide Farmers NGO Private Public semi-public Total Advice and Bookkeeping 8 4 1 13 Advice and Digital tech 1 3 4 Advice and Education 2 4 3 5 14 Advice and Health services 1 2 3 Advice and Inputs 1 14 15 Advice and Inputs and Outputs 15 5 20 Advice and Machinery 7 7 Advice and Outputs 8 1 8 2 19 Advice and Research 2 2 5 12 1 22 Only advice and training 16 26 10 1 53 Total 53 7 76 32 2 170 Second, we have set a series of variables to characterise the services they provide. The main variables are: Number of advisors of the organisation Number of advisors Number of organisations in that group [0:5] 96 ]10:50] 35 ]5:10] 16 >50 19 n.a. 4 Total 170 Percentage of advisors in the staff of the organisation % of advisors Number of organisations [0:25[ 43 [25:50[ 17 [50:75[ 30 [75:100] 70 n.a. 10 Total 170 Share of back-office activities in the staff of the organisation Share of back-office (%) Number of organisations [0:25[ 41 [25:50[ 26 [50:75[ 66 [75:100] 24 n.a. 13 Total 170 Number of farmers client of the supplier per advisor Number of clients per organisation Number of organisation [0:25[ 31 [25:75[ 43 [50:75[ 3 [75:175[ 28 >175 36 n.a. 29 Total 170 Main advisory method Main Advisory method Number of organisations Group Advice 19 IT tool (app, software���) 2 n.a. 1 One to One Advice 129 Phone or web helpdesk 15 Publications 4 Total 170 Main funding source Main funding source Number of organisations EU funds 15 Fee-for-advice 46 Joint trade 42 Membership 11 Membership fee 6 n.a. 16 Public funding 3 Public funds 4 State budget 27 Total 170 More detailed information about the variables collected can be found in the questionnaire that is available in the appendix of the deliverable D4.2 of AgriLink

人口中普遍存在中度或严重的粮食不足：占人口百分比在12-01-2022达12.300%，相较于12-01-2021的12.400%有所下降。人口中普遍存在中度或严重的粮食不足：占人口百分比数据按年更新，12-01-2015至12-01-2022期间平均值为11.950%，共8份观测结果。该数据的历史最高值出现于12-01-2015，达14.700%，而历史最低值则出现于12-01-2018，为10.700%。CEIC提供的人口中普遍存在中度或严重的粮食不足：占人口百分比数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的葡萄牙 – Table PT.World Bank.WDI: Social: Health Statistics。

The proportion of affirmative responses for each item of the Self-Administered Food Security Survey Module for Children and corresponded thresholds according to the classes of food security status.

Scientific production of researchers from Portuguese-speaking African institutions that align with the Food and Nutrition Security Strategy of the Community of Portuguese Speaking Countries (ESAN-CPLP) .

Information criteria for each model parameterization of the food security data.