ArticleBMC public health2023
A 5-year review of prevalence, temporal trends and characteristics of individuals experiencing moderate and severe food insecurity in 34 high income countries.
Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
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Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 22 citations in OpenAlex.
- Food Insecurity in Families With Children or Young People With Autism: A Systematic Review and Meta-Analysis.Nutrition bulletin · 2026Pooled it
- Associations between food insecurity in high-income countries and pregnancy outcomes: A systematic review and meta-analysis.PLoS medicine · 2024Pooled it
- Article
- Income, food expenditure shares, and severe food insecurity in Australia across 21 waves of HILDA.Health promotion international · 2026Article
- Individual Characteristics and National Income Modify the Association between Cognitive Social Capital and Food Insecurity: Evidence from the Gallup World Poll, 2014-2021.Current developments in nutrition · 2026Article
- Multidimensional determinants of food insecurity among households in Somalia: evidence from the 2018/2019 Somalia health and demographic survey.Frontiers in nutrition · 2026Article
- Association between food insecurity and intimate partner violence: the role of gendered asset policies.BMJ global health · 2025Article
- Regional disparities and sociodemographic determinants of food insecurity in Somalia: a secondary cross-sectional analysis of a National survey.Journal of health, population, and nutrition · 2025Article
- Food (in)Security and Peripartum Health in Marginalised Neighbourhoods in Denmark: Intersectional and Biopsychosocial Perspectives From Birthing Parents and Care Workers.Sociology of health & illness · 2025Article
- A Beta Regression Approach to Modelling Country-Level Food Insecurity.Foods (Basel, Switzerland) · 2025Article
- Glycemic control is worse in rural compared to urban type 2 diabetes in Bangladesh, irrespective of food security status.Journal of diabetes investigation · 2025Article
- Scarce and unpredictable, yet obesogenic: modeling the impact of food insecurity on adiposity in mice.Obesity (Silver Spring, Md.) · 2025Article
- Feeding Practices Used by Australian Parents of Young Children Living With Food Insecurity and Household Chaos.Maternal & child nutrition · 2025Article
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- Article
- Stakeholder Perspectives on the Acceptability, Design, and Integration of Produce Prescriptions for People with Type 2 Diabetes in Australia: A Formative Study.International journal of environmental research and public health · 2024Article
- Food Insecurity Screening in High-Income Countries, Tool Validity, and Implementation: A Scoping Review.Nutrients · 2024Article
- Food Insecurity in Greece and across the Globe: A Narrative Literature Review.Foods (Basel, Switzerland) · 2024Review
- A design thinking-led approach to develop a responsive feeding intervention for Australian families vulnerable to food insecurity: Eat, Learn, Grow.Health expectations : an international journal of public participation in health care and health policy · 2024Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDue to the relatively low numbers of households in high income countries experiencing food insecurity most studies conflate the levels of severity, which masks between- and within-country differences. This study aims to describe the characteristics of individuals living in high income countries who were moderately or severely food insecure and investigates temporal trends in prevalence. It assesses these characteristics in comparison to those who were food secure.
methodsThis is a secondary analysis of data collected by the FAO Voices of the Hungry between 2014-2018. The data were collected during the annual Gallup World Polls of nationally representative samples using the Food Insecurity Experience Scale. Data from 34 highly developed, wealthy countries were analysed. The age, gender, income, education, area of residence and household structure of individuals experiencing moderate/severe food insecurity (FI), and severe FI, were compared using ANOVA, Welch's F, Pearson's Chi-square, and Linear-by-Linear Association, dependent on the variable of interest. Hierarchical cluster analysis was used to group countries according to their prevalence of moderate/severe FI, and severe FI.
resultsOverall, 6.5% of the weighted sample were moderately/severely food insecure (M-SFI), while 1.6% were severely food insecure. M-SFI individuals were present in all 34 countries, in all years and across all education levels and income quintiles. The proportion of individuals experiencing moderate/severe FI varied between years and countries. Fifteen countries showed a significant downward temporal trend in prevalence of moderate/severe FI (p < 0.001), while three countries demonstrated an increasing temporal trend driven by increasing prevalence in those aged 65 years or less (p < 0.001). Comparing individuals experiencing moderate versus severe FI showed over-representation of males, single adult households and lower household income in the severe FI group.
conclusionsIndividuals across all income, education and age categories living in high income countries are experiencing moderate/severe food insecurity, but with higher prevalence in those experiencing more disadvantage. Over the study period some countries experienced escalating while others demonstrated decreasing moderate/severe FI trends. This comparison of countries with similar economic and human development indices highlights an opportunity to investigate subtle variations in social, economic and education policy that could have profound impacts on food insecurity.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.