Food Security Index data explorer and methodology

On this page we have collected together a number of visual representations of the Food Security Index data for those interested to explore and make comparisons themselves, plus the methodology behind the index's development. We have extensive experience helping national and local governments increase their food security and climate resilience, and welcome interest in the index.

IIED Food Security Index

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Delve into the data

Explore the Food Security Index data through a set of interactive maps and scatter charts that let you examine patterns, compare countries and uncover how food security and climate vulnerability intersect. These visual tools are designed for anyone who wants to go beyond the headline findings and investigate the data in more depth for themselves.

By navigating the charts, you can compare countries across regions and income groups, identify outliers, and better understand the structural inequalities and climate risks shaping food security outcomes.

Explore food security levels across 162 countries by overall Food Security Index score and the four pillars of availability, access, utilisation and sustainability. Toggle between baseline and warming scenarios (1.5°C, 2.0°C, 4.0°C) to see how projections shift; use the 'highlight groups' option to draw attention to Fragile and Conflict-Affected States (FCAS), least developed countries (LDCs) and Small Island Developing States (SIDS) – multiple groups can be selected simultaneously. Hover over any country for details.

The highest five scoring countries on the Food Security Index. Hover over the bars to see each country's exact score

The lowest five scoring countries on the Food Security Index. Hover over the bars to see each country's exact score

Examine the correlation between the climate change risk index and the overall Food Security Index for different country groups. Toggle the country groups or hover over countries to see the climate risk and Food Security Index scores.

Examine the correlation between the Food Security Index and greenhouse gas emissions for different country groups. Toggle the country groups or hover over countries to see the climate risk and Food Security Index scores.

Methodology

Our methodology is based on a four-pillar food security framework consistent with the UN Food and Agriculture Organization’s (FAO) approach, which is also widely adopted in the literature. 

For each pillar we created a sub-index using data from more than two dozen datasets produced by organisations such as INFORM, the World Bank, the UN Development Programme, FAO, World Health Organization and UNICEF. A full list of data can be found in the box below.

  • Food Production Index
  • Crop Production Index
  • Average dietary energy supply adequacy (%)
  • Value of food imports in total merchandise exports (kcal per capita per day)
  • Fat grams per capita per day
  • Protein grams per capita per day​
  • GDP per capita
  • Human Development Index
  • Development and deprivation score
  • Gender Inequality Index
  • Income Gini coefficient
  • Access to electricity (% of population)
  • Infrastructure Index
  • Adult literacy rate
  • Internet users (% of population)
  • Mobile cellular subscriptions (per 100 people)
  • Under-5 mortality rate (per 1,000 live births)
  • Prevalence of undernourishment (%)
  • Maternal mortality ratio
  • Immunisation Coverage Index
  • Lack of access to healthcare index
  • Health of children under 5
  • Current health expenditure per capita
  • People using at least basic sanitation services (% of population)
  • People using at least basic drinking water services (% of population)
  • Hazard and Exposure Index
  • Conflict Probability Index
  • Current Conflict Index
  • Most recent Hyogo Framework for Action scores (index)
  • Lack of institutional stability index
  • Lack of government effectiveness index
  • Corruption Perception Index
  • Public aid per capita (US$)
  • Net official development assistance received (% of gross national income)
  • Volume of remittances (in US$) as a proportion of total GDP (%)

These disparate sources were normalised using the x/max x method, dividing the values for all 162 countries analysed by the dataset maximum. This produced scores ranging from 0 (worst) to 10 (best). Higher-is-worse indicators, such as child mortality, were reversed before normalisation.

We used ordinary least squares and regressed each dependent variable (meaning all four pillars and the composite scores) separately on the same set of independent variables to ensure comparability of results.

The F-statistic was used to test overall model significance and the coefficient of determination (R²) to test explanatory power. We used standard t-tests to evaluate the statistical significance of individual coefficients.

To investigate the effects of climate change on food security, we generated three projections consistent with the Intergovernmental Panel on Climate Change’s warming scenarios of 1.5°C, 2°C and 4°C. We used the INFORM Risk Framework to derive scenario-specific values of the CRI that reflect projected increases in climate-related hazards. Countries’ non-climate structural characteristics were held constant.

The resulting food security scores were based on the estimated marginal effect of climate risk obtained from the regression analysis. Rather than re-estimating the indices mechanically, the approach applied partial-effect adjustments to observed index values, thereby preserving observed country-specific baselines.

Since the food security scores are bounded measures, we truncated to zero projected values that fell below zero to preserve interpretability and keep projections within the index scale.

The resulting scenario-adjusted scores represent counterfactual outcomes under alternative climate risk conditions. They don’t represent precise forecasts but illustrate the direction and magnitude of potential climate impacts on different dimensions of food security.