Measure global hunger

Add data on undernourishment

The first measure of hunger that you'll map is the prevalence of undernourishment. When global discussing hunger, undernourishment is one of the most important measurements to consider.

  1. Go to Sustainable Development Goal 2.1.1: Prevalence of undernourishment (percent).

    The map's preview page opens.

    You can also find this data by going the main hub site,; clicking Zero Hunger; and searching for the dataset, Prevalence of undernourishment (percent).

  2. On the preview page, click View Full Details.

    View Full Details button

    The full details page opens. This page contains metadata about the map, including map description, data attributes, and more.

  3. On the full details page, scroll down to the I want to section and click Create a Map. Choose Advanced Mapping.

    Advanced Mapping option

    The Start Simple option opens a map similar to the one you saw on the preview page with simple annotation tools. The Advanced Mapping option you chose opens the map in ArcGIS Online so you can perform analysis on this data later.

    Indicator 2.1.1 in ArcGIS Online


    This map opens in Map Viewer. This is one of two map viewers offered by ArcGIS Online for viewing, creating, and using maps.

    On this map, the percentage of the population that is undernourished is shown with graduated symbols for countries that have reported data. The larger the circle, the more prevalent undernourishment is in the country. Based on a visual analysis of the map, what countries look like they have the biggest problem with undernourishment? What countries haven't reported data?

    There are lots of overlapping points on the map, so it's difficult to tell what each is showing. Because this data is normalized, given in the form of a percentage, you can also choose to show it as polygon features with graduated colors. First, you'll need to sign in to your ArcGIS organizational account.

  4. On the ribbon, click Sign in and enter the credentials for your ArcGIS Online account.

    If you don't have an organizational account, you can sign up for an ArcGIS free trial.

    The map reloads. Next, you'll add polygon data to use as each country's boundary. The layer you're looking for is maintained by Esri and stored in ArcGIS Living Atlas. ArcGIS Living Atlas of the World is an authoritative collection of geographic data, including layers, maps, and apps.

  5. On the ribbon, click Add and choose Browse Living Atlas Layers.

    Browse Living Atlas Layers option

  6. In the Living Atlas pane, search for Countries and add World Countries (generalized).

    Add button

    The World Countries layer draws on top of the map.

  7. In the Living Atlas pane, click the back arrow. In the Change Style pane, click Done.

    The Contents pane appears with the two layers listed. Normally, you'd reorder the layers to show point data on top of polygon data, but you won't need the points much longer. Now that you have polygon data, you'll use the Join Features tool to add the data from the Prevalence of undernourishment layer to the country polygon layer.

  8. On the ribbon, click Analysis.

    Analysis button

  9. In the Perform Analysis pane, expand Summarize Data and click Join Features.

    Join Features tool

    A join is a way to combine your data, based on either shared attributes or location. You'll connect the data values from the undernourishment dataset to the polygon shapes of the country layer. To do this, you'll use a spatial join, which means that the data for each point will be added to the polygon it overlaps.

  10. For Choose target layer, ensure the World Countries layer is chosen.
  11. For Choose layer to join to target layer, choose the Indicator 2.1.1 layer.
  12. For Select the type of join, choose Spatial Relationship and choose Completely Contains.

    Join Features parameters

    Choosing Completely contains as the spatial relationship ensures that none of the overlapping symbols are added to the wrong country. Because each point symbol originates in the centroid of the country, each country polygon will only completely contain one data point.

  13. For Choose join operation, confirm that Join one to one is chosen.

    This parameter further specifies that there is only one record in the Indicator layer that needs to be joined to the Countries layer. Because you already only have one data point per country, you don't need to change the Define which record is kept parameter.

  14. For Result layer name, change the layer name to Undernourishment and add your initials.

    Each layer must have a unique name. Adding your initials is a way of making your result layer name unique.

  15. Uncheck Use current map extent. Click Run Analysis.

    Run Analysis button

    When the tool is finished running, the layer is added to the Contents pane.

  16. In the Contents pane, uncheck the World Countries and Indicator layers to turn them off.

    Map showing the results of the Join analysis

    Now it is more clear which countries do not have reported data. Countries without a polygon outline weren't added to the join output layer because they didn't have data in the Indicator layer. Many of the countries without reported data are in Africa, though there are several others. Now you'll change the symbology to show where undernourishment is most prevalent.

  17. Point to the Undernourishment layer and click Change Style.

    Change Style button

    The Change Style pane appears. Currently, the map shows just the location of the data. To map the amounts, you'll change the attribute to symbolize. For this map, you'll use the Latest Value field. This field has the most current reported data value for each country, so the latest date of reporting may vary. If you want to explore the reported data values for individual countries, you can open the attribute table and select the country.

  18. For Choose an attribute to show, choose Latest Value.

    The map automatically redraws to show default symbology for the Counts and Amounts (Color) style. On this map, the darkest blues show where undernourishment is most prevalent. This symbology is also called graduated colors.

  19. Click Done.

    Map showing undernourishment by country in graduated color symbology

    What do you see on this map? Which countries have the highest rates of undernourishment? Are you able to see any patterns in the data that weren't as clear before?

  20. Click different countries on the map to read information about them, including the Latest Value attribute.

    According to the data, the top five countries whose populations are experiencing undernourishment are Haiti (48.2 percent), North Korea (47.6 percent), Madagascar (41.7 percent), Chad (39.6 percent), and Liberia (37.5 percent). These places are located all over the world, and have varying reasons for the high prevalence of undernourishment.

    Why do you think these countries might be facing high percentages of undernourishment? Are there specific events in recent history that might be tied to these rates?

    Often when discussing hunger, the conversation focuses on undernourishment and similar measures of severity. But food access isn't just a problem across the Southern Hemisphere, where it appears most prevalent. In the next section, you'll map a different metric, food insecurity.

Compare food insecurity

To get another perspective on where people are experiencing hunger, you'll also map food insecurity. As defined by the UN, food insecurity is "the extent to which people have difficulties in accessing food of adequate quality and/or quantity due to lack of money or other resources. Difficulties include also psychological concerns associated with the struggle in accessing food." Access to food can be limited by many social and economic factors, from not having enough money to buy food to social unrest and famine causing a lack of food availability.

  1. On the ribbon, click Add and choose Search for Layers.
  2. Click My Content and choose ArcGIS Online.

    ArcGIS Online option

    This layer is published to ArcGIS Online.

  3. Search for severe food insecurity and add the Indicator 2.1.2: Prevalence of moderate or severe food insecurity in the adult population (percent) layer owned by unstats_admin.

    Data for Indicator 2.1.2

    You can also find this data on the UN Sustainable Development Goals site at Indicator 2.1.2: Prevalence of moderate or severe food insecurity in the adult population (percent).

  4. In the ArcGIS Online pane, click the back arrow.

    Map showing food insecurity data

    How does the prevalence of severe food insecurity layer compare to the prevalence of undernourishment layer in each country? Notice that some countries have reported food insecurity data and not undernourishment—why do you think this is?

    Where data is available, many countries disaggregate the data by sex, so many countries have three data points. For the attribute Sex Desc, the values Female and Male account for people over the age of 15 of each sex. For the value Both Sexes, data is reported as a percentage of the population, regardless of age.

  5. In the Contents pane, uncheck the Undernourishment layer to turn it off.
  6. Click the points for different countries to explore the data. Read the pop-ups, and if necessary, click the arrows to see how the data varies by sex.

    Pop-up arrow

    While the percentage of people experiencing food insecurity is relatively low in many countries in the Northern Hemisphere, there is more variety in this data. Why do you think food insecurity is important to pay attention to?


    To continue this analysis, you can follow the same process to join the Indicator 2.1.2 layer to the World Countries layer.

Hunger is a critical challenge all over the world, though it varies in both severity and the way it's measured. Undernourishment is undoubtedly the more urgent indicator to monitor and address, and is caused and exacerbated by different factors that should be addressed differently than food insecurity. As the UN works toward the goal of ending hunger and achieving food security, both of these indicators are necessary to factor into creating sustainable, long-term solutions.

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