Exploring The Relationship Between Sociopolitical Environments & Food Security In Africa

St. Olaf College | SDS 164: Data Science 1 - Martha Zillig, Ph.D

Introduction

The sociopolitical environment of a country affects the diet and health of a country more than ever in the 21 century due to increasing levels of political unrest, conflict between countries, and changes in the availability of resources like clean water ¹. With this project, we hope to explore how the political stability of countries in Africa impact populations’ diets, including the availability of fruits and vegetables, the proportion of clean water, and the proportion of overweight adults in the 21st century.

This data analysis is important because it strives to find correlations between variables related to a country’s infrastructure and economic development to variables related to a population’s diet and health. Our specific research question hopes to explore what factors affect food outcomes by region of Africa. This is necessary to research because food security is a leading social determinant of health, with one’s environment shaping this relationship ². This work is helpful for non-profits or the UN when wanting to improve rates of malnourishment.

Our data is sourced from the FoodSystemsDashboard.org website. It is a public database led by the Global Alliance for Improved Nutrition, the Columbia Climate school, and Cornell’s University of Agriculture and Life Sciences, and the Food and Agriculture Organization of the United Nations ³. The data variables were collected from a range of over 40 sources, including the Food and Agriculture Organization (FAO), United Nations Children’s Fund (UNICEF), World Health Organization (WHO), and World Bank. More information about the data sources can be found in the Metadata which includes the indicator source, definition, its relevance and why it was included, how the variable was calculated, and also how missing variables were treated. The range of the data in the data set is 1960 to 2024. The Food Systems Dashboard data set continues to be updated with new variables, and was originally published in 2020.

The key variables we plan to examine can be grouped into two categories, variables related to food security and variables linked to the sociopolitical environment of a country. We have seven variables of interest related to food security including undernourishment prevalence, proportion with safe water, proportion of overweight adults, proportion of adults with diabetes, and the average protein supply per capita. Our variables connected to the sociopolitical environment of each respective country is the political stability and literacy rates. For each variable, we have data on each variable in each country in the world from 1980 to 2024.

Variables of Interest

Definitions of Variables

Factor	Unit	Description
Literacy_Rate	% of population	Percentage of the adult population that can read and write.
Political_Stability	Index (-4 to +2)	Index of political stability and absence of violence/terrorism.
Adult_Diabetes_Prevalence	% of adult population	Prevalence of diabetes among the adult population.
Undernourishment_Prevalence	% of population	Prevalence of undernourishment in the population.
Prop_With_Safe_Water	% of population	Percentage of the population using safely managed drinking water services.
Prop_Adult_Overweight	% of adult popultation	Percentage of the adult population classified as overweight.
Avg_Protein_Supply	grams/capita/day	Average daily protein supply per capita.

Political Stability

Figure 1. This is a scatter plot showing the relationship between Political Stability and Undernourishment Prevalence (%) in African countries from 1980 to 2015. The variable ‘political stability’ is a value that has negative values indicating political instability (the presence of conflict, terrorism, or governmental volatility) and positive values indicating stronger political stability (more peaceful conditions and governmental constancy). Data points are colored by region, and a general trend line indicates that higher political stability is associated with lower undernourishment. Data from UNESCO and World Bank, via foodsystemsdashboard.org.

Interpretation: This graphs shows the relationship between the political stability of a country and the prevalence of undernourishment in the population, grouped by region of Africa. The continent Africa was grouped by region, with a total of 5 regions including Central Africa, Eastern Africa, Northern Africa, Southern Africa, and Western Africa. Undernourishment Prevalence is the percentage of the population that is undernourished. With this graph, it is difficult to determine if there is a correlation between the political stability of a country and the prevalence of undernourishment. For each region of Africa, the plot points are fairly well distributed throughout the plot. The regression line shows that as a country becomes more politically stable, rates of undernourishment may slightly decrease throughout the continent of Africa. Further graph analysis is needed to explore our research question.

Figure 2. This is a scatter plot graph, grouped by region of Africa. In Central, Eastern, and Northern Africa, there is a positive relationship between the political stability of a country and the average protein supply per capita. The variable ‘political stability’ is a value that has negative values indicating political instability (the presence of conflict, terrorism, or governmental volatility) and positive values indicating stronger political stability (more peaceful conditions and governmental constancy). The variable average protein supply is measured in grams per capita per day. The data was compiled by the Food Systems Dashboard initiative and sourced from UNESCO and the World Bank.

Interpretation: This graph attempts to make sense of and find a better relationship between food security and political stability in Africa. Each data point represents a specific country for a given year. This graph compares the political stability of countries to the average protein supply of the population. By grouping by each region of Africa, we can see that there is a positive correlation in some regions of Africa. Central, Eastern and Northern Africa show that as countries become more politically stable on the scale, the intake of protein in diets also increases. For Southern Africa, there is a slightly positive relationship between political stability and average protein supply, while Western Africa shows neither a positive or negative correlation between the variables. Here, a potential finding is that countries with stronger political stability also have more established food systems with access to a range of protein sources ⁴. It is important to consider that diets vary greatly by region of Africa, with protein sources varying as well, which may sway interpretations of this data.

Figure 3. This is a map graph of Africa that colors countries blue/green/yellow (viridis color palette) based on the proportion of the total population that is undernourished in 2022. Undernourishment is measured as a percentage between 0-100%. If a country is dark blue, rates of undernourishment are relatively low. Countries such as Algeria, Egypt, and South Africa have the darkest blues, showcasing low undernourishment rates. The highest rates of undernourishment can be seen in Central Africa in countries like the Democratic Republic of the Congo, which has a medium blue coloring. This map, which visualizes rates of undernourishment across Africa, encourages us to further explore why there are disparities in nourishment across the continent. The data was compiled by the Food Systems Dashboard initiative and sourced from UNESCO and the World Bank.

Interpretation: This map visualizes how undernourishment varies throughout the continent of Africa, with Northern, Western, and Southern regions have relatively low rates of undernourishment. Central Africa and parts of Eastern Africa show higher rates of undernourishment in the continent. This graph provides more context for figure 2, as the proportion of data points that have negative political stability in Central Africa is significant and this graph the rate of undernourishment is high for Central Africa. This map fits with the assumption that parts of Africa that are more politically stable, such as Northern and Southern Africa have low rates of undernourishment, while regions with moderate political instability like Central and Eastern Africa, have higher rates of malnourishment as seen in this graph.

Clean Water

Figure 4. The graph shows a moderate/weak positive correlation between Year and Literacy Rate for countries in Eastern Africa. The findings of this graph provide context for the education infrastructure in Eastern Africa throughout the decades. The data was compiled by the Food Systems Dashboard initiative and sourced from UNESCO and the World Bank. Literacy rate is the proportion of adults within a country who can read and write. The graph showcases that most countries have their literacy rate increase over time. More information can be found at https://www.foodsystemsdashboard.org.

Interpretation: We have a scatterplot that showcases an overall positive trend between year and literacy rate across Eastern Africa. Generally, it seems like Seychelles and Mauritius have the highest literacy rates over time. South Sudan, a very new country, only has two observations plotted, both relatively low, around 25-30%. Burundi has one of the strongest correlations, with it’s lowest values being around 25% and it’s highest around 75%. Inherently, year shouldn’t have an effect on literacy rate, but rather, increased access to resources, increased access to good education, urban development, political stability, absence of violence, and policy changes would affect literacy rate.

Figure 5. This is a scatterplot that shows a moderate positive correlation between the proportion of safe drinking water to the literacy rate of countries throughout Africa. Both variables are measured as a percentage from 0-100%. The moderate positive correlation is best shown in the regions of Northern and Southern Africa. This graph aligns with the assumption that different parts of Africa have varying access to safe drinking water, however, there is significant variation in data points for the Central, Eastern, and Western regions of Africa. In particular, Eastern Africa has relatively high literacy rates and less access to safe drinking water. The data was compiled by the Food Systems Dashboard initiative and sourced from UNESCO and the World Bank.

Interpretation: For the Northern and Southern regions of Africa, there is a positive relationship between the proportion of safe water and literacy rates, while Central, Eastern, and Western Africa do not show a significant correlation because of more variability in each region. The moderate positive correlation is best shown in the regions of Northern and Southern Africa. This graph aligns with the assumption that different parts of Africa have varying access to safe drinking water, however, there is significant variation in data points for the Central, Eastern, and Western regions of Africa. In particular, Eastern Africa has relatively high literacy rates and less access to safe drinking water. Figure 4 provides context for the relatively high literacy rates in Eastern Africa, which is consistent throughout the region.

Conclusions

We believe that our analysis showcases some significant relationships between sociopolitical factors and food security across Africa, as well as the differences between each region. Political stability seems to be a key factor of food security, particularly in Central, Eastern, and Northern Africa. This relationship suggests that stable governments are crucial in the maintenance of food systems and better nutritional outcomes. Interestingly, this pattern is less pronounced in Southern and Western Africa. It is unclear why at this moment, but regional factors and historical contexts seemingly play important roles in this relationship as well.

The geographic disparities in undernourishment, as visualized in our maps, show that Northern and Southern regions generally experience lower undernourishment rates compared to Central Africa, where rates approach 50% in some countries. These patterns are then contextualized by our findings on literacy rates and access to safe water, which show a positive correlation in Northern and Southern Africa. The steady increase in literacy rates across Eastern Africa over time points to gradual improvements in the education system. This relationship may support the idea that better food security is an outcome of enhanced knowledge and better economic opportunities. Overall, our findings highlight the complex connection between the sociopolitical environment of a country and its food security. The regional differences we found highlight the need for ‘regionally tailored’ approaches to addressing political stability and infrastructure development to combat food insecurity across Africa.

Appendix

Figure A. The data was compiled by the Food Systems Dashboard initiative and sourced from UNESCO and the World Bank.

Figure B.The data was compiled by the Food Systems Dashboard initiative and sourced from UNESCO and the World Bank.

Figure C. A bar chart that shows the number of observations there are for each region of Africa. Each observation represents a country for a given year. Eastern and Western Africa have the highest amount of observations. Southern Africa has the least amount of observations.

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