Gender Inequality and Global Food Security
Areas all around the world have been suffering from the harsh effects of food insecurity. In fact, the global food crisis exploded in 2007 and prices of main commodities went through significant increases on global markets. The crisis has not only spiked in recent years but also disproportionately affected poor women, who were much more vulnerable in the impact of the global food price crisis. While various food insecurity contributors such as growing populations, desertification, urbanization, and more have already been identified, there should be more research on the effects of gender inequities on the food security of a local population.
Thus, the purpose of this research paper is to find out if gender equality is directly related to food security with updated and comprehensive data. The main research question in this report is: Is systematic gender inequality a factor that contributes to the food insecurity of a country?
The central hypothesis to my research question is that gender equality in a community is positively correlated with food security. When women lack rights and opportunities, “their contribution to measured economic activity, growth, and well-being is far below its potential, with serious macroeconomic consequences” like food insecurity. On the other hand, working women boost the strength of the economy, add wages to households, and allow for overall greater access to nutritious food in households. Furthermore, countries with more misogynistic cultures also subdue the education of women; thus, women who are less educated would have a harder time taking care of children and understanding the nutrition requirements of young children. For example, in India, children whose mothers have minimal education tend to have a lower nutritional status than do children of more-educated mothers, even after controlling for other demographic and socioeconomic variables. Therefore, there should be a positive correlation between gender equality and food security.
Four datasets have been used to test the hypothesis that increased gender equality will lead to better food security. These datasets are various measurements of countries in the United Nations. Two datasets are used to measure gender equality/inequality. One dataset is used to measure food security. And the last dataset is a list of every country’s gross domestic product (GDP).
The first dataset is the gender inequality index (GII), which was created by the United Nations Development Programme. The gender inequality index is a holistic evaluation of a nation’s gender inequality (Human Development Reports 2016). The index is created through three different areas that are vital to gender equality: reproductive health, empowerment, and economic status. Reproductive health is measured by “maternal mortality ratio and adolescent birth rates,” empowerment is measured by the proportion of females who hold parliamentary seats and hold some secondary education, and economic status is measured by the female labour force participation rate. Through these three variables, the country’s GII is rated from 0 to 1, with 0 being full gender equality and 1 being full gender inequality.
The second dataset to measure gender equality/inequality is the female share of paid employment in non-agriculture (Human Development Reports 2016). It is also an indicator of gender equality because it represents the relative economic status of women in the population. The purpose of this dataset is to find a more specific correlation between the economic status of women and food security.
The third dataset includes measurements of food security. The dataset comes from the Food and Agriculture Organization of the United Nations, and includes around twenty measurements of a country’s food security in terms of its availability, access, stability, and utilization (Food Security Indicators 2016). For the sake of this report, six of those twenty measurements are used; the measurements are the average dietary energy supply adequacy (availability), the prevalence of undernourishment, per capita food production variability (stability), domestic food price index (access), percentage of children under 5 years of age who are underweight (utilization), and domestic food price volatility (stability). These indicators not only are the most important indicators when it comes to evaluating the country’s food security, but also have the most amount of information available in the FAO database.
The fourth dataset is relatively simple and just includes each country’s gross domestic product per capita (GDP) (Human Development Reports 2016). This measurement is used to evaluate the relative wealth of the average individual in a certain country.
To evaluate the correlation of these four datasets, a Python program, as seen in Figure 1., was created that cross-referenced the countries and formed a consolidated spreadsheet of each country and its measurements (gender inequality index, gender unemployment ratio, food security indicators and GDP per capita). The spreadsheet can be seen in Figure 2.
Using the statistical software, JMP, multiple regression models were run using these variables. GII stands for Gender Inequality Index, and FSE stands for Female Share of Employment.
A multiple regression model essentially shows the effects of multiple explanatory variables on one response variable. The reason why GDP per capita is used as the second explanatory variable is because it distinguishes the causation from increase in wealth from increase in gender equality. Thus, if the gender inequality measurements are found to be statistically significant in a certain model, it can be concluded that the correlation is due to changes in gender equality, not because of a confounding variable like the economic status of a nation. This will help clarify the relationships among the different variables.
Lastly, I will synthesize my findings with the current research that has been done in the field. There currently has been some research done that examines the relationship between gender inequality and food security; thus, it will be beneficial to combine the two and see how the research in this report adds to the current progress in the field.
After running the models, it can be concluded that gender inequality does have a tangible impact on the food security of a region when accounting for the confounding effects of GDP per capita. Statistically significant correlations exist between gender inequality and two fields of food security (models 4, 5, 10, 11) - domestic food price index and the percentage of children under the age of 5 years who are underweight. Both the gender inequality index and the female share of paid employment variables are statistically significant for the domestic food price index and the percentage of children under the age of 5 years who are underweight. This report will show the results of the more statistically significant X variable; the gender inequality index was more statistically significant in model 5 than the female share of paid employment in model 11, and the female share of paid employment was more statistically significant in model 10 than in model 4. All other models were found to not be statistically significant.
The equation can explain roughly 62% of the variation found within the percentage of children under 5 years who are underweight data. As seen in the predicted vs. actual plot in Figure 4., the predicted line of the equation lies relatively close to the actual points of the data; this means that there is a strong correlation among the gender inequality index, GDP per capita, and the percentage of children under 5 years who are underweight. When the GDP per capita is held equal, a .1 increase in the gender inequality index will lead to a .609% increase in the percentage of children under 5 who are underweight. This means that countries that have greater gender inequality also have a higher proportion of children who are underweight, even when the country’s economic status is accounted for. This shows a direct relationship between the gender inequality index and children’s food security. Meanwhile, a 1% increase in the GDP per capita will lead to .26% decrease in the percentage of children who are underweight. Once again, this logically makes sense because a wealthier nation can take better care of its children.
Model 10 has an adjusted r-squared value was .752, which means that roughly 75% of the variation found within the food price index data can be explained by this equation. As seen in the predicted vs. actual plot in Figure 5., the predicted line of the equation lies relatively close to the actual points of the data; this means that there is a strong correlation among the female share of paid employment, GDP per capita, and the domestic food price index. The variable coefficients show how changes in each variable affect the domestic food price index while the other variable is held equal. When there is no change in the GDP per capita (to prevent any confounding), a .1 increase in the female share of paid employment translates to a -.644 decrease in the domestic food price index. This shows that more paid employment for females in a region will decrease the relative price of food commodities, which means that food more easily accessible by the local population. Furthermore, a 1% increase in the GDP per capita (putting the variable in a logarithmic function shows percentage increase) will lead to a -2.11 decrease in the domestic food price index. Logically, this makes sense. A wealthier nation will have better access to food commodities.
Current Progress in the Field
This report is meant to add on to the current progress that has been made in current research regarding the role of women in food security. Women are incredibly important in any type of household, and familial health is reliant on the presence of women. Studies have shown that poor households headed by women often succeed in providing more nutritional food for their children than those headed by men. This study has also separated the effects of gender equality on specifically the nutrition of a household. Women’s nutrition among countries that have roughly the same incomes can have varying levels of nutrition due to cultural norms about eating and women’s low social status [that can] affect women’s diets. This information supports the research that has been done in this report. The problem of food security is not simply economic, but also from a whole range of gender inequities that contribute to poor nutrition, lower child mortality rates, etc.
Furthermore, gender inequality hinders a population’s productivity, and the prevention of women from working and farming has led to higher levels of poverty and food insecurity. Since many women in impoverished countries cannot have access to land and services required for rural livelihoods, they are unable to use their time and energy on food production and other income opportunities. This aligns well with the data from this report. The report has shown that countries with a lower share of females in paid employment also have a higher domestic food price index, meaning that it is significantly more difficult to access food commodities. When populations have trouble accessing basic food necessities, they are more vulnerable to shocks and less well positioned to respond to the effects of climate change or other rapid changes in the environment.
Food insecurity is an extremely complex problem with a multitude of economic, political, and social contributors that cannot all be immediately addressed at once. However, it is clear that one important contributor towards food insecurity is gender inequality. Through the analysis that has been done in this report, it can be determined that broad gender inequalities that encompass poor reproductive health and less political empowerment are heavily linked to child malnutrition in the region (lower gender inequality index leads to higher percentage of children under 5 years who are underweight). And more specifically, countries that have less economic opportunity for women experience higher domestic food price indices (lower female share of paid employment leads to higher prices for food commodities). This demonstrates that with less women in the labor force, necessary food commodities are more expensive and harder to access. Looking forward, to achieve food security, there must be economic development and agriculture to contribute to GDP inclusively and sustainably. There should also be intervention that gives women more equal representation with men as decision-makers in rural institutions and in shaping laws, policies and programs. By promoting economic empowerment and reducing gender inequities for women, the world will be one step closer to global food security.