What does it mean to be a woman growing up in different parts of the world?
Are girls equally likely to go to school, get a stable job, survive adulthood, and live a life of dignity, regardless of whether they are in rural sub-Saharan Africa or urban Western Europe?
Believing that the real story of gender inequality often remains hidden, we wanted to shed some light on it through the lens of data. Our goal was to uncover the invisible gaps that quietly shape women’s lives, that begin in childhood across the themes of education, health and economic opportunities.
Our analysis spans from adolescent fertility to access to education, from unemployment to labor market vulnerability, and from life expectancy to poverty. Each indicator reveals a different facet of the same story.
By bringing them together, we built a broader, data-driven narrative that reveals where progress has been made and where inequality still holds women back. Our project is not just about numbers, it’s about asking difficult questions, such as:
How far have we really come in ensuring equality for women?
Through interactive visualizations, we invite you to join us on a journey of discovery: a journey that crosses continents, regions and countries. To better understand the following analysis, let’s start by exploring the first graph, which examines the relationship between adolescent fertility, employment, and enrollment levels
LET’S START WITH THE BIG PICTURE: A GLOBAL VIEW
GLOBAL FLOWS OF WOMEN’S LIVES
By clicking on a continent bubble (sized by poverty rate and colored by female life expectancy), the Sankey diagram updates to show the most frequent flows within that region. Thicker bands represent more common transitions between school enrollment, employment, and fertility levels.
Several interesting insights can be derived by playing with the dashboard: for example, Africa, the poorest continent with the lowest life expectancy for women, shows extremely high fertility, along with high enrollment and high employment. Europe, which has the highest life expectancy and the lowest poverty rate, shows a far lower fertility rate, although employment and enrollment are both high.
ZOOMING IN: DISPARITIES ACROSS REGIONS
The Radar Chart compares average adult mortality rates by gender across global regions. While male mortality consistently exceeds female mortality, some regions: Sub-Saharan Africa or Southern Asia, for example, show unusually high female rates, highlighting important regional disparities in women’s health and survival.
The second chart shows a global drop in fertility rates from 1960 to 2020. Again, some regions like Sub-Saharan Africa stand out with the highest rates throughout the period, showing a slower decline compared to other regions. So, we can conclude that women’s fertility and mortality rates often go hand in hand. This persistently high fertility may be linked to high adult mortality, as seen in the radar chart, where Sub-Saharan Africa also shows the highest death rates for women.
Fertility trends by Regions and Countries
To complement the line chart above, which shows a steady global decline in fertility rates across regions from 1960 to 2020. This race chart was created to explore country-level variations within each region.
While the overall trend is remarkably consistent across continents, the race chart allows us to zoom in and check for discrepancies within regions.
What we observe is that most countries within the same region follow a similar downward trajectory, suggesting a regionally cohesive transition.
However, a few notable exceptions emerge, particularly among Northern Europe countries, where fertility declines are more uneven and in some cases significantly delayed.
Here you can also use the toggle at the top to sort countries from highest to lowest fertility rate, or the opposite.
White Hat vs. Black Hat: The Power of Framing
This scatterplot reflects a white hat perspective by highlighting how higher female secondary school enrollment is strongly associated with lower job vulnerability. Each region is represented by a distinct symbol, and the downward trend emphasizes the ethical importance of investing in female education to promote more stable and equitable employment outcomes worldwide.
This scatterplot represents the black hat perspective, focusing on selected developing regions and showing that higher female education levels rarely lead to lower job vulnerability. It would seem that in several cases, women face high employment insecurity despite relatively strong school enrollment rates. Thus, one could think, wrongly, yet seemingly supported by the data, that the problem lies with women themselves. Maybe they’re choosing the wrong subjects, or failing to adapt to labor market demands. The data may be real, but the story told with them can be subtly manipulative, reinforcing harmful narratives under the guise of neutrality.
COUNTRY-LEVEL DETAIL
This interactive bubble chart shows the relationship between female school enrollment and female employment rates from 1990 to 2019. We selected a few top-performing and underperforming countries to highlight the stark differences in trends across the years.
This interactive map provides a global overview of economic inequality, measured by the Gini Index. This index, ranging from 0 (representing perfect equality) to 100 (representing maximum inequality, as used in this scale), assesses how income (or wealth) is distributed among a country’s population.
The map highlights significant regional differences. For instance, many European countries tend towards greener shades, while several nations in Latin America and Southern Africa display warmer colors, indicating greater challenges related to economic inequality.
Last but not least, we have implemented an original visualization that you can easily download by clicking the button
Conclusions
Returning to our original question, What does it mean to be a woman growing up in different parts of the world?
We’ve seen that the answer depends on a complex constellation of factors: access to education, job security, fertility expectations, mortality risks, and broader economic inequality.
Our project doesn’t claim to provide a single truth, but rather to make visible the layers of disparity that shape women’s lives globally.
From the persistent vulnerability in Sub-Saharan Africa to the more stable conditions in Northern Europe, the contrasts are striking, but not random. They’re the result of systemic patterns, not individual choices.
Through interactive storytelling and symbolic visuals, we hoped to turn data into empathy, and charts into questions.
And most importantly, we hope this journey reminds us that behind every statistic is a life, a context, and a possibility for change.