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READ: Data Exploration - Life Expectancy

Life expectancy has increased a lot since 1900. Which countries have benefited the most? This article introduces you to a chart that measures life expectancy around the world.
The data exploration article below uses “Three Close Reads”. If you want to learn more about this strategy, click here.

First read: preview – what do we have?

This will be your quickest read. It should help you get the general idea of what this chart is about and the information it contains. Pay attention to:
  • Labels and titles. What is the title? How are the axes labeled? Is anything else on the chart labeled?
  • Data representation. How many variables are there and what are they? What are the scales? What time period does the chart cover? Is the chart interactive?
  • Data source. Where did the data for this chart come from? Do you trust it? Who created the chart?

Second read: key ideas – what do we know?

In this read, you will pay attention to the information that most helps you understand the chart and the information it is trying to convey. Pay attention to:
  • Claim(s). What can you say about the data? What story does it tell? Can you make any claims about this data? Does it change when you zoom in compared to when you look at the data as a whole?
  • Evidence. What data from the chart supports this story? Does this change if you change the scale or variables?
  • Presentation. How does the way this chart is presented influence how you read it? Has the author selected certain variables or scales that change the conclusions that can be drawn? Is there anything missing from this chart?
By the end of the second read, you should be able to answer the following questions:
  1. How has life expectancy changed in the last 500 years?
  2. What periods saw the most dramatic increases in life expectancy? What events might have caused this?
  3. What does this chart tell you about inequality between regions and nations?
  4. According to the chart, has life expectancy been increasing since 1543? What evidence can you find in the chart to support or challenge this claim?
  5. Many of the countries on this chart have no data before 1900. Yet, the chart includes “World” data all the way back to before 1800. Do you think we can trust this data? How do you think the makers of this chart might have made estimates for global life expectancy from incomplete data?

Third read: making connections – what does this tell us?

The third reading is really about why the chart is important and what it can tell us about the past and help us think about the future. Pay attention to:
  • Significance. Why does this matter? Does this impact me, and if so, how? How does it connect what is going on in the world right now? How does it relate to what was happening at the time it was created?
  • Back to the future. How does this data compare to today? Based on what you now know, what are your thoughts on this phenomenon 25 years, 50 years, and 100 years from now?
At the end of the third read, you should be able to respond to these questions:
  1. Why does this chart matter? What do these changes in life expectancy tell us about world history? Does the quality of the data tell us anything about inequality among different regions?
  2. Using this chart, make one prediction about how life expectancy will change in your lifetime. What evidence from the chart supports your prediction? What evidence challenges it?
Now that you know what to look for, it’s time to read! Remember to return to these questions once you’ve finished reading.

Life Expectancy Data Introduction

Black and white photograph of an old man and woman adjusting a clock.
Max Roser, adapted by Eman M. Elshaikh
Life expectancy has increased a lot since 1900. Which countries have benefited the most? This article introduces you to a chart that measures life expectancy around the world.
How do we know if a population is healthy? Scientists and analysts use all kinds of data to answer this question. One key measure of a population's health and well-being is life expectancy. Life expectancy measures the average age a person born today could expect to live to if the average age of death did not change over their lifetime. Life expectancy can vary quite a lot in different places and in different eras. In fact, for much of human history, life expectancy was pretty short. Before the modern era, life expectancy was about 30 years, all around the world! This was even true of the countries that today are the richest in the world. High child mortality rates were a big part of the reason for short life expectancy. A lot of people died very young. Since 1900, the global average life expectancy has more than doubled and is now above 70 years.
Life expectancy changed, both globally and regionally, in the past few hundred years. After industrialization, people in some regions started to experience longer and longer lives. Life expectancy had previously been fairly equal around the world — all countries had similarly short life expectancies. But after industrialization, life expectancy started to become more unequal. The populations living in industrialized countries became much healthier and experienced longer life expectancies. This left many poorer countries in the world far behind. Recently, however, this gap has been closing as health has improved across all countries in the world.

Changes in life expectancy

The line chart below shows the dramatic increase in life expectancy over the last few centuries. For the United Kingdom (UK) — the country for which we have the earliest data — we see that before the nineteenth century, there was no real improvement in life expectancy. Life expectancy stayed between 30 and 40 years.
Chart 1:
Chart showing how life expectancy has improved dramatically from 30 to 40 years in 1543 to 70 to 80 years in 2015.
Explore at: https://ourworldindata.org/grapher/life-expectancy By Our World in Data, CC BY 4.0.
Over the last 200 years, people across the world have seen massive improvements in health, leading to an increase in life expectancy. In the UK, life expectancy doubled and is now more than 80 years. In Japan, health started to improve at a later date than the UK, but the country caught up quickly and surpassed it in the late 1960s. Health improvements started even later in South Korea, but that country achieved even faster progress, and it too has now surpassed life expectancy in the UK.
The chart gives evidence that allows us to make comparisons between regions and across historical eras. We can see that a century ago, life expectancy in India and South Korea was as short as 23 years. A century later, life expectancy in India has almost tripled; in South Korea, it has almost quadrupled. If you view the chart online, you can switch to the map view to compare life expectancy across countries. This view shows that there are still huge differences between countries: In sub-Saharan Africa, the average life expectancy is less than 50 years, while in Japan, it's more than 80.
Author Bio
Max is the founder and director of Our World in Data. He began the project in 2011 and for several years was the sole author, until receiving funding for the formation of a team. Max’s research focuses on poverty, global health, and the distribution of incomes. He is also Programme Director of the Oxford Martin Programme on Global Development at the University of Oxford, and Co-executive Director of Global Change Data Lab, the non-profit organization that publishes and maintains the website and the data tools that make OWID’s work possible.

Want to join the conversation?

  • leaf green style avatar for user Leo Williams
    Is this relevant to the 1500s-1700s, or is this meant to be in the next unit?
    (4 votes)
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  • blobby green style avatar for user ealmaguer
    Max is the founder and director of Our World in Data. He began the project in 2011 and for several years was the sole author, until receiving funding for the formation of a team. Max’s research focuses on poverty, global health, and the distribution of incomes. He is also Programme Director of the Oxford Martin Programme on Global Development at the University of Oxford, and Co-executive Director of Global Change Data Lab, the non-profit organization that publishes and maintains the website and the data tools that make OWID’s work possible.
    (1 vote)
    Default Khan Academy avatar avatar for user