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Life is data, data is life! The stories and insights of data experts and innovators



The US clearly stands out as the chart shows: Americans spend far more on health than any other country in the world, yet the life expectancy of the American population is shorter than in other rich countries that spend far less.


The unequal development over recent decades led to an inequality between the US and other rich countries. In the US health spending per capita is up to four times higher, yet life expectancy is lower than in all of these countries.




Life is data, data is life!



One could write an entire book on what this chart shows us. Here I want to look at one key question: why is life expectancy in the US shorter? Which causes of death are more common in the US than in other rich countries?


This is of course important but it cannot explain the growing inequality in life expectancy between the US and other countries over time. Over the last few decades, homicide rates have declined more in the US than in other rich countries. In relative terms, the faster decline of homicide rates in the US has reduced the relative difference in life expectancy between countries.


Opioid overdoses are still thankfully a relatively rare cause of death overall (it is the cause of death of 1.6% of Americans), but these deaths affect life expectancy because many victims are relatively young.


Ruhm (2017) carefully studied opioid mortality in the US on a local level and found that the availability and the prescription of opioid-based painkillers is the main driver of the opioid mortality surge in the US.4 This contributes to an explanation of both aspects that the first chart above highlights: lower life expectancy and higher healthcare costs.


Suicides are also among the few causes of death that are a high risk for younger people. The age distribution of suicides and the fact that suicides are rising in the US and falling in many other rich countries explain why this is another cause of death that contributes to the divergence in life expectancy that we are trying to explain.


Poorer Americans are already substantially worse off within the first year of life. Over the life course, the disadvantages accumulate. The inequality in life expectancy is large in the US, the difference between the poorest 1% and the richest 1% in the US is 14.6 years.7 And this income gradient in life expectancy has widened recently.


The low life expectancy of poorer Americans is a big part of why the average life expectancy in the US is lower than in other rich countries. Kinge et al (2019) study the difference between the US and Norway.8 Like the US, Norway is exceptionally rich, but it is much less unequal. As a consequence Norwegians in the lower half of the income distribution are richer than Americans in the lower half of the income distribution. The lower level of income inequality in Norway is mirrored by a lower inequality in life expectancy. The life expectancy of Norwegians in the lower-middle-income segment is about 3 to 4 years higher than the life expectancy of Americans in that same income segment.


In addition to my overview I recommend two research publications that study in detail why in terms of life expectancy the US is falling behind other rich countries.12 You can also use our extensive data presentation on causes of death to explore this yourself.


Now, in the middle of a global pandemic, there is little reason to hope that the US can reverse the recent trend of declining life expectancy. For the years ahead a focus on the high death rates of causes of deaths that kill younger people can be the starting point to get the US population back on track towards a longer and healthier life.


The latest county-by-county data on life expectancy published here by the IHME refers to 2014. Global life expectancy in 2014 was 71.4 years according to the UN.These counties have a lower life expectancy than that 1. Oglala Lakota County (Shannon County), South Dakota; 2. Union County, Florida; 3. Todd County, South Dakota; 4. Sioux County, North Dakota; 5. Buffalo County, South Dakota; 6. Owsley County, Kentucky; 7. Breathitt County, Kentucky; 8. McDowell County, West Virginia; 9. Perry County, Kentucky; 16. Kusilvak Census Area, Alaska; 10. Tunica County, Mississippi; 11. Holmes County, Mississippi; 12. Dewey County, South Dakota; 13. Coahoma County, Mississippi; 17. Wolfe County, Kentucky; 14. Leslie County, Kentucky; 15. Roosevelt County, Montana; 18. Phillips County, Arkansas; 19. Mingo County, West Virginia.


All visualizations, data, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.


Licenses: All visualizations, data, and articles produced by Our World in Data are open access under the Creative Commons BY license. You have permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited. All the software and code that we write is open source and made available via GitHub under the permissive MIT license. All other material, including data produced by third parties and made available by Our World in Data, is subject to the license terms from the original third-party authors.


Life expectancy is the key metric for assessing population health. Broader than the narrow metric of the infant and child mortality, which focus solely at mortality at a young age, life expectancy captures the mortality along the entire life course. It tells us the average age of death in a population.


Life expectancy has increased rapidly since the Age of Enlightenment. In the early 19th century, life expectancy started to increase in the early industrialized countries while it stayed low in the rest of the world. This led to a very high inequality in how health was distributed across the world. Good health in the rich countries and persistently bad health in those countries that remained poor. Over the last decades this global inequality decreased. No country in the world has a lower life expectancy than the countries with the highest life expectancy in 1800. Many countries that not long ago were suffering from bad health are catching up rapidly.


Since 1900 the global average life expectancy has more than doubled and is now above 70 years. The inequality of life expectancy is still very large across and within countries. in 2019 the country with the lowest life expectancy is the Central African Republic with 53 years, in Japan life expectancy is 30 years longer.


The population of many of the richest countries in the world have life expectancies of over 80 years. In 2019 the life expectancy in Spain, Switzerland, Italy, and Australia was over 83 years. In Japan it was the highest with close to 85 years.


Demographic research suggests that at the beginning of the 19th century no country in the world had a life expectancy longer than 40 years.2 Every country is shown in red. Almost everyone in the world lived in extreme poverty, we had very little medical knowledge, and in all countries our ancestors had to prepare for an early death.


Over the next 150 years some parts of the world achieved substantial health improvements. A global divide opened. In 1950 the life expectancy for newborns was already over 60 years in Europe, North America, Oceania, Japan and parts of South America. But elsewhere a newborn could only expect to live around 30 years. The global inequality in health was enormous in 1950: People in Norway had a life expectancy of 72 years, whilst in Mali this was 26 years. Africa as a whole had an average life expectancy of only 36 years, while people in other world regions could expect to live more than twice as long.


The three maps summarize the global history of life expectancy over the last two centuries: Back in 1800 a newborn baby could only expect a short life, no matter where in the world it was born. In 1950 newborns had the chance of a longer life if they were lucky enough to be born in the right place. In recent decades all regions of the world made very substantial progress, and it were those regions that were worst-off in 1950 that achieved the biggest progress since then. The divided world of 1950 has been narrowing.


Globally the life expectancy increased from less than 30 years to over 72 years; after two centuries of progress we can expect to live much more than twice as long as our ancestors. And this progress was not achieved in a few places. In every world region people today can expect to live more than twice as long.


Over the last 200 years people in all countries in the world achieved impressive progress in health that lead to increases in life expectancy. In the UK, life expectancy doubled and is now higher than 80 years. In Japan health started to improve later, but the country caught up quickly with the UK and surpassed it in the late 1960s. In South Korea health started to improve later still and the country achieved even faster progress than the UK and Japan; by now life expectancy in South Korea has surpassed life expectancy in the UK.


The chart also shows how low life expectancy was in some countries in the past: A century ago life expectancy in India and South Korea was as low as 23 years. A century later, life expectancy in India has almost tripled and in South Korea it has almost quadrupled.


You can switch to the map view to compare life expectancy across countries. This view shows that there are still huge differences between countries: people in many Sub-Saharan countries have a life expectancy of less than 60 years, while in Japan it exceeds 80.


In the pre-modern, poor world life expectancy was around 30 years in all regions of the world. The estimates by historian James Riley shown here suggest that there was some variation, between different world regions, but in all world regions life expectancy was well below 40 years.5


How to read the following graph: On the x-axis you find the cumulative share of the world population. The countries are ordered along the x-axis ascending by the life expectancy of the population. 2ff7e9595c


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