By Stephen Holzman

People have sex.

This has been linked to later giving birth in some cases.

Behold this chart:

Historical Fertility Rates

Source: Human Fertility Database (As of January 27, 2016)
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You can also view multiple years at once if you would like!

TLDR; Number of babies being born around the world per woman has mostly been going down! Age of moms is going up!

Fertility rates are a measure of the number of children being born into the world, but there are a few different types that might cause confusion if you are not the kind of person that reads Population and Development Review for fun.

1. Age-Specific Fertility Rates

Age-Specific Fertility Rates are relatively straight-forward and the main focus of the interactive chart above. An ASFR for a given age in a given year is the number of babies a woman that age would have birthed on average that year. ASFRs tend to be pretty small, although as a Facebook user in my mid-twenties it sometimes does not seem this way.

The overall size of the blobs indicate the size of the Total Fertility Rate. The shifting peaks in the blobs show the age most women in a particular country are having babies.

2. Total Fertility Rates

This is the simple one-number statistic you are most likely to be familiar with. The Total Fertility Rate for a given year is the sum of all the ASFRs, in other words the average number of children a woman would have if the age-specific rates were held constant throughout her reproductive years assuming she survives to live them.

The exact TFR for a given country in a given year can be viewed on the country selection table.

3. Cohort Completed Fertility

Of course, Age-Specific Fertility Rates are anything but constant. Cohort completed fertility is what actually happens for women born in a given year. It is possible for a population’s total fertility rate to drop not because people are having fewer babies over the course of their lives, but because they are just delaying pregnancy until later in life.

This chart does not show cohort completed fertility or how many total babies on average are projected to be born to women still in their reproductive years.

What you should look for in this chart.

Fertility rates are at the heart of a phenomenon called “The Demographic Transition”. The countries in the Human Fertility Database are mostly developed countries that have seen their TFRs transition from as high as 6, 7, or 8 to below 2 in some cases as mortality rates drop and life expectancy increases. The detailed age-specific data has only been collected relatively recently (and even then only reliablly so in developed countries), but it captures how many different paths countries can take during their own Demographic Transition.

Some suggested country pairings:

  • Germany and Russia: In 1959, the two countries had very similar ASFR curves and TFRs. By 2006, they still have similar TFRs even though Russian mothers tend to get pregnant a bit earlier in life.

  • Taiwan and Sweden: Taiwan’s transition is happening at breakneck speed and is now much lower than even Demographic Transition pioneers like Sweden. In 1976, Taiwan’s TFR was 3.06 and Sweden’s was 1.68. In 2010, Taiwan is at an extremely low .89 while Sweden actually climbed to 1.99.

  • United States and Canada: It’s impossible to talk about fertility rates without mentioning the Baby Boom. It drastically changed what at least the next century of population age-distributions will look like. The bubble that starts in the 1940’s was especially felt by the United States and Canada.

Why does this matter?

Speaking of population age-distributions, behold this other chart:

Historical Population Age-Distributions

Source: Human Mortality Database (As of February 8, 2016)
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Note: "YEAR-" and "YEAR+" indicate country border changes

People talk about aging populations, shrinking workforces, and the relative size of certain generations because humans are changing their babymaking habits. Changes in fertility rates have ripple effects for centuries, but most of human history has had relatively stable population age-distributions to go with their stable fertility rates. Only recently have fertility changes happened fast enough to be especially disruptive to age-distributions.

Some countries to look at:

  • Sweden: That flare at the base in 1751 is caused by high child mortality, or in other words kids that never made it to adulthood. It slowly fades away over time. Who needs high fertility rates when almost all children survive to adulthood?

  • Italy: In the absence of solid birth recordkeeping, a lot of people tend to forget how old they are. When asked for an age on surveys or censuses, these people might answer in rounded ages to the nearest 0 or maybe 5. Demographers call this “age-heaping”.

  • Japan: What an “old” population distribution looks like. Population growth is a lot easier on society than shrinking populations.

  • England/Wales Civilians, France Civilians, United States: Note the dip in the Male population during the World Wars. More information about how each country counts people can be found on the Human Mortality Database website and on individual government websites.

What about countries not in these databases?

The Human Mortality Database and Human Fertility Database contain detailed information from countries that have historically kept good population records. They are constantly being updated and new countries will become available for these charts as they are published. This data also happens to be particularly easy to work with, so I chose them for the first round of charts.

They are far from the only data sources available. This page and all future “Trends” posts on Charts On Charts are living posts intended to be a basic primer for particular topics. If you happen to teach, feel free to use these charts as you see fit.

The next visualizations to be added to this post will be based on United Nations fertility data and explore how other developed countries and way more developing countries are uniquely experiencing the transition to lower fertility rates.

Stephen Holzman

Stephen Holzman
Data. Code. Art. Curious about the world and the people in it.

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