Age Structure

First published in September 2019.

The global population pyramid

In 1950 there were 2.5 billion people on the planet. Now in 2019, there are 7.7 billion. By the end of the century the UN expects a global population of 11.2 billion. The visualization of the population pyramid below makes it possible to understand this enormous global transformation.

Population pyramids visualize the demographic structure of a population. The width represents the size of the population of a given age; women on the right and men to the left. The bottom layer represents the number of newborns and above it you find the numbers of older cohorts. Represented in this way the population structure of societies with high mortality rates resembled a pyramid – this is how this famous type of visualization got its name.

In the darkest blue you see the pyramid that represents the structure of the world population in 1950. Two factors are responsible for the pyramid shape in 1950: An increasing number of births broadened the base layer of the population pyramid and a continuously high risk of death throughout life is evident by the pyramid narrowing towards the top. There were many newborns relative to the number of people at older ages.

The narrowing of the pyramid just above the base is testimony to the fact that more than 1-in-5 children born in 1950 died before they reached the age of five.1

Through shades of blue and green the same visualization shows the population structure over the last decades up to 2018. You see that in each subsequent decade the population pyramid was fatter than before – in each decade more people of all ages were added to the world population.

If you look at the green pyramid for 2018 you see that the narrowing above the base is much less strong than back in 1950; the child mortality rate fell from 1-in-5 in 1950 to fewer than 1-in-20 today.

In comparing 1950 and 2018 we see that the number of children born has increased – 97 million in 1950 to 143 million today – and that the mortality of children decreased at the same time. If you now compare the base of the pyramid in 2018 with the projection for 2100 you see that the coming decades will not resemble the past: According to the projections there will be fewer children born at the end of this century than today. The base of the future population structure is narrower.

The Demography of the World Population from 1950 to 21002
Population pyramid 1950 to 2100

We are at a turning point in global population history. Between 1950 and today it was a widening of the entire pyramid that was responsible for the increase of the world population. What is responsible for the increase of the world population from now on is not a widening of the base, but a ‘fill up’ of the population above the base. Not children will be added to the world population, but people of working age and old age. The number of children born will remain as high as it is today, but as global health is improving and mortality is falling these children will live longer. The final step that will end rapid population growth.

At a country level “peak child” is often followed by a time in which the country benefits from a “demographic dividend” when the proportion of the dependent young generation falls and the share of the population in working age increases.3

This is now happening at a global scale. For every child younger than 15 there were 1.8 people in working-age (15 to 64) in 1950; today there are 2.5; and by the end of the century there will be 3.4.4

Richer countries have benefited from this transition in the last decades and are now facing the demographic problem of an increasingly larger share of retired people that are not contributing to the labor market. In the coming decades it will be the poorer countries that can benefit from this demographic dividend.

The change from 1950 to today and the projections to 2100 show a world population that is becoming healthier. When the top of the pyramid becomes wider and looks less like a pyramid and instead becomes more box-shaped, the population lives through younger ages with very low risk of death and dies at an old age. The demographic structure of a healthy population at the final stage of the demographic transition is the box shape that we see for the entire world for 2100.

How does median age vary across the world?

Median age provides an important single indicator of the age distribution of a population. It provides the age ‘midpoint’ of a population; there are the same number of people who are older than the median age as there are younger than it.

Median age therefore provides an indicator of how ‘young’ or ‘old’ a country is, but is also indicative of population growth.

In the map below we see the distribution of median ages across the world. The global average median age was 29.6 years in 2015. This means half of the global population were older than 29.6 years, and half were younger. Japan had the highest median age at 46.3 years. The youngest was Niger at 14.9 years.

Overall we see that higher-income countries, across North America, Europe and East Asia have a higher median age.

Click to open interactive version

Lower-income countries tend to have a lower median. This is because they have a ‘younger’ population overall: high fertility rates across these countries means they have larger populations of young children and adolescents.

Countries with the lowest median age tend to have higher population growth rates.

Click to open interactive version
Click to open interactive version

How is the age structure of populations changing?

The age structure of a population has important impacts for various aspects of society: economic growth rates, labour force participation, educational and healthcare services, housing markets amongst others.5,6

Over the past century, the age structure of populations has been changing. We can see this transition over time, but we also see large differences in the age composition between countries of the world.

In the charts below we see the population by broad age groups for two example countries: Japan and Nigeria. This is shown from 1950 onwards. Here there are two key points to notice.

  1. There are large differences in the age composition of the two countries. Nigeria has a much younger population: in 2015, around 44% of Nigerians were under 15 years old. In Japan, this was only 13%. Japan has a much older population: in 2015 more than 1-in-4 (26%) were 65 years and older. Less than 3% of Nigerians fell into this age bracket.
  2. We also see a major ageing transition in Japan over the past half-century. In 1950, more than half of its population (55%) were under the age of 25. By 2015 this had more than halved to less than a quarter. Instead, the share of those over 65 years old has increased more than five-fold, from less than 5% in 1950 to 26% in 2015.
Click to open interactive version
Click to open interactive version

We can look at this breakdown of age groupings even more broadly: split between children and adolescents (under 15 years old), the working age population (15-64 years) and elderly population (65 years and older).

As we discuss in our exploration of dependency ratios, this distribution between working age versus young and old (dependent) populations is important for the economic and social functioning of societies.

This breakdown is shown in the visualization. You can explore this data for any country using the “change country” button on the interactive chart.

Click to open interactive version

How do dependency ratios vary across the world?

A productive population is essential to maintain economic and social stability and progress. From this perspective, societies are split into two groups: the working and non-working age population. The latter group – often called ‘dependents’ – comprises the young (under 15 years) and old (65 years and older). The ‘working-age’ population is therefore those aged between 15 and 64 years.

The balance between the working-age population and ‘dependents’ has important implications for the functioning of the population. Evidence suggests that too many ‘dependents’ relative to those working can have negative impacts for labour productivity, capital formation, information and communication improvements, and savings rates.7

We can approximate the level of this dependency using a metric called the ‘age dependency ratio’. This measures the ratio between ‘dependents’ (the sum of young and old) to the working-age population (aged 15 to 64 years old). It’s given as the number (percentage) of dependents per 100 people of working-age. For example, a value of 100% would mean the number of dependents in a country was the same as the size of the working-age population.

The age dependency ratio across the world is shown in the map below. A higher number means there are more ‘dependents’ relative to the working-age population; a lower number means fewer.

Here we see significant variation across the world. The majority of countries have a ‘dependent’ population that is 50-60% the size of its working-age population. The ratio is much higher across many countries in Sub-Saharan Africa: Niger and Mali, for example, have a larger dependent population than they have working-age populations. As we see in the next section, this is the result of having very young populations.

Click to open interactive version

How do dependents vary across the world?

In the chart above we considered the ‘dependent’ population – both young and old – as a single group. But the split between young and old populations vary significantly across the world.

In the charts below we see the breakdown of age dependency by young and old populations for two contrasting countries: Japan and Nigeria. As we see, Japan has a much older population: in 2017, there were more than twice as many people aged 65+ years old than those younger than 15. Here we see that Japan has aged significantly in recent decades: in 1960 the young outnumbered the old by nearly 5-to-1.

The opposite is true in Nigeria. Almost 95% of dependents there are young.

You can explore this data for any country using the “change country” button in the charts below. You’ll notice fairly consistent patterns: higher-income countries with low fertility rates and longer life expectancies are dominated by an older population. The opposite is true for lower income countries with high fertility rates.

Click to open interactive version
Click to open interactive version

Young and old dependencies across the world

We can also see this distribution of young and old populations across the world clearly in the two maps below. These again show the age dependency ratio, but are now split between young (under 15 years) and old (65+ years) dependency ratios.

There is a clear contrast between the two. The young dependency ratio is high across Sub-Saharan Africa in particular. Some countries in this region have close to the same number of youth as they have working-age population. Lower fertility rates across higher income countries, the young dependency ratio is much lower.

The old dependency ratio is almost a mirror image. It’s now higher-income countries – particularly across Europe, North America and East Asia – which have the high dependency ratios.

Whilst the total age dependency ratio is a useful indicator, understanding the breakdown of this dependency between young and old is key. The needs, behaviour and future pathways for young and old populations is very different. This has important implications for national planning, spanning everything from education and healthcare services, to labour supply, savings rates and pensions.

Click to open interactive version
Click to open interactive version

What does the age structure of future populations look like?

The world population is changing: For the first time there are more people over 64 than children younger than 5

Countries across the world have been going through an important demographic transition: from young to increasingly ageing populations.

In 2018 the number of people older than 64 years old surpassed the number of children under 5 years old. This was the first time in history this was the case.8

We can see this transition clearly when we look at the population by age bracket in the chart below – this is shown from 1950 onwards, with UN projections to 2100.

In the chart below you can explore the projected age structure of future populations – for any country or world region. Just click on Change Country in the bottom left.

Click to open interactive version

Going beyond the global perspective, when did this crossover point occur in countries around the world?

The timing varied significantly between countries – in higher income countries with low fertility rates and longer life expectancies, it has been shifting for decades. In the United States, under-5s were already outnumbered by those older than 64 by 1966. In Spain it was 1970; in South Korea it was 2000.

For many countries, this crossover point is still to come. In India, it’s projected to be 2028. In South Africa, it’s expected to happen in 2036. In low-income countries with high fertility rates and lower life expectancy this point is still many decades away: it’s projected that in Nigeria, under-5s will outnumber those older than 64 until 2087.

The number of children under 5 years old is projected to peak and plateau for most of the 21st century. And as the global population of people older than 64 years will continue to grow, it’s clear that we’re moving towards an ageing world.

Demographic opportunities and challenges: dividends and ageing populations

When we look at the age structure of populations we see major challenges at both the young and old end of the spectrum. Lower-income countries with high fertility rates typically have a very young population; a large share of the population is children who aren’t (or shouldn’t) be in the productive working population. High-income countries with a large elderly population face the same challenge for working-age populations.

But how is this expected to change in the future? In the charts below we see breakdown of two example populations – Japan and Nigeria – by age between young (under 15 years old), working-age (15-64 years old) and elderly (65+ years old). This has been extended to the year 2100 based on the UN’s medium projected scenario.

For Japan, and other high-income countries, it’s expected that the older demographic over 65 years old will continue to increase in the coming decades. Since the youth share is not expected to change significantly, this means the share of the population of working-age is expected to fall further.

This is not the case for Nigeria. It currently has a very young population. But these children and adolescents will move into the working-age bracket. This means that in the decades to follow its productive, working population will increase significantly. As fertility rates decline, it’s expected that the working population as a share of the total population will continue to increase throughout this century.

Click to open interactive version
Click to open interactive version

From an economic perspective, this change in age structure generates very different opportunities and challenges across the spectrum of countries. This is because the balance between the working-age and ‘dependent’ (young and old) populations will move in opposite directions depending on the current level of development of the country.

For Nigeria, the population of productive working-age will increase relative to the ‘dependent’ population. We see this in the charts below which show the age dependency ratio (the ratio between non-working and working-age populations). This ratio is expected to decline throughout this century. This economic opportunity is often called the ‘demographic dividend’.9

It provides a window of opportunity for more rapid economic growth because its working population has less people to support.

But as research shows: taking full advantage of this opportunity is not a given. India – as the second-most populous countries and a country that has seen rapid decline in fertility rates in recent decades – has had a large potential demographic dividend. You can view its age dependency ratio in the chart below using the “change country” button. Here we see that the age dependency ratio in 1970 was almost 80%: a very young demographic. Since then it has fallen to 50%, and has until the late 2040s until it begins to rise again.

Studies, however, suggest that despite impressive rates of economic growth, India has failed to take full advantage of this possible demographic dividend. To reap the benefits of this demographic transition a few conditions are required: the labour market and jobs need to be available for young adults to move into; and the employability status of the youth needs to be suitable to fill these jobs. Studies suggest that the absorption of India’s youth into the workforce has not been as high as expected.10

Youth unemployment rates are high, and educational and health deficits are prevalent.11

This limits India’s ability to optimise economic growth from a large working-age population. Although it’s recognized that this demographic transition has had positive impacts for India’s growth, educational and health deficits combined with poor job creation means it hasn’t fully optimized this growth.12

The demographic dividend from a rapid reductions in fertility rates can provide a major opportunity for accelerated economic growth. But maximising this potential needs a strong policy environment for education, health and job creation. If lower-income countries can achieve this, they could see major economic gains throughout the 21st century.

Click to open interactive version
Click to open interactive version

Data Sources

UN Population Database
  • Data Source: UN Population Division based on ‘cohort-component’ framework by demographic trends (see Data Quality section)
  • Description of available measures:
    ◦ Population, by Five-Year Age Group and Sex
    ◦ Population Sex Ratio (males per 100 females)
    ◦ Median Age
    ◦ Population Growth Per Year
    ◦ Crude Birth Rate
    ◦ Crude Death Rate
    ◦ Net Reproduction Rate
    ◦ Total Fertility Rate
    ◦ Life Expectancy at Birth by Sex
    ◦ Net Migration Rate
    ◦ Sex ratio at birth
    ◦ Births
    ◦ Births by Age-group of Mother
    ◦ Age-specific Fertility Rates
    ◦ Women Aged 15-49
    ◦ Deaths by Sex
    ◦ Infant Mortality
    ◦ Mortality Under Age 5
    ◦ Dependency Ratios
    ◦ Population by Age: 0-4, 0-14, 5-14, 15-24, 15-59, 15-64, 60+, 65+, 80+
  • Time span: 1950-2015
  • Geographical coverage: Global by country
  • Link: