Do Age at childbearing and Women's age at first marriage (census-based) go together across countries?

Across 176 countries the link before adjusting for anything is r = +0.63, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives +0.59.

Does the link hold within countries over time, not just across countries?

Comparing each country only with itself across 1990-2019, and setting aside what happened worldwide in each year, the link is +0.491 (123 countries, 1,180 country-years). Using year-to-year changes, it is +0.099.

Does Age at childbearing cause Women's age at first marriage (census-based)?

This analysis cannot answer that. It shows only that the two go together. A link between two country measures, adjusted or not, does not show that either one changes the other. Country figures also say nothing about individual people.

Age at childbearing vs. Women's age at first marriage (census-based)

Holds up after adjusting for income

Across 176 countries, Age at childbearing and Women's age at first marriage (census-based) rise and fall together at r = +0.63 (on a scale from −1 to +1, where 0 means no link). It holds up almost unchanged when only countries with similar income (GDP per person) are compared (r = +0.50, q = 0.0031, allowing for the many pairs tested).

Comparing countries across the middle half of age at childbearing, 28.2 to 30.3 years, women's age at first marriage (census-based) is 3.27 years higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 2 years.

Link before adjusting (r)+0.627p = 1.2e-20 · 176 countries

After adjusting for national income+0.497p = 2.7e-12 · likely range [+0.38, +0.60]

p, allowing for regions4.7e-5standard error 0.048 · 7 regions

Check for luck (q)0.003across 14,952 pairs

How to read these.r runs from −1 (one goes up as the other goes down) to +1 (they rise together), and 0 means no link. Adjusting for national income means comparing countries with the same GDP per person, so differences in wealth can’t explain the link. Income is used in percentage terms, since an extra $1,000 means more to a poor country than to a rich one. p is how likely a link this strong would be if there were really none. Below 0.05 means it is unlikely to be chance. Very small values are written in short form: 1.1e-32 means a decimal point followed by 31 zeros and then 11, so very close to zero. The likely range is where the true figure probably lies, and a range that crosses zero means the link could easily be chance. Countries in the same region tend to resemble each other, so the third figure allows for that, which gives a fairer p. The standard error is the typical size of the error in r. Finally, testing this many pairs means some will look strong by luck alone. A q below 0.05 means this link is unlikely to be one of those.

Age at childbearing · yearslink with income +0.44 · moderate

Women's age at first marriage (census-based) · yearslink with income +0.75 · high

“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.

Every country as a dot

best-fit line line after adjusting

Four ways to measure the link

Method	r	p	Countries
Standard (Pearson), not adjusted	+0.627	1.2e-20	176
By rank (Spearman), not adjusted	+0.586	1.4e-17	176
Standard (Pearson), adjusted for national income	+0.497	2.7e-12	176
By rank (Spearman), adjusted for national income	+0.428	3.6e-9	176

The rank version uses only each country’s place in line, from lowest to highest, so a few extreme countries count for less. The adjusted and unadjusted versions use the same 176 countries: those that report both measures and GDP per person. So the gap between them comes from the adjustment, not from a change in which countries are counted. Drop in the size of r after adjusting: +0.130 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.474 (without GUY) to +0.521 (without BGR). The bar above shows that range on a scale from −1 to +1, with the solid line at the full result. The single country that moves r most: BGR (+0.024).

Within each region

Countries are not separate, unrelated cases, and neighbors share a lot. A link that holds inside each region is far more believable than one that shows up only when comparing regions.

	n	r
East Asia & Pacific	26	+0.63
Europe & Central Asia	50	+0.16
Latin America & Caribbean	32	+0.43
Middle East, North Africa, Afghanistan & Pakistan	17	+0.79
Sub-Saharan Africa	42	+0.23

By income third

If the link shows up only in the richest third of countries, it is a feature of rich countries, not a general pattern.

	n	r
Poorest third	59	+0.57
Middle third	58	+0.34
Richest third	59	+0.40

By largest religious group

Countries grouped by a label they share, such as main religion, rather than by a number. Groups of fewer than twelve countries are not shown. These groups differ in income, region and history all at once. So a gap between them is a place to start asking questions, not an answer.

	n	r
Christians	105	+0.52
Muslims	42	+0.59

By last european coloniser

	n	r
France	22	+0.78
Never a European colony	20	+0.70
Spain	20	+0.76
United Kingdom	50	+0.45

Without outliers (countries far outside the middle half of countries on either measure, by more than one and a half times the width of that middle half): r = +0.497 after dropping 0 countries.

Two series, one country

Both measures over the years for one country you pick. The two charts are stacked so they share only the years along the bottom.

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Over time, within countries

Everything above compares countries with each other at one moment. This section compares each country only with itself over 30years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

The link shows up within countries over time (r = +0.491) but mostly disappears in year-to-year changes (r = +0.099). That points to slow trends particular to each country, not the two measures moving together from year to year.

Across countries (adjusted)+0.497for comparison

Within countries+0.616each country vs itself

…and vs the same year elsewhere+0.491q = 0.000 · 123 countries

Year-on-year changes+0.099q = 0.084

Read with care.

The association is much weaker in year-on-year changes than in levels, which points to shared country-specific trends.

1,180 country-years (one country in one year), 123 countries, 1990–2019, about 10 years each on average. Share of the variation that happens within countries over time: 20% for Age at childbearing, 14% for Women's age at first marriage (census-based). The margins of error allow for each country appearing many times, and for each year’s value being close to the year before.

Year-to-year changes are a cautious test, not a final answer. Looking only at changes from one year to the next removes each country’s own trends. But it also makes measurement mistakes louder, which pulls the results toward zero. A near-zero result here is weak evidence of no link, not proof.

With one measure years behind the other

Same year (lag 0): +0.491. A peak away from zero does not show which comes first. These series change slowly — this year’s value is close to last year’s. That makes the curve smooth and nearly symmetric, whatever produced the data. Even a sharp peak at one lag (a gap of some years) would not prove that one measure changes the other.

The data

	years	years	Years
Korea, Rep. KOR	33.4	31.5	2023, 2015
Hong Kong SAR, China HKG	32.9	29.9	2023, 2016
San Marino SMR	32.8	31.3	2023, 2018
Ireland IRL	32.7	32.4	2023, 2016
Spain ESP	32.5	27.7	2023, 2011
Luxembourg LUX	32.3	30.7	2023, 2018
Italy ITA	32.3	32.2	2023, 2018
Switzerland CHE	32.3	30.9	2023, 2017
Singapore SGP	32.3	27.9	2023, 2010
Macao SAR, China MAC	32.1	30.3	2023, 2011
Bermuda BMU	32.1	31.9	2023, 2016
Greece GRC	32	29.2	2023, 2011
Japan JPN	31.9	29.2	2023, 2015
Netherlands NLD	31.8	32.4	2023, 2018
Portugal PRT	31.7	30.1	2023, 2011

United Nations, Department of Economic and Social Affairs, Population Division: World Population Prospects 2024 and Estimates and Projections of Women of Reproductive Age Who Are Married or in a Union
World Bank Gender Statistics, from UN Population Division, World Marriage Data

Sources

Age at childbearing

Mean age of mothers at childbearing

United Nations Department of Economic and Social Affairs, Population Division · via Our World in Data · CC BY 3.0 IGO · updated biennial

The average age of women giving birth in the year, based on how many births women of each age have. Later childbearing goes with fewer births, but not one for one. A country can have late but plentiful births, or early but few. No "better" direction is set.

Women's age at first marriage (census-based)

Age at first marriage, female

World Bank · CC BY 4.0 · updated annual

The average age at which women first marry. It is worked out from census and survey counts of how many women in each age group have never married, by the UN Population Division (World Marriage Data), so it covers far more countries than registered marriages do. Most countries have a figure only every few years, and the series ends in 2019. No "better" direction is set.

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2023. To adjust for income, each measure is first predicted from GDP per person (in percentage terms, on a log scale) with a straight-line fit. Only what is left over is then compared. This is called a partial correlation. The line is drawn the standard way (ordinary least squares), which picks the line that comes closest to all the countries at once. The error margins allow for countries in the same region resembling each other, using 7 World Bank regions. The q-value corrects for testing all 14,952 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Age at childbearing and Women's age at first marriage (census-based)

This page shows that two measures go together. It does not show that Age at childbearing changes Women's age at first marriage (census-based), or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.