placestats

Married by 18 vs. Population 65+

Fades after adjusting for income

Across 136 countries, Married by 18 and Population 65+ rise and fall together at r = -0.51 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.15, which could easily be chance (q = 0.31, allowing for the many pairs tested, and allowing for countries in the same region being alike). So the first figure mostly shows richer countries differing from poorer ones, not a link between these two things.

Comparing countries across the middle half of population 65+, 3.48% to 10% of population, married by 18 is better by 8.34% of women aged 20-24 at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 2.75% of women aged 20-24.

Link before adjusting (r)-0.506p = 3.2e-10 · 136 countries
After adjusting for national income-0.152p = 0.079 · likely range [-0.31, +0.02]
p, allowing for regions0.233standard error 0.112 · 6 regions
Check for luck (q)0.307across 12,497 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.

Married by 18 · % of women aged 20-24link with income -0.60 · moderate
Population 65+ · % of populationlink with income +0.76 · high

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

Every country as a dot

Married by 18 · % of women aged 20-24 →Population 65+ · % of population →0%76.3%1.7%24.2%Afghanistan: 28.7% of women aged 20-24, 2.43% of populationAngola: 23.1% of women aged 20-24, 2.89% of populationAlbania: 11.8% of women aged 20-24, 17.6% of populationArgentina: 15.5% of women aged 20-24, 12.6% of populationArmenia: 5.3% of women aged 20-24, 14.4% of populationAzerbaijan: 15% of women aged 20-24, 9.17% of populationBurundi: 19% of women aged 20-24, 2.55% of populationBelgium: 0.1% of women aged 20-24, 21% of populationBenin: 27.5% of women aged 20-24, 3.15% of populationBurkina Faso: 38.2% of women aged 20-24, 2.68% of populationBangladesh: 47.2% of women aged 20-24, 6.67% of populationBosnia and Herzegovina: 3.5% of women aged 20-24, 22.9% of populationBelarus: 4.7% of women aged 20-24, 18.3% of populationBelize: 33.5% of women aged 20-24, 5.23% of populationBolivia: 14.5% of women aged 20-24, 5.74% of populationBarbados: 29.2% of women aged 20-24, 17.1% of populationBhutan: 9% of women aged 20-24, 6.63% of populationCentral African Republic: 61% of women aged 20-24, 2.2% of populationChile: 0% of women aged 20-24, 14.6% of populationChina: 2.8% of women aged 20-24, 14.9% of populationCote d'Ivoire: 25.8% of women aged 20-24, 2.65% of populationCameroon: 29.8% of women aged 20-24, 2.82% of populationCongo, Dem. Rep.: 29.9% of women aged 20-24, 3.08% of populationCongo, Rep.: 27.3% of women aged 20-24, 3.06% of populationColombia: 23.4% of women aged 20-24, 10.2% of populationComoros: 20.7% of women aged 20-24, 4.45% of populationCabo Verde: 8.4% of women aged 20-24, 7.15% of populationCosta Rica: 17.1% of women aged 20-24, 12.8% of populationDjibouti: 6.5% of women aged 20-24, 4.97% of populationDenmark: 0.7% of women aged 20-24, 21.1% of populationDominican Republic: 31.5% of women aged 20-24, 8.19% of populationAlgeria: 3.8% of women aged 20-24, 6.81% of populationEcuador: 22.2% of women aged 20-24, 8.6% of populationEgypt, Arab Rep.: 15.8% of women aged 20-24, 5.27% of populationEthiopia: 40.3% of women aged 20-24, 3.3% of populationFinland: 0.1% of women aged 20-24, 24.2% of populationFiji: 4% of women aged 20-24, 6.63% of populationGabon: 13.3% of women aged 20-24, 4.13% of populationUnited Kingdom: 0% of women aged 20-24, 19.7% of populationGeorgia: 9.4% of women aged 20-24, 16% of populationGhana: 16.1% of women aged 20-24, 3.79% of populationGuinea: 46.5% of women aged 20-24, 3.47% of populationGambia, The: 23.1% of women aged 20-24, 3.18% of populationGuinea-Bissau: 25.7% of women aged 20-24, 3.24% of populationEquatorial Guinea: 29.5% of women aged 20-24, 3.76% of populationGuatemala: 29.5% of women aged 20-24, 4.96% of populationGuyana: 32.3% of women aged 20-24, 6.98% of populationHonduras: 34% of women aged 20-24, 4.54% of populationHaiti: 14.9% of women aged 20-24, 4.79% of populationIndonesia: 16.3% of women aged 20-24, 7.54% of populationIndia: 22.3% of women aged 20-24, 7.38% of populationIran, Islamic Rep.: 16.7% of women aged 20-24, 8.58% of populationIraq: 27.9% of women aged 20-24, 3.45% of populationIsrael: 0.8% of women aged 20-24, 12.7% of populationJamaica: 26.9% of women aged 20-24, 8.58% of populationJordan: 9.9% of women aged 20-24, 4.75% of populationKazakhstan: 6.1% of women aged 20-24, 9% of populationKenya: 12.5% of women aged 20-24, 3.02% of populationKyrgyz Republic: 9.2% of women aged 20-24, 5.97% of populationCambodia: 17.9% of women aged 20-24, 6.38% of populationKiribati: 18.4% of women aged 20-24, 4.38% of populationLao PDR: 30.5% of women aged 20-24, 4.81% of populationLebanon: 6% of women aged 20-24, 10.4% of populationLiberia: 24.9% of women aged 20-24, 3.33% of populationLibya: 4.1% of women aged 20-24, 5.19% of populationSt. Lucia: 24% of women aged 20-24, 9.96% of populationSri Lanka: 9.8% of women aged 20-24, 12.5% of populationLesotho: 13.4% of women aged 20-24, 3.88% of populationLithuania: 0.2% of women aged 20-24, 20.7% of populationMorocco: 13.7% of women aged 20-24, 8.45% of populationMoldova: 12.2% of women aged 20-24, 16.9% of populationMadagascar: 38.8% of women aged 20-24, 3.47% of populationMaldives: 2.2% of women aged 20-24, 4.96% of populationMexico: 18.2% of women aged 20-24, 8.52% of populationNorth Macedonia: 7.5% of women aged 20-24, 18.5% of populationMali: 48.5% of women aged 20-24, 2.36% of populationMyanmar: 16% of women aged 20-24, 7.52% of populationMontenegro: 5.8% of women aged 20-24, 18.3% of populationMongolia: 8.1% of women aged 20-24, 5.43% of populationMozambique: 48.4% of women aged 20-24, 2.73% of populationMauritania: 36.6% of women aged 20-24, 3.25% of populationMalawi: 38.7% of women aged 20-24, 2.59% of populationNamibia: 6.9% of women aged 20-24, 3.79% of populationNiger: 76.3% of women aged 20-24, 2.62% of populationNigeria: 33.4% of women aged 20-24, 3.07% of populationNicaragua: 35.2% of women aged 20-24, 5.7% of populationNorway: 0% of women aged 20-24, 19.1% of populationNepal: 34.9% of women aged 20-24, 6.62% of populationNaoero: 18.2% of women aged 20-24, 3.01% of populationOman: 4% of women aged 20-24, 2.69% of populationPakistan: 18.3% of women aged 20-24, 4.36% of populationPanama: 26.4% of women aged 20-24, 9.66% of populationPeru: 17.9% of women aged 20-24, 9.47% of populationPhilippines: 9.4% of women aged 20-24, 5.72% of populationPapua New Guinea: 27.3% of women aged 20-24, 3.59% of populationParaguay: 21.6% of women aged 20-24, 6.72% of populationWest Bank and Gaza: 13.4% of women aged 20-24, 3.85% of populationQatar: 1.7% of women aged 20-24, 1.7% of populationRomania: 6.9% of women aged 20-24, 20.1% of populationRussian Federation: 6.2% of women aged 20-24, 17.8% of populationRwanda: 5.5% of women aged 20-24, 4.02% of populationSaudi Arabia: 3.4% of women aged 20-24, 3.06% of populationSudan: 34.2% of women aged 20-24, 3.39% of populationSenegal: 30.2% of women aged 20-24, 3.65% of populationSingapore: 0.1% of women aged 20-24, 14.2% of populationSolomon Islands: 21.3% of women aged 20-24, 3.67% of populationSierra Leone: 29.6% of women aged 20-24, 3.28% of populationEl Salvador: 19.7% of women aged 20-24, 8.31% of populationSerbia: 5.5% of women aged 20-24, 23.1% of populationSao Tome and Principe: 28% of women aged 20-24, 3.94% of populationSuriname: 36% of women aged 20-24, 8.19% of populationEswatini: 1.9% of women aged 20-24, 4.35% of populationTurks and Caicos Islands: 23.3% of women aged 20-24, 11.7% of populationChad: 60.6% of women aged 20-24, 2.12% of populationTogo: 24.8% of women aged 20-24, 3.48% of populationThailand: 17% of women aged 20-24, 16% of populationTajikistan: 8.8% of women aged 20-24, 4.07% of populationTurkmenistan: 6.1% of women aged 20-24, 4.81% of populationTimor-Leste: 14.9% of women aged 20-24, 5.23% of populationTonga: 10.1% of women aged 20-24, 6.85% of populationTrinidad and Tobago: 4.2% of women aged 20-24, 12.9% of populationTunisia: 2.4% of women aged 20-24, 9.94% of populationTurkiye: 14.7% of women aged 20-24, 10.6% of populationTuvalu: 1.8% of women aged 20-24, 7.04% of populationTanzania: 29.1% of women aged 20-24, 3.04% of populationUganda: 34% of women aged 20-24, 2.23% of populationUkraine: 9.1% of women aged 20-24, 19% of populationUruguay: 24.6% of women aged 20-24, 16.3% of populationUzbekistan: 3.4% of women aged 20-24, 6.07% of populationViet Nam: 14.6% of women aged 20-24, 9.49% of populationVanuatu: 20.9% of women aged 20-24, 4.38% of populationSamoa: 7.4% of women aged 20-24, 6.07% of populationKosovo: 4% of women aged 20-24, 10.5% of populationSouth Africa: 3.6% of women aged 20-24, 6.89% of populationZambia: 23.9% of women aged 20-24, 2% of populationZimbabwe: 33.7% of women aged 20-24, 3.56% of populationBELBIHBRBCAFFINNEROMNQATSAUTCD

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5063.2e-10136
By rank (Spearman), not adjusted-0.5562.1e-12136
Standard (Pearson), adjusted for national income-0.1520.079136
By rank (Spearman), adjusted for national income-0.1950.023136

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 136 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: +0.355 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.172 (without BRB) to -0.113 (without GUY). 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: GUY (+0.038).

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.

nr
East Asia & Pacific20-0.15
Europe & Central Asia26-0.16
Latin America & Caribbean25-0.43
Middle East, North Africa, Afghanistan & Pakistan17-0.38
Sub-Saharan Africa42-0.42

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.

nr
Poorest third46-0.40
Middle third45-0.19
Richest third45-0.28

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.

nr
Christians76-0.33
Muslims43-0.19

By last european coloniser

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.

nr
France24-0.41
Never a European colony19+0.11
Spain19-0.40
United Kingdom43-0.02

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 = -0.141 after dropping 10 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 36years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Within countries over time, there is no link that is clearly more than chance (r = +0.194, comparing each country only with itself over the years, and each year only with the same year elsewhere). Whatever the cross-country picture shows, countries whose married by 18 moved did not tend to see their population 65+ move with it.

Across countries (adjusted)-0.152for comparison
Within countries-0.315each country vs itself
…and vs the same year elsewhere+0.194q = 0.264 · 31 countries
Year-on-year changes—q = —
The direction flips. Comparing each country only with itself gives -0.31. Also taking out what happened to the whole world each year gives +0.19. So the first figure was picking up a trend both measures share with worldwide progress, not a link between them.

205 country-years (one country in one year), 31 countries, 1990–2025, about 7 years each on average. Share of the variation that happens within countries over time: 26% for Married by 18, 14% for Population 65+. 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

The data


% of women aged 20-24

% of population
Years
Niger NER76.3%2.62%2012, 2025
Central African Republic CAF61%2.2%2019, 2025
Chad TCD60.6%2.12%2019, 2025
Mali MLI48.5%2.36%2024, 2025
Mozambique MOZ48.4%2.73%2023, 2025
Bangladesh BGD47.2%6.67%2025
Guinea GIN46.5%3.47%2018, 2025
Ethiopia ETH40.3%3.3%2016, 2025
Madagascar MDG38.8%3.47%2021, 2025
Malawi MWI38.7%2.59%2024, 2025
Burkina Faso BFA38.2%2.68%2021, 2025
Mauritania MRT36.6%3.25%2021, 2025
Suriname SUR36%8.19%2018, 2025
Nicaragua NIC35.2%5.7%2012, 2025
Nepal NPL34.9%6.62%2022, 2025

World Bank, World Development Indicators
World Bank, World Development Indicators

Sources

Married by 18

Women who were first married by age 18 (% of women ages 20-24)

UNICEF · CC BY 4.0 · updated quarterly

From household surveys, mostly in lower-income countries, and only in years a survey ran. No year reaches sixty countries, so the latest value used is up to a decade old for some. Rich countries rarely report it at all, which shapes any link with income.

Population 65+

Population ages 65 and above (% of total)

World Bank · CC BY 4.0 · updated quarterly

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2025. 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 6 World Bank regions. The q-value corrects for testing all 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Married by 18 and Population 65+

This page shows that two measures go together. It does not show that Married by 18 changes Population 65+, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Married by 18 or Population 65+