placestats

Married by 18 vs. Skilled birth attendance

Fades after adjusting for income

Across 131 countries, Married by 18 and Skilled birth attendance rise and fall together at r = -0.64 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.43, which could easily be chance (q = 0.10, 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. Caution: direction is not consistent across regions.

Comparing countries across the middle half of skilled birth attendance, 79.3% to 99.5% of births, married by 18 is better by 11.3% of women aged 20-24 at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 7.95% of women aged 20-24.

Link before adjusting (r)-0.644p = 1.0e-16 · 131 countries
After adjusting for national income-0.427p = 4.0e-7 · likely range [-0.56, -0.28]
p, allowing for regions0.081standard error 0.196 · 6 regions
Check for luck (q)0.102across 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
Skilled birth attendance · % of birthslink with income +0.69 · 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 →Skilled birth attendance · % of births →0%76.3%40.3%100%Afghanistan: 28.7% of women aged 20-24, 61.8% of birthsAngola: 23.1% of women aged 20-24, 49.6% of birthsAlbania: 11.8% of women aged 20-24, 99.8% of birthsArgentina: 15.5% of women aged 20-24, 98.8% of birthsArmenia: 5.3% of women aged 20-24, 99.8% of birthsAzerbaijan: 15% of women aged 20-24, 99.9% of birthsBurundi: 19% of women aged 20-24, 76.5% of birthsBenin: 27.5% of women aged 20-24, 78.1% of birthsBurkina Faso: 38.2% of women aged 20-24, 79.8% of birthsBangladesh: 47.2% of women aged 20-24, 59% of birthsBosnia and Herzegovina: 3.5% of women aged 20-24, 99.9% of birthsBelarus: 4.7% of women aged 20-24, 99.9% of birthsBelize: 33.5% of women aged 20-24, 94.6% of birthsBolivia: 14.5% of women aged 20-24, 81.1% of birthsBarbados: 29.2% of women aged 20-24, 98.4% of birthsBhutan: 9% of women aged 20-24, 98.9% of birthsCentral African Republic: 61% of women aged 20-24, 40.3% of birthsChile: 0% of women aged 20-24, 99.8% of birthsChina: 2.8% of women aged 20-24, 99.9% of birthsCote d'Ivoire: 25.8% of women aged 20-24, 84% of birthsCameroon: 29.8% of women aged 20-24, 69% of birthsCongo, Dem. Rep.: 29.9% of women aged 20-24, 85.2% of birthsCongo, Rep.: 27.3% of women aged 20-24, 91.2% of birthsColombia: 23.4% of women aged 20-24, 98.8% of birthsComoros: 20.7% of women aged 20-24, 82.2% of birthsCabo Verde: 8.4% of women aged 20-24, 97.3% of birthsCosta Rica: 17.1% of women aged 20-24, 99% of birthsDjibouti: 6.5% of women aged 20-24, 87.4% of birthsDenmark: 0.7% of women aged 20-24, 95.3% of birthsDominican Republic: 31.5% of women aged 20-24, 99.2% of birthsAlgeria: 3.8% of women aged 20-24, 98.8% of birthsEcuador: 22.2% of women aged 20-24, 99.4% of birthsEgypt, Arab Rep.: 15.8% of women aged 20-24, 97.1% of birthsEthiopia: 40.3% of women aged 20-24, 49.8% of birthsFinland: 0.1% of women aged 20-24, 99.5% of birthsFiji: 4% of women aged 20-24, 99.8% of birthsGabon: 13.3% of women aged 20-24, 89.3% of birthsGeorgia: 9.4% of women aged 20-24, 99.8% of birthsGhana: 16.1% of women aged 20-24, 78.9% of birthsGuinea: 46.5% of women aged 20-24, 55.3% of birthsGambia, The: 23.1% of women aged 20-24, 83.8% of birthsGuinea-Bissau: 25.7% of women aged 20-24, 53.8% of birthsEquatorial Guinea: 29.5% of women aged 20-24, 68.3% of birthsGuatemala: 29.5% of women aged 20-24, 69.6% of birthsGuyana: 32.3% of women aged 20-24, 97.6% of birthsHonduras: 34% of women aged 20-24, 94.1% of birthsHaiti: 14.9% of women aged 20-24, 41.6% of birthsIndonesia: 16.3% of women aged 20-24, 94.7% of birthsIndia: 22.3% of women aged 20-24, 89.4% of birthsIran, Islamic Rep.: 16.7% of women aged 20-24, 99% of birthsIraq: 27.9% of women aged 20-24, 95.6% of birthsJamaica: 26.9% of women aged 20-24, 99.7% of birthsJordan: 9.9% of women aged 20-24, 99.7% of birthsKazakhstan: 6.1% of women aged 20-24, 99.9% of birthsKenya: 12.5% of women aged 20-24, 70.2% of birthsKyrgyz Republic: 9.2% of women aged 20-24, 100% of birthsCambodia: 17.9% of women aged 20-24, 98.7% of birthsKiribati: 18.4% of women aged 20-24, 91.9% of birthsLao PDR: 30.5% of women aged 20-24, 64.4% of birthsLiberia: 24.9% of women aged 20-24, 84.4% of birthsLibya: 4.1% of women aged 20-24, 99.9% of birthsSt. Lucia: 24% of women aged 20-24, 100% of birthsSri Lanka: 9.8% of women aged 20-24, 99.5% of birthsLesotho: 13.4% of women aged 20-24, 86.6% of birthsLithuania: 0.2% of women aged 20-24, 100% of birthsMorocco: 13.7% of women aged 20-24, 86.6% of birthsMoldova: 12.2% of women aged 20-24, 99.6% of birthsMadagascar: 38.8% of women aged 20-24, 45.8% of birthsMaldives: 2.2% of women aged 20-24, 99.5% of birthsMexico: 18.2% of women aged 20-24, 96.6% of birthsNorth Macedonia: 7.5% of women aged 20-24, 100% of birthsMali: 48.5% of women aged 20-24, 67.3% of birthsMyanmar: 16% of women aged 20-24, 60.2% of birthsMontenegro: 5.8% of women aged 20-24, 98.8% of birthsMongolia: 8.1% of women aged 20-24, 99.3% of birthsMozambique: 48.4% of women aged 20-24, 73% of birthsMauritania: 36.6% of women aged 20-24, 70.4% of birthsMalawi: 38.7% of women aged 20-24, 96.4% of birthsNamibia: 6.9% of women aged 20-24, 88.2% of birthsNiger: 76.3% of women aged 20-24, 43.7% of birthsNigeria: 33.4% of women aged 20-24, 50.7% of birthsNicaragua: 35.2% of women aged 20-24, 94.1% of birthsNorway: 0% of women aged 20-24, 99.2% of birthsNepal: 34.9% of women aged 20-24, 77.2% of birthsOman: 4% of women aged 20-24, 99.9% of birthsPakistan: 18.3% of women aged 20-24, 68% of birthsPanama: 26.4% of women aged 20-24, 95% of birthsPeru: 17.9% of women aged 20-24, 94.9% of birthsPhilippines: 9.4% of women aged 20-24, 84.4% of birthsPapua New Guinea: 27.3% of women aged 20-24, 56.4% of birthsParaguay: 21.6% of women aged 20-24, 92.2% of birthsWest Bank and Gaza: 13.4% of women aged 20-24, 99.7% of birthsQatar: 1.7% of women aged 20-24, 100% of birthsRomania: 6.9% of women aged 20-24, 93% of birthsRussian Federation: 6.2% of women aged 20-24, 99.6% of birthsRwanda: 5.5% of women aged 20-24, 94.2% of birthsSaudi Arabia: 3.4% of women aged 20-24, 94.8% of birthsSudan: 34.2% of women aged 20-24, 77.7% of birthsSenegal: 30.2% of women aged 20-24, 74.5% of birthsSingapore: 0.1% of women aged 20-24, 99.6% of birthsSolomon Islands: 21.3% of women aged 20-24, 86.2% of birthsSierra Leone: 29.6% of women aged 20-24, 86.9% of birthsEl Salvador: 19.7% of women aged 20-24, 99.9% of birthsSerbia: 5.5% of women aged 20-24, 99.9% of birthsSao Tome and Principe: 28% of women aged 20-24, 96.8% of birthsSuriname: 36% of women aged 20-24, 98.4% of birthsEswatini: 1.9% of women aged 20-24, 88.3% of birthsTurks and Caicos Islands: 23.3% of women aged 20-24, 100% of birthsChad: 60.6% of women aged 20-24, 47.2% of birthsTogo: 24.8% of women aged 20-24, 69.4% of birthsThailand: 17% of women aged 20-24, 99.1% of birthsTajikistan: 8.8% of women aged 20-24, 94.8% of birthsTurkmenistan: 6.1% of women aged 20-24, 100% of birthsTimor-Leste: 14.9% of women aged 20-24, 56.7% of birthsTonga: 10.1% of women aged 20-24, 98.3% of birthsTrinidad and Tobago: 4.2% of women aged 20-24, 100% of birthsTunisia: 2.4% of women aged 20-24, 99.5% of birthsTurkiye: 14.7% of women aged 20-24, 97% of birthsTuvalu: 1.8% of women aged 20-24, 99.5% of birthsTanzania: 29.1% of women aged 20-24, 63.5% of birthsUganda: 34% of women aged 20-24, 74.2% of birthsUkraine: 9.1% of women aged 20-24, 99.9% of birthsUruguay: 24.6% of women aged 20-24, 100% of birthsUzbekistan: 3.4% of women aged 20-24, 99% of birthsViet Nam: 14.6% of women aged 20-24, 96.1% of birthsVanuatu: 20.9% of women aged 20-24, 89.4% of birthsSamoa: 7.4% of women aged 20-24, 88.9% of birthsKosovo: 4% of women aged 20-24, 99% of birthsSouth Africa: 3.6% of women aged 20-24, 96.7% of birthsZambia: 23.9% of women aged 20-24, 80.4% of birthsZimbabwe: 33.7% of women aged 20-24, 86% of birthsAGOCAFCHLDOMHTILTUMWINERSGPSURTCDTLS

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.6441.0e-16131
By rank (Spearman), not adjusted-0.6261.4e-15131
Standard (Pearson), adjusted for national income-0.4274.0e-7131
By rank (Spearman), adjusted for national income-0.3632.2e-5131

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 131 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: +0.217 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.469 (without HTI) to -0.394 (without NER). 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: HTI (-0.042).

Fragile: this link may not hold up.
  • direction is not consistent across regions

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 & Pacific19-0.46
Europe & Central Asia24-0.03
Latin America & Caribbean25+0.19
Middle East, North Africa, Afghanistan & Pakistan15-0.33
Sub-Saharan Africa42-0.63

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 third44-0.48
Middle third43-0.50
Richest third44-0.19

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
Christians74-0.20
Muslims42-0.74

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
France23-0.37
Never a European colony19-0.72
Spain19-0.05
United Kingdom41-0.33

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 = -0.371 after dropping 5 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 0years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Not enough history inside each country to look at this over time. That needs countries measured for several years in a row, and at least one of these measures is measured too rarely.

The data


% of women aged 20-24

% of births
Years
Niger NER76.3%43.7%2012, 2021
Central African Republic CAF61%40.3%2019
Chad TCD60.6%47.2%2019
Mali MLI48.5%67.3%2024, 2018
Mozambique MOZ48.4%73%2023, 2015
Bangladesh BGD47.2%59%2025, 2019
Guinea GIN46.5%55.3%2018
Ethiopia ETH40.3%49.8%2016, 2019
Madagascar MDG38.8%45.8%2021
Malawi MWI38.7%96.4%2024, 2020
Burkina Faso BFA38.2%79.8%2021, 2015
Mauritania MRT36.6%70.4%2021
Suriname SUR36%98.4%2018
Nicaragua NIC35.2%94.1%2012, 2017
Nepal NPL34.9%77.2%2022, 2019

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.

Skilled birth attendance

Births attended by skilled health staff (% of total)

UNICEF and WHO · CC BY 4.0 · updated quarterly

Based on surveys, so a country reports it every few years rather than yearly.

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 Skilled birth attendance

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

More links with Married by 18 or Skilled birth attendance