Do Married by 18 and Physicians go together across countries?

Across 134 countries the link before adjusting for anything is r = -0.55, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives -0.64.

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

There are not enough years of data within countries to check this over time.

Does Married by 18 cause Physicians?

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.

Married by 18 vs. Physicians

Fades after adjusting for income

Across 134 countries, Married by 18 and Physicians rise and fall together at r = -0.55 (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 = 0.20, 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 physicians, 0.245 to 2.69 per 1,000 people, married by 18 is better by 12.8% of women aged 20-24 at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 4.38% of women aged 20-24.

Link before adjusting (r)-0.546p = 8.5e-12 · 134 countries

After adjusting for national income-0.151p = 0.083 · likely range [-0.31, +0.02]

p, allowing for regions0.251standard error 0.116 · 6 regions

Check for luck (q)0.198across 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

Physicians · per 1,000 peoplelink with income +0.85 · proxy

“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	-0.546	8.5e-12	134
By rank (Spearman), not adjusted	-0.641	7.3e-17	134
Standard (Pearson), adjusted for national income	-0.151	0.083	134
By rank (Spearman), adjusted for national income	-0.293	0.001	134

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 134 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: +0.395 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.176 (without URY) to -0.103 (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 (+0.048).

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	20	-0.45
Europe & Central Asia	25	-0.03
Latin America & Caribbean	24	-0.48
Middle East, North Africa, Afghanistan & Pakistan	17	-0.30
Sub-Saharan Africa	42	-0.37

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	45	-0.34
Middle third	44	-0.22
Richest third	45	-0.29

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	76	-0.15
Muslims	42	-0.37

By last european coloniser

	n	r
France	24	-0.25
Never a European colony	19	-0.38
Spain	19	-0.16
United Kingdom	43	-0.13

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 = -0.209 after dropping 3 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	per 1,000 people	Years
Niger NER	76.3%	0.038	2012, 2023
Central African Republic CAF	61%	0.074	2019, 2023
Chad TCD	60.6%	0.085	2019, 2023
Mali MLI	48.5%	0.188	2024, 2023
Mozambique MOZ	48.4%	0.175	2023, 2022
Bangladesh BGD	47.2%	0.722	2025, 2023
Guinea GIN	46.5%	0.21	2018, 2022
Ethiopia ETH	40.3%	0.143	2016, 2023
Madagascar MDG	38.8%	0.172	2021, 2022
Malawi MWI	38.7%	0.054	2024, 2022
Burkina Faso BFA	38.2%	0.148	2021, 2022
Mauritania MRT	36.6%	0.261	2021, 2022
Suriname SUR	36%	1.35	2018, 2023
Nicaragua NIC	35.2%	0.682	2012, 2018
Nepal NPL	34.9%	1.01	2022, 2023

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.

Physicians

Physicians (per 1,000 people)

World Health Organization · CC BY 4.0 · updated quarterly

Reported irregularly, so the latest value in the time window used is from a different year for different countries. Hospital beds, already on the site, have no "better" direction, since more beds is not plainly better. More doctors is closer to plainly better, so a direction is set on that basis.

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 Physicians

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