DTP3 immunisation vs. Marriage rate (UN)
Holds up after adjusting for income
Across 93 countries, DTP3 immunisation and Marriage rate (UN) rise and fall together at r = +0.16 (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 = +0.31, q = 0.028, allowing for the many pairs tested).
Comparing countries across the middle half of marriage rate (un), 3.8 to 5.63 marriages per 1,000 people, dtp3 immunisation is better by 1.74% of children aged 12-23 months at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 3.26% of children aged 12-23 months.
Link before adjusting (r)+0.161p = 0.122 · 93 countries
After adjusting for national income+0.314p = 0.002 · likely range [+0.12, +0.49]
p, allowing for regions0.008standard error 0.081 · 7 regions
Check for luck (q)0.028across 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.
DTP3 immunisation · % of children aged 12-23 monthslink with income +0.53 · moderate
Marriage rate (UN) · marriages per 1,000 peoplelink with income -0.21 · independent
“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 | +0.161 | 0.122 | 93 |
| By rank (Spearman), not adjusted | +0.166 | 0.112 | 93 |
| Standard (Pearson), adjusted for national income | +0.314 | 0.002 | 93 |
| By rank (Spearman), adjusted for national income | +0.258 | 0.013 | 93 |
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 93 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: -0.152 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from +0.280 (without PAN) to +0.350 (without STP). 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: STP (+0.037).
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 | ||
|---|---|---|---|
| Europe & Central Asia | 49 | +0.21 | |
| Latin America & Caribbean | 19 | +0.53 |
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 | 31 | +0.36 | |
| Middle third | 31 | +0.31 | |
| Richest third | 31 | +0.17 |
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 | 61 | +0.27 | |
| Muslims | 17 | +0.60 |
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.
| n | r | ||
|---|---|---|---|
| Never a European colony | 12 | +0.32 | |
| United Kingdom | 25 | +0.28 |
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 = +0.168 after dropping 8 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 12years. 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 = +0.026, 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 dtp3 immunisation moved did not tend to see their marriage rate (un) move with it.
Across countries (adjusted)+0.314for comparison
Within countries+0.148each country vs itself
…and vs the same year elsewhere+0.026q = 0.787 · 88 countries
Year-on-year changes+0.006q = 0.922
937 country-years (one country in one year), 88 countries, 2013–2024, about 11 years each on average. Share of the variation that happens within countries over time: 16% for DTP3 immunisation, 27% for Marriage rate (UN). 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): +0.026. 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.
This curve peaks at the edge of the window (lag -7), so it is still drifting where the search stops. That pattern usually reflects a slow trend left over in the data, not a link with real timing. The peak value should not be read as the “true” link at the right lag.
The data
% of children aged 12-23 months | marriages per 1,000 people | Years | |
|---|---|---|---|
| St. Vincent and the Grenadines VCT | 99% | 3.13 | 2024, 2021 |
| Turkiye TUR | 99% | 6.65 | 2024 |
| Portugal PRT | 99% | 3.53 | 2024, 2023 |
| Luxembourg LUX | 99% | 3.82 | 2024 |
| St. Lucia LCA | 99% | 3.58 | 2024, 2019 |
| Kuwait KWT | 99% | 2.78 | 2024, 2023 |
| Japan JPN | 99% | 3.81 | 2024, 2023 |
| Jamaica JAM | 99% | 6.13 | 2024, 2018 |
| Hungary HUN | 99% | 4.86 | 2024 |
| Costa Rica CRI | 99% | 4.17 | 2024 |
| Brunei Darussalam BRN | 99% | 5.59 | 2024, 2023 |
| Kazakhstan KAZ | 98% | 6.13 | 2024 |
| Israel ISR | 98% | 4.9 | 2024, 2023 |
| Iran, Islamic Rep. IRN | 98% | 6.77 | 2024, 2021 |
| Guyana GUY | 98% | 5.38 | 2024, 2017 |
World Bank, World Development Indicators
United Nations Statistics Division, Demographic Yearbook, 2017 to 2024 editions: tables of marriages and crude marriage rates, and of divorces and crude divorce rates, by urban/rural residence.
Sources
DTP3 immunisation
Immunization, DPT (% of children ages 12-23 months)
WHO and UNICEF · CC BY 4.0 · updated quarterly
Three doses of the diphtheria, tetanus and whooping cough (pertussis) vaccine, the standard measure of a routine vaccination system. Measles coverage is published the same way and moves with it almost exactly, so only one of the two is here.
Marriage rate (UN)
Crude marriage rate, countries with complete registration
United Nations Statistics Division · UNdata terms of use · updated annual (each edition covers the latest five years)
Marriages registered in the year per 1,000 people, from each country's civil register, as published in the UN Demographic Yearbook. Only countries whose register the UN rates as at least 90% complete are included. That leaves out most of Africa and much of South Asia, where many marriages are religious or customary and never registered, so the countries here lean toward places with strong record-keeping. Countries whose figures include visitors' weddings (Seychelles, about 30 per 1,000, and the Bahamas) are left out, since they show a wedding industry rather than how often residents marry. So is Equatorial Guinea, whose register is far too thin to be complete. Each yearly edition covers five years; where they overlap, the newest is used, since countries revise. Where both exist it matches the OECD series almost exactly (r = 0.998), so the two are treated as one measure, not two findings. The low points in 2020 are the pandemic. A few small island territories, such as the Turks and Caicos Islands (11 to 16 per 1,000), probably count visitors' weddings without saying so. No "better" direction is set: it describes how people live.
How this was computed
Data used: most recent value in 2010-2025; values come from 2013–2024. 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 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore DTP3 immunisation and Marriage rate (UN)
This page shows that two measures go together. It does not show that DTP3 immunisation changes Marriage rate (UN), or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with DTP3 immunisation or Marriage rate (UN)
- Marriage rate (UN) vs Women's age at first marriage before -0.37 → after adjusting -0.43
- DTP3 immunisation vs Skilled birth attendance before +0.61 → after adjusting +0.42
- Civil liberties (FH) vs Marriage rate (UN) before +0.47 → after adjusting +0.42
- Divorce rate (UN) vs Marriage rate (UN) before +0.36 → after adjusting +0.39
- DTP3 immunisation vs Health coverage index before +0.60 → after adjusting +0.36
- Marriage rate (UN) vs Primary completion before +0.09 → after adjusting +0.33
- Marriage rate (UN) vs Women in a union before +0.37 → after adjusting +0.32
- DTP3 immunisation vs Education score before +0.56 → after adjusting +0.29