Across 186 countries, DTP3 immunisation and HDI rise and fall together at r = +0.53 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.13, which could easily be chance (q = 0.21, 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 hdi, 0.628 to 0.861 points, dtp3 immunisation is better by 10.4% 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 7.59% of children aged 12-23 months.
Link before adjusting (r)+0.528p = 9.4e-15 · 186 countries
After adjusting for national income+0.135p = 0.068 · likely range [-0.01, +0.27]
p, allowing for regions0.070standard error 0.061 · 7 regions
Check for luck (q)0.214across 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
HDI · index, 0 to 1link with income +0.96 · 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
+0.528
9.4e-15
186
By rank (Spearman), not adjusted
+0.521
2.4e-14
186
Standard (Pearson), adjusted for national income
+0.135
0.068
186
By rank (Spearman), adjusted for national income
+0.070
0.346
186
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 186 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: +0.393 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from +0.116 (without TON) to +0.162 (without LBN). 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: LBN (+0.027).
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
29
+0.43
Europe & Central Asia
50
+0.02
Latin America & Caribbean
31
+0.03
Middle East, North Africa, Afghanistan & Pakistan
22
+0.13
Sub-Saharan Africa
46
+0.15
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
62
+0.28
Middle third
62
-0.04
Richest third
62
-0.12
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
108
+0.22
Muslims
49
+0.03
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
France
25
-0.17
Never a European colony
21
+0.27
Spain
20
+0.07
United Kingdom
63
+0.21
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 = +0.189 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 34years. 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 also shows up within countries over time (r = +0.307). It holds even when looking only at changes from one year to the next (r = +0.069). This is the strongest kind of evidence available here: it holds when each country is compared only with itself, and it is not just a product of shared trends.
Across countries (adjusted)+0.135for comparison
Within countries+0.444each country vs itself
…and vs the same year elsewhere+0.307q = 0.000 · 190 countries
Year-on-year changes+0.069q = 4.0e-5
Read with care.
Almost all of this indicator's variation is between countries, not within them, so the within-country estimate rests on a small part of the data.
The association is much weaker in year-on-year changes than in levels, which points to shared country-specific trends.
5,835 country-years (one country in one year), 190 countries, 1990–2023, about 31 years each on average. Share of the variation that happens within countries over time: 9% for DTP3 immunisation, 30% for HDI. 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): +0.307. 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
% of children aged 12-23 months
index, 0 to 1
Years
St. Vincent and the Grenadines VCT
99%
0.798
2024, 2023
Turkiye TUR
99%
0.853
2024, 2023
Tonga TON
99%
0.769
2024, 2023
Portugal PRT
99%
0.89
2024, 2023
Oman OMN
99%
0.858
2024, 2023
Naoero NRU
99%
0.703
2024, 2023
Maldives MDV
99%
0.766
2024, 2023
Luxembourg LUX
99%
0.922
2024, 2023
St. Lucia LCA
99%
0.748
2024, 2023
Kuwait KWT
99%
0.852
2024, 2023
Japan JPN
99%
0.925
2024, 2023
Jamaica JAM
99%
0.72
2024, 2023
Hungary HUN
99%
0.87
2024, 2023
Costa Rica CRI
99%
0.833
2024, 2023
Brunei Darussalam BRN
99%
0.837
2024, 2023
World Bank, World Development Indicators United Nations Development Programme, Human Development Report 2025
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.
United Nations Development Programme, Human Development Report Office · via Our World in Data · CC BY 3.0 IGO · updated annual
The geometric mean (a kind of average that multiplies the parts together) of three parts: income per person (GNI per capita), life expectancy, and schooling (expected years and average years). All four inputs are on this site, and each is flagged. So a link between the HDI and any of them is shown for what it is: the index matching a part of itself. For the same reason it is kept out of this site's own topic scores. Those already contain its parts, and adding it would count each twice. It is the most-cited development index there is. It is here mostly so its parts can be read separately.
How this was computed
Data used: most recent value in 2010-2025; values come from 2023–2024. 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 HDI
This page shows that two measures go together. It does not show that DTP3 immunisation changes HDI, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.