Across 155 countries, Child stunting and DTP3 immunisation rise and fall together at r = -0.52 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.28, which could easily be chance (q = 0.085, 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 child stunting, 5.7% to 23.8% of children under 5, dtp3 immunisation is worse by 9.93% 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 7.27% of children aged 12-23 months.
Link before adjusting (r)-0.519p = 4.5e-12 · 155 countries
After adjusting for national income-0.276p = 0.001 · likely range [-0.42, -0.12]
p, allowing for regions0.013standard error 0.080 · 7 regions
Check for luck (q)0.085across 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.
Child stunting · % of children under 5link with income -0.80 · proxy
DTP3 immunisation · % of children aged 12-23 monthslink with income +0.53 · moderate
“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
-0.519
4.5e-12
155
By rank (Spearman), not adjusted
-0.524
2.5e-12
155
Standard (Pearson), adjusted for national income
-0.276
0.001
155
By rank (Spearman), adjusted for national income
-0.243
0.002
155
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 155 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: +0.243 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from -0.307 (without BDI) to -0.229 (without PNG). 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: PNG (+0.047).
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
26
-0.68
Europe & Central Asia
32
-0.19
Latin America & Caribbean
24
-0.24
Middle East, North Africa, Afghanistan & Pakistan
20
-0.24
Sub-Saharan Africa
46
-0.28
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
52
-0.29
Middle third
51
-0.32
Richest third
52
-0.04
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
86
-0.38
Muslims
48
-0.21
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
-0.14
Never a European colony
21
-0.25
Spain
18
-0.21
United Kingdom
52
-0.46
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 = -0.316 after dropping 6 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 25years. 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 shows up within countries over time (r = -0.179) but mostly disappears in year-to-year changes (r = -0.020). That points to slow trends particular to each country, not the two measures moving together from year to year.
Across countries (adjusted)-0.276for comparison
Within countries-0.245each country vs itself
…and vs the same year elsewhere-0.179q = 0.002 · 161 countries
Year-on-year changes-0.020q = 0.365
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.
4,006 country-years (one country in one year), 161 countries, 2000–2024, about 25 years each on average. Share of the variation that happens within countries over time: 9% for Child stunting, 26% for DTP3 immunisation. 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): -0.179. 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 under 5
% of children aged 12-23 months
Years
Burundi BDI
55.3%
89%
2024
Niger NER
48.3%
86%
2024
Angola AGO
47.7%
64%
2024
Papua New Guinea PNG
47.6%
42%
2024
Timor-Leste TLS
45.4%
83%
2024
Guatemala GTM
44.6%
81%
2024
Congo, Dem. Rep. COD
44.1%
65%
2024
Afghanistan AFG
42%
59%
2024
Central African Republic CAF
38.9%
42%
2024
Madagascar MDG
38.4%
60%
2024
Mozambique MOZ
37%
70%
2024
Ethiopia ETH
35.5%
73%
2024
Sudan SDN
35.4%
39%
2024
Lesotho LSO
35%
86%
2024
Nigeria NGA
33.8%
67%
2024
World Bank, World Development Indicators World Bank, World Development Indicators
Prevalence of stunting, height for age, modelled estimate (% of children under 5)
UNICEF, WHO and World Bank Joint Child Malnutrition Estimates · CC BY 4.0 · updated quarterly
An estimate from a statistical model. The agencies fit a model to household surveys and predict every country and year. So this is smoother than the surveys behind it, and it has values for years nobody measured. The survey-only series never reaches sixty countries in any year.
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.
How this was computed
Data used: most recent value in 2010-2025; values come from 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 Child stunting and DTP3 immunisation
This page shows that two measures go together. It does not show that Child stunting changes DTP3 immunisation, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with Child stunting or DTP3 immunisation