Across 178 countries, Infant mortality and Out of school, primary rise and fall together at r = +0.57 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.33 (q = 0.012, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a weak positive link remains. Caution: correlation moves sharply once outliers are trimmed.
Comparing countries across the middle half of infant mortality, 4.7 to 27.4 per 1,000 live births, out of school, primary is worse by 8.82% of primary-age children at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 7.24% of primary-age children.
Link before adjusting (r)+0.569p = 1.1e-16 · 178 countries
After adjusting for national income+0.331p = 6.9e-6 · likely range [+0.19, +0.46]
p, allowing for regions0.000standard error 0.047 · 7 regions
Check for luck (q)0.012across 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.
Infant mortality · per 1,000 live birthslink with income -0.86 · proxy
Out of school, primary · % of primary-age childrenlink with income -0.45 · 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
+0.569
1.1e-16
178
By rank (Spearman), not adjusted
+0.528
3.8e-14
178
Standard (Pearson), adjusted for national income
+0.331
6.9e-6
178
By rank (Spearman), adjusted for national income
+0.245
0.001
178
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 178 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: +0.238 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from +0.268 (without GNQ) to +0.367 (without CPV). 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: GNQ (-0.063).
Fragile: this link may not hold up.
correlation moves sharply once outliers are trimmed
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.
n
r
East Asia & Pacific
28
-0.16
Europe & Central Asia
50
-0.04
Latin America & Caribbean
30
+0.20
Middle East, North Africa, Afghanistan & Pakistan
18
+0.28
Sub-Saharan Africa
44
+0.25
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
60
+0.31
Middle third
59
+0.32
Richest third
59
+0.69
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
106
+0.29
Muslims
44
+0.35
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
23
+0.26
Never a European colony
19
+0.72
Spain
20
+0.81
United Kingdom
59
+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 = +0.157 after dropping 21 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 35years. 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 = +0.521) but mostly disappears in year-to-year changes (r = +0.048). That points to slow trends particular to each country, not the two measures moving together from year to year.
Across countries (adjusted)+0.331for comparison
Within countries+0.657each country vs itself
…and vs the same year elsewhere+0.521q = 0.000 · 181 countries
Year-on-year changes+0.048q = 0.403
Read with care.
The association is much weaker in year-on-year changes than in levels, which points to shared country-specific trends.
3,612 country-years (one country in one year), 181 countries, 1990–2024, about 20 years each on average. Share of the variation that happens within countries over time: 17% for Infant mortality, 27% for Out of school, primary. 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): +0.521. 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
per 1,000 live births
% of primary-age children
Years
Nigeria NGA
69.8
24.3%
2024, 2023
Niger NER
65.6
40.4%
2024
Liberia LBR
63.2
38.3%
2024, 2022
Zimbabwe ZWE
62.4
10.5%
2024
Guinea GIN
59.8
14.7%
2024, 2020
Central African Republic CAF
58.8
37.9%
2024, 2012
Chad TCD
56.3
24.8%
2024
Lesotho LSO
56.3
32.2%
2024
Sierra Leone SLE
54.6
0.888%
2024, 2015
Pakistan PAK
48.2
17.9%
2024
Equatorial Guinea GNQ
47.6
65.6%
2024, 2015
Mali MLI
47.5
34%
2024, 2023
Benin BEN
45.2
9.61%
2024, 2022
Cote d'Ivoire CIV
44.8
12.6%
2024
Mozambique MOZ
43.7
1%
2024, 2022
World Bank, World Development Indicators World Bank, World Development Indicators
UNESCO Institute for Statistics · CC BY 4.0 · updated quarterly
Children of primary-school age not enrolled at any level. Treated as measuring the same thing as gross primary enrolment, which is on the site. They are two ways of asking whether children are in school, so their agreement is not a finding.
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 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 Infant mortality and Out of school, primary
This page shows that two measures go together. It does not show that Infant mortality changes Out of school, primary, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with Infant mortality or Out of school, primary