placestats

Child stunting vs. PISA reading

Fades after adjusting for income

Across 64 countries, Child stunting and PISA reading rise and fall together at r = -0.51 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.24, which could easily be chance (q = 0.076, 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 pisa reading, 374 to 472 PISA points, child stunting is better by 6.69% of children under 5 at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 4.3% of children under 5.

Link before adjusting (r)-0.508p = 1.8e-5 · 64 countries
After adjusting for national income-0.239p = 0.059 · likely range [-0.46, +0.01]
p, allowing for regions0.120standard error 0.121 · 5 regions
Check for luck (q)0.076across 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
PISA reading · PISA pointslink with income +0.77 · high

Both of these rise and fall closely with national income, so a strong link between them before adjusting was close to certain. Read the adjusted figure, not the first one.

“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.

Every country as a dot

Child stunting · % of children under 5 →PISA reading · PISA points →1%44.6%329543Albania: 7.4% of children under 5, 358 PISA pointsArgentina: 10.7% of children under 5, 401 PISA pointsAustralia: 3.1% of children under 5, 498 PISA pointsBelgium: 2.6% of children under 5, 479 PISA pointsBulgaria: 5.5% of children under 5, 404 PISA pointsBosnia and Herzegovina: 7.9% of children under 5, 403 PISA pointsBelarus: 1.1% of children under 5, 474 PISA pointsBrazil: 8.9% of children under 5, 410 PISA pointsBrunei Darussalam: 9.9% of children under 5, 429 PISA pointsChile: 1.7% of children under 5, 448 PISA pointsColombia: 11.6% of children under 5, 409 PISA pointsCosta Rica: 10.6% of children under 5, 415 PISA pointsCzechia: 2.4% of children under 5, 489 PISA pointsGermany: 2.2% of children under 5, 480 PISA pointsDominican Republic: 5.6% of children under 5, 351 PISA pointsAlgeria: 8.9% of children under 5, 350 PISA pointsEstonia: 1.3% of children under 5, 511 PISA pointsFinland: 1.7% of children under 5, 490 PISA pointsUnited Kingdom: 3.5% of children under 5, 494 PISA pointsGeorgia: 4.7% of children under 5, 374 PISA pointsGreece: 2% of children under 5, 438 PISA pointsGuatemala: 44.6% of children under 5, 374 PISA pointsIndonesia: 22.6% of children under 5, 359 PISA pointsIreland: 2.2% of children under 5, 516 PISA pointsJamaica: 6.9% of children under 5, 410 PISA pointsJordan: 7.7% of children under 5, 342 PISA pointsJapan: 5.2% of children under 5, 516 PISA pointsKazakhstan: 4.4% of children under 5, 386 PISA pointsCambodia: 22% of children under 5, 329 PISA pointsKorea, Rep.: 1.8% of children under 5, 515 PISA pointsLebanon: 10.1% of children under 5, 353 PISA pointsLithuania: 1.6% of children under 5, 472 PISA pointsLatvia: 1.7% of children under 5, 475 PISA pointsMorocco: 13.7% of children under 5, 339 PISA pointsMoldova: 4.2% of children under 5, 411 PISA pointsMexico: 13.1% of children under 5, 415 PISA pointsNorth Macedonia: 3.8% of children under 5, 359 PISA pointsMalta: 3.5% of children under 5, 445 PISA pointsMontenegro: 8% of children under 5, 405 PISA pointsMongolia: 7.1% of children under 5, 378 PISA pointsMalaysia: 24.3% of children under 5, 388 PISA pointsNetherlands: 1.6% of children under 5, 459 PISA pointsPanama: 14% of children under 5, 392 PISA pointsPeru: 10.6% of children under 5, 408 PISA pointsPhilippines: 27.7% of children under 5, 347 PISA pointsPoland: 1% of children under 5, 489 PISA pointsPortugal: 3.2% of children under 5, 477 PISA pointsParaguay: 3.2% of children under 5, 373 PISA pointsWest Bank and Gaza: 8% of children under 5, 349 PISA pointsQatar: 5.4% of children under 5, 419 PISA pointsRomania: 7% of children under 5, 428 PISA pointsSaudi Arabia: 11.1% of children under 5, 383 PISA pointsSingapore: 2.8% of children under 5, 543 PISA pointsEl Salvador: 9.4% of children under 5, 365 PISA pointsSerbia: 4.6% of children under 5, 440 PISA pointsThailand: 12.3% of children under 5, 379 PISA pointsTrinidad and Tobago: 7.8% of children under 5, 427 PISA pointsTunisia: 8.9% of children under 5, 361 PISA pointsTurkiye: 5.5% of children under 5, 456 PISA pointsUkraine: 11.7% of children under 5, 428 PISA pointsUruguay: 6.5% of children under 5, 430 PISA pointsUnited States: 4.2% of children under 5, 504 PISA pointsUzbekistan: 6.7% of children under 5, 336 PISA pointsViet Nam: 19.2% of children under 5, 462 PISA pointsDOMESTGTMKHMKORMKDMYSPHLSGPUZBVNM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5081.8e-564
By rank (Spearman), not adjusted-0.6612.8e-964
Standard (Pearson), adjusted for national income-0.2390.05964
By rank (Spearman), adjusted for national income-0.3580.00464

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 64 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: +0.269 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.313 (without GTM) to -0.199 (without MYS). 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: GTM (-0.074).

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.

nr
East Asia & Pacific12-0.47
Europe & Central Asia27-0.28
Latin America & Caribbean15-0.18

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.

nr
Poorest third22-0.02
Middle third21-0.38
Richest third21-0.72

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.

nr
Christians38-0.18
Muslims16-0.18

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.

nr
Spain14-0.04

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 = -0.267 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 23years. 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 = -0.236, 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 child stunting moved did not tend to see their pisa reading move with it.

Across countries (adjusted)-0.239for comparison
Within countries-0.209each country vs itself
…and vs the same year elsewhere-0.236q = 0.364 · 36 countries
Year-on-year changes—q = —
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.

255 country-years (one country in one year), 36 countries, 2000–2022, about 7 years each on average. Share of the variation that happens within countries over time: 7% for Child stunting, 10% for PISA reading. 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

0.40−0.4-60+6years PISA reading trails Child stunting →lag -6: r = -0.297 (n = 212)lag -5: r = -0.301 (n = 212)lag -4: r = -0.305 (n = 212)lag -3: r = -0.310 (n = 212)lag -2: r = -0.226 (n = 255)lag -1: r = -0.231 (n = 255)lag +0: r = -0.236 (n = 255)lag +1: r = -0.064 (n = 231)lag +2: r = -0.079 (n = 231)lag +3: r = -0.103 (n = 231)lag +4: r = -0.092 (n = 205)lag +5: r = -0.115 (n = 205)lag +6: r = -0.133 (n = 205)

Same year (lag 0): -0.236. 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 largest value on this curve (-0.31 at lag -3) is higher than the same-year one by 0.07. That gap is not a finding. It is the largest of 13 closely related estimates, and picking the biggest of many tests always makes it look bigger. That is exactly why nothing on this site is ranked or chosen by lag.

The data


% of children under 5
PISA points		Years
Guatemala GTM44.6%3742024, 2022
Philippines PHL27.7%3472024, 2022
Malaysia MYS24.3%3882024, 2022
Indonesia IDN22.6%3592024, 2022
Cambodia KHM22%3292024, 2022
Viet Nam VNM19.2%4622024, 2022
Panama PAN14%3922024, 2022
Morocco MAR13.7%3392024, 2022
Mexico MEX13.1%4152024, 2022
Thailand THA12.3%3792024, 2022
Ukraine UKR11.7%4282024, 2022
Colombia COL11.6%4092024, 2022
Saudi Arabia SAU11.1%3832024, 2022
Argentina ARG10.7%4012024, 2022
Peru PER10.6%4082024, 2022

World Bank, World Development Indicators
OECD databases as named on each indicator: PISA, Social Expenditure Database (SOCX), Income Distribution Database, Development Assistance Committee statistics, Family Database, Government at a Glance, Corporate Tax Statistics, employment and environment statistics

Sources

Child stunting

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.

PISA reading

PISA mean reading score

OECD · via Our World in Data · CC BY 4.0 (OECD terms and conditions) · updated annual, except the snapshots noted per indicator

How this was computed

Data used: most recent value in 2010-2025; values come from 2015–2024. 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 5 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 PISA reading

This page shows that two measures go together. It does not show that Child stunting changes PISA reading, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Child stunting or PISA reading