placestats

Child stunting vs. East Asian ancestry

Holds up after adjusting for income

A country is not a person, and ancestry is not destiny. Countries where more people have ancestors from one part of the world also tend to differ on the other measure, and that is all. It does notfollow that people with that ancestry are the people with the different score. Making that leap is called the ecological fallacy: reading a pattern across places as a fact about individual people. Ancestry also goes very closely with region and with history, including colonisation and the Atlantic slave trade, and with national income. So much of what looks like ancestry here is really those. That is what the adjusted figures and the region-by-region view are for. The shares are one estimate, for around the year 2000, of where people’s ancestors lived in 1500, not how anyone identifies.

Across 136 countries, Child stunting and East Asian ancestry rise and fall together at r = +0.08 (on a scale from −1 to +1, where 0 means no link). There is almost no link to explain.

Comparing countries across the middle half of east asian ancestry, 0% to 0.5% of population, child stunting is worse by 0.0171% of children under 5 at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0326% of children under 5.

Link before adjusting (r)+0.083p = 0.335 · 136 countries
After adjusting for national income+0.262p = 0.002 · likely range [+0.10, +0.41]
p, allowing for regions0.302standard error 0.232 · 7 regions
Check for luck (q)0.009across 13,797 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
East Asian ancestry · % of populationlink with income +0.24 · independent

“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 →East Asian ancestry · % of population →1%55.3%0%100%Afghanistan: 42% of children under 5, 0% of populationAngola: 47.7% of children under 5, 0% of populationAlbania: 7.4% of children under 5, 0% of populationArgentina: 10.7% of children under 5, 0% of populationArmenia: 6.2% of children under 5, 0% of populationAustralia: 3.1% of children under 5, 7.1% of populationAzerbaijan: 6.8% of children under 5, 0% of populationBurundi: 55.3% of children under 5, 0% of populationBelgium: 2.6% of children under 5, 0% of populationBenin: 33.2% of children under 5, 0% of populationBurkina Faso: 19.5% of children under 5, 0% of populationBangladesh: 25.1% of children under 5, 0% of populationBulgaria: 5.5% of children under 5, 0% of populationBahrain: 4.6% of children under 5, 0% of populationBosnia and Herzegovina: 7.9% of children under 5, 0% of populationBelarus: 1.1% of children under 5, 0% of populationBelize: 11.7% of children under 5, 0.5% of populationBolivia: 10.7% of children under 5, 0% of populationBrazil: 8.9% of children under 5, 0.8% of populationBhutan: 17.9% of children under 5, 0% of populationBotswana: 21% of children under 5, 0% of populationCentral African Republic: 38.9% of children under 5, 0% of populationChile: 1.7% of children under 5, 0% of populationChina: 4.5% of children under 5, 100% of populationCote d'Ivoire: 20.3% of children under 5, 0% of populationCameroon: 27.2% of children under 5, 0% of populationCongo, Dem. Rep.: 44.1% of children under 5, 0% of populationCongo, Rep.: 16.3% of children under 5, 0% of populationColombia: 11.6% of children under 5, 0% of populationComoros: 17.4% of children under 5, 0% of populationCabo Verde: 5.3% of children under 5, 0% of populationCosta Rica: 10.6% of children under 5, 1% of populationCzechia: 2.4% of children under 5, 0% of populationGermany: 2.2% of children under 5, 0% of populationDominican Republic: 5.6% of children under 5, 0% of populationAlgeria: 8.9% of children under 5, 0% of populationEcuador: 17.7% of children under 5, 0% of populationEgypt, Arab Rep.: 12.9% of children under 5, 0% of populationEstonia: 1.3% of children under 5, 0% of populationEthiopia: 35.5% of children under 5, 0% of populationFinland: 1.7% of children under 5, 0% of populationFiji: 7.2% of children under 5, 52.8% of populationGabon: 13.7% of children under 5, 0% of populationUnited Kingdom: 3.5% of children under 5, 0% of populationGeorgia: 4.7% of children under 5, 0% of populationGhana: 15.6% of children under 5, 0% of populationGuinea: 26.6% of children under 5, 0% of populationGambia, The: 14% of children under 5, 0% of populationGuinea-Bissau: 28.3% of children under 5, 0% of populationEquatorial Guinea: 17.1% of children under 5, 0% of populationGreece: 2% of children under 5, 0% of populationGuatemala: 44.6% of children under 5, 0% of populationGuyana: 7.1% of children under 5, 0.7% of populationHonduras: 17.9% of children under 5, 0% of populationHaiti: 21.6% of children under 5, 0% of populationIndonesia: 22.6% of children under 5, 100% of populationIndia: 32.9% of children under 5, 0% of populationIreland: 2.2% of children under 5, 0% of populationIran, Islamic Rep.: 4.8% of children under 5, 0% of populationIraq: 9.4% of children under 5, 0% of populationJamaica: 6.9% of children under 5, 0.5% of populationJordan: 7.7% of children under 5, 0% of populationJapan: 5.2% of children under 5, 100% of populationKazakhstan: 4.4% of children under 5, 2.1% of populationKenya: 17.9% of children under 5, 0% of populationKyrgyz Republic: 11% of children under 5, 2% of populationCambodia: 22% of children under 5, 100% of populationKorea, Rep.: 1.8% of children under 5, 100% of populationKuwait: 4.5% of children under 5, 0% of populationLao PDR: 29.9% of children under 5, 100% of populationLebanon: 10.1% of children under 5, 0% of populationLiberia: 26.9% of children under 5, 0% of populationLibya: 9.2% of children under 5, 0% of populationSri Lanka: 10.1% of children under 5, 0% of populationLesotho: 35% of children under 5, 0% of populationLithuania: 1.6% of children under 5, 0% of populationLatvia: 1.7% of children under 5, 0% of populationMorocco: 13.7% of children under 5, 0% of populationMoldova: 4.2% of children under 5, 0% of populationMadagascar: 38.4% of children under 5, 0% of populationMexico: 13.1% of children under 5, 0% of populationNorth Macedonia: 3.8% of children under 5, 0% of populationMali: 23.2% of children under 5, 0% of populationMalta: 3.5% of children under 5, 0% of populationMyanmar: 24.5% of children under 5, 97.5% of populationMongolia: 7.1% of children under 5, 98.2% of populationMozambique: 37% of children under 5, 0% of populationMauritania: 21.5% of children under 5, 0% of populationMauritius: 7.8% of children under 5, 3% of populationMalawi: 33.2% of children under 5, 0% of populationMalaysia: 24.3% of children under 5, 92.5% of populationNamibia: 16.4% of children under 5, 0% of populationNiger: 48.3% of children under 5, 0% of populationNigeria: 33.8% of children under 5, 0% of populationNetherlands: 1.6% of children under 5, 0.95% of populationNepal: 26% of children under 5, 0% of populationOman: 12.9% of children under 5, 1.08% of populationPakistan: 33.6% of children under 5, 0% of populationPanama: 14% of children under 5, 1.5% of populationPeru: 10.6% of children under 5, 2% of populationPhilippines: 27.7% of children under 5, 100% of populationPapua New Guinea: 47.6% of children under 5, 100% of populationPoland: 1% of children under 5, 0% of populationPortugal: 3.2% of children under 5, 0.9% of populationParaguay: 3.2% of children under 5, 0% of populationQatar: 5.4% of children under 5, 2.2% of populationRomania: 7% of children under 5, 0% of populationRwanda: 29.8% of children under 5, 0% of populationSaudi Arabia: 11.1% of children under 5, 1.2% of populationSudan: 35.4% of children under 5, 0% of populationSenegal: 17.2% of children under 5, 0% of populationSingapore: 2.8% of children under 5, 92% of populationSierra Leone: 25.2% of children under 5, 0% of populationEl Salvador: 9.4% of children under 5, 0% of populationSomalia, Fed. Rep.: 23.9% of children under 5, 0% of populationEswatini: 18.9% of children under 5, 0% of populationSyrian Arab Republic: 23.5% of children under 5, 0% of populationChad: 31.5% of children under 5, 0% of populationTogo: 23% of children under 5, 0% of populationThailand: 12.3% of children under 5, 100% of populationTajikistan: 13.1% of children under 5, 0% of populationTurkmenistan: 6.5% of children under 5, 0% of populationTimor-Leste: 45.4% of children under 5, 100% of populationTrinidad and Tobago: 7.8% of children under 5, 1.5% of populationTunisia: 8.9% of children under 5, 0% of populationTurkiye: 5.5% of children under 5, 0% of populationTanzania: 29.9% of children under 5, 0% of populationUganda: 23.5% of children under 5, 0% of populationUkraine: 11.7% of children under 5, 0% of populationUruguay: 6.5% of children under 5, 0% of populationUnited States: 4.2% of children under 5, 3.35% of populationUzbekistan: 6.7% of children under 5, 1% of populationViet Nam: 19.2% of children under 5, 100% of populationSouth Africa: 24.4% of children under 5, 0.45% of populationZambia: 32.3% of children under 5, 0% of populationZimbabwe: 23.7% of children under 5, 0% of populationAGOBDIBLRCHNESTJPNKORLAONERPNGPOLTLS

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.0830.335136
By rank (Spearman), not adjusted-0.1030.235136
Standard (Pearson), adjusted for national income+0.2620.002136
By rank (Spearman), adjusted for national income+0.2820.001136

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 136 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: -0.179 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.213 (without PNG) to +0.288 (without GTM). 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 (-0.050).

Fragile: this link may not hold up.
  • correlation moves sharply once outliers are trimmed

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 & Pacific17+0.18
Europe & Central Asia30+0.03
Latin America & Caribbean21-0.01
Middle East, North Africa, Afghanistan & Pakistan18+0.53
Sub-Saharan Africa44-0.03

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 third46+0.46
Middle third45+0.19
Richest third45+0.28

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
Christians74+0.36
Muslims44+0.38

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
France24+0.45
Never a European colony21-0.01
Spain18+0.29
United Kingdom41+0.36

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 = +0.080 after dropping 26 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 0years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Not enough history inside each country to look at this over time. That needs countries measured for several years in a row, and at least one of these measures is measured too rarely.

The data


% of children under 5
% of population		Years
Burundi BDI55.3%0%2024, 2000
Niger NER48.3%0%2024, 2000
Angola AGO47.7%0%2024, 2000
Papua New Guinea PNG47.6%100%2024, 2000
Timor-Leste TLS45.4%100%2024, 2000
Guatemala GTM44.6%0%2024, 2000
Congo, Dem. Rep. COD44.1%0%2024, 2000
Afghanistan AFG42%0%2024, 2000
Central African Republic CAF38.9%0%2024, 2000
Madagascar MDG38.4%0%2024, 2000
Mozambique MOZ37%0%2024, 2000
Ethiopia ETH35.5%0%2024, 2000
Sudan SDN35.4%0%2024, 2000
Lesotho LSO35%0%2024, 2000
Nigeria NGA33.8%0%2024, 2000

World Bank, World Development Indicators
Putterman, L. and Weil, D. N. (2010), 'Post-1500 Population Flows and the Long-Run Determinants of Economic Growth and Inequality', Quarterly Journal of Economics 125(4); World Migration Matrix version 1.1 (2009).

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.

East Asian ancestry

East Asian and Pacific ancestry (share of the population)

Louis Putterman and David N. Weil, Brown University · No licence stated; used with citation · updated one edition (version 1.1, 2009)

The estimated share of today's population whose ancestors in the year 1500 lived in East Asia, Southeast Asia or the Pacific. This is the closest thing to race shares that can be compared across countries: national censuses each use their own race and ethnic categories, and most countries record none. It is about where people's ancestors lived, not how anyone identifies, and it is one estimate for around the year 2000, built from history, migration records and genetic studies. Every country's six ancestry shares add up to 100%, so they are linked to each other by arithmetic. No "better" direction is set.

How this was computed

Data used: most recent value in 2010-2025; values come from 2000–2024. 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 13,797 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Child stunting and East Asian ancestry

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

More links with Child stunting or East Asian ancestry