placestats

Child stunting vs. Internet users

Fades after adjusting for income

Across 155 countries, Child stunting and Internet users rise and fall together at r = -0.78 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.38, which could easily be chance (q = 0.053, 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 internet users, 45.6% to 89.3% of population, child stunting is better by 15.9% of children under 5 at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 9.49% of children under 5.

Link before adjusting (r)-0.782p = 3.0e-33 · 155 countries
After adjusting for national income-0.376p = 1.6e-6 · likely range [-0.50, -0.23]
p, allowing for regions0.007standard error 0.093 · 7 regions
Check for luck (q)0.053across 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
Internet users · % of populationlink with income +0.85 · proxy

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 →Internet users · % of population →1%55.3%8.6%100%Afghanistan: 42% of children under 5, 16.1% of populationAngola: 47.7% of children under 5, 40.7% of populationAlbania: 7.4% of children under 5, 85.9% of populationArgentina: 10.7% of children under 5, 89.7% of populationArmenia: 6.2% of children under 5, 81.3% of populationAustralia: 3.1% of children under 5, 96.1% of populationAzerbaijan: 6.8% of children under 5, 90.8% of populationBurundi: 55.3% of children under 5, 8.6% of populationBelgium: 2.6% of children under 5, 95.8% of populationBenin: 33.2% of children under 5, 34% of populationBurkina Faso: 19.5% of children under 5, 28.3% of populationBangladesh: 25.1% of children under 5, 53.4% of populationBulgaria: 5.5% of children under 5, 82.4% of populationBahrain: 4.6% of children under 5, 100% of populationBosnia and Herzegovina: 7.9% of children under 5, 86.1% of populationBelarus: 1.1% of children under 5, 94.3% of populationBelize: 11.7% of children under 5, 80% of populationBolivia: 10.7% of children under 5, 79.7% of populationBrazil: 8.9% of children under 5, 84.5% of populationBarbados: 5.8% of children under 5, 70.4% of populationBrunei Darussalam: 9.9% of children under 5, 96.3% of populationBhutan: 17.9% of children under 5, 91.3% of populationBotswana: 21% of children under 5, 57.5% of populationCentral African Republic: 38.9% of children under 5, 13.8% of populationChile: 1.7% of children under 5, 95.6% of populationChina: 4.5% of children under 5, 91.6% of populationCote d'Ivoire: 20.3% of children under 5, 41.4% of populationCameroon: 27.2% of children under 5, 46.3% of populationCongo, Dem. Rep.: 44.1% of children under 5, 19.7% of populationCongo, Rep.: 16.3% of children under 5, 47.3% of populationColombia: 11.6% of children under 5, 79.3% of populationComoros: 17.4% of children under 5, 32.5% of populationCabo Verde: 5.3% of children under 5, 74.7% of populationCosta Rica: 10.6% of children under 5, 87.2% of populationCzechia: 2.4% of children under 5, 87.7% of populationGermany: 2.2% of children under 5, 93.5% of populationDjibouti: 20.9% of children under 5, 65.3% of populationDominican Republic: 5.6% of children under 5, 91% of populationAlgeria: 8.9% of children under 5, 77.4% of populationEcuador: 17.7% of children under 5, 77.2% of populationEgypt, Arab Rep.: 12.9% of children under 5, 74.6% of populationEstonia: 1.3% of children under 5, 92.2% of populationEthiopia: 35.5% of children under 5, 21.9% of populationFinland: 1.7% of children under 5, 93.7% of populationFiji: 7.2% of children under 5, 74.7% of populationGabon: 13.7% of children under 5, 68.7% of populationUnited Kingdom: 3.5% of children under 5, 95.5% of populationGeorgia: 4.7% of children under 5, 83.8% of populationGhana: 15.6% of children under 5, 72.2% of populationGuinea: 26.6% of children under 5, 33.3% of populationGambia, The: 14% of children under 5, 49.5% of populationGuinea-Bissau: 28.3% of children under 5, 29.8% of populationEquatorial Guinea: 17.1% of children under 5, 63.3% of populationGreece: 2% of children under 5, 86.3% of populationGuatemala: 44.6% of children under 5, 60.2% of populationGuyana: 7.1% of children under 5, 83% of populationHonduras: 17.9% of children under 5, 58.6% of populationHaiti: 21.6% of children under 5, 47.9% of populationIndonesia: 22.6% of children under 5, 72.8% of populationIndia: 32.9% of children under 5, 70% of populationIreland: 2.2% of children under 5, 97.2% of populationIran, Islamic Rep.: 4.8% of children under 5, 85.3% of populationIraq: 9.4% of children under 5, 81.5% of populationJamaica: 6.9% of children under 5, 90.1% of populationJordan: 7.7% of children under 5, 95.6% of populationJapan: 5.2% of children under 5, 85.5% of populationKazakhstan: 4.4% of children under 5, 93.4% of populationKenya: 17.9% of children under 5, 35% of populationKyrgyz Republic: 11% of children under 5, 92% of populationCambodia: 22% of children under 5, 68.5% of populationKiribati: 14.7% of children under 5, 89.4% of populationKorea, Rep.: 1.8% of children under 5, 97.9% of populationKuwait: 4.5% of children under 5, 100% of populationLao PDR: 29.9% of children under 5, 65.6% of populationLebanon: 10.1% of children under 5, 80.6% of populationLiberia: 26.9% of children under 5, 32.2% of populationLibya: 9.2% of children under 5, 82% of populationSt. Lucia: 2.8% of children under 5, 68.2% of populationSri Lanka: 10.1% of children under 5, 54.6% of populationLesotho: 35% of children under 5, 51.8% of populationLithuania: 1.6% of children under 5, 89.2% of populationLatvia: 1.7% of children under 5, 92.7% of populationMorocco: 13.7% of children under 5, 91.2% of populationMoldova: 4.2% of children under 5, 77.4% of populationMadagascar: 38.4% of children under 5, 18.7% of populationMaldives: 14.2% of children under 5, 85.2% of populationMexico: 13.1% of children under 5, 83.1% of populationMarshall Islands: 30% of children under 5, 65.9% of populationNorth Macedonia: 3.8% of children under 5, 93.1% of populationMali: 23.2% of children under 5, 36.8% of populationMalta: 3.5% of children under 5, 93.9% of populationMyanmar: 24.5% of children under 5, 45.4% of populationMontenegro: 8% of children under 5, 88.9% of populationMongolia: 7.1% of children under 5, 85.1% of populationMozambique: 37% of children under 5, 20.5% of populationMauritania: 21.5% of children under 5, 45.8% of populationMauritius: 7.8% of children under 5, 73.3% of populationMalawi: 33.2% of children under 5, 19% of populationMalaysia: 24.3% of children under 5, 98% of populationNamibia: 16.4% of children under 5, 64.9% of populationNiger: 48.3% of children under 5, 15.6% of populationNigeria: 33.8% of children under 5, 41.2% of populationNetherlands: 1.6% of children under 5, 97% of populationNepal: 26% of children under 5, 46.3% of populationNaoero: 16% of children under 5, 83% of populationOman: 12.9% of children under 5, 95.3% of populationPakistan: 33.6% of children under 5, 57.3% of populationPanama: 14% of children under 5, 72.8% of populationPeru: 10.6% of children under 5, 82% of populationPhilippines: 27.7% of children under 5, 67.3% of populationPapua New Guinea: 47.6% of children under 5, 18.8% of populationPoland: 1% of children under 5, 88.6% of populationPortugal: 3.2% of children under 5, 88.5% of populationParaguay: 3.2% of children under 5, 81.6% of populationWest Bank and Gaza: 8% of children under 5, 86.6% of populationQatar: 5.4% of children under 5, 98.1% of populationRomania: 7% of children under 5, 91.3% of populationRwanda: 29.8% of children under 5, 31.7% of populationSaudi Arabia: 11.1% of children under 5, 100% of populationSudan: 35.4% of children under 5, 18.6% of populationSenegal: 17.2% of children under 5, 60.1% of populationSingapore: 2.8% of children under 5, 94.4% of populationSolomon Islands: 29.8% of children under 5, 29% of populationSierra Leone: 25.2% of children under 5, 25.1% of populationEl Salvador: 9.4% of children under 5, 66.5% of populationSomalia, Fed. Rep.: 23.9% of children under 5, 27.9% of populationSerbia: 4.6% of children under 5, 87.7% of populationSao Tome and Principe: 10% of children under 5, 59.1% of populationSuriname: 8% of children under 5, 87.4% of populationEswatini: 18.9% of children under 5, 63.4% of populationSeychelles: 6.2% of children under 5, 87.8% of populationSyrian Arab Republic: 23.5% of children under 5, 33.8% of populationChad: 31.5% of children under 5, 12.6% of populationTogo: 23% of children under 5, 39.5% of populationThailand: 12.3% of children under 5, 90.9% of populationTajikistan: 13.1% of children under 5, 55.8% of populationTurkmenistan: 6.5% of children under 5, 18% of populationTimor-Leste: 45.4% of children under 5, 35% of populationTonga: 1.6% of children under 5, 67.4% of populationTrinidad and Tobago: 7.8% of children under 5, 82.2% of populationTunisia: 8.9% of children under 5, 76.5% of populationTurkiye: 5.5% of children under 5, 89.8% of populationTuvalu: 5.3% of children under 5, 35.2% of populationTanzania: 29.9% of children under 5, 31.2% of populationUganda: 23.5% of children under 5, 8.95% of populationUkraine: 11.7% of children under 5, 82.5% of populationUruguay: 6.5% of children under 5, 92% of populationUnited States: 4.2% of children under 5, 94.7% of populationUzbekistan: 6.7% of children under 5, 89.5% of populationViet Nam: 19.2% of children under 5, 84.2% of populationVanuatu: 31% of children under 5, 22.4% of populationSamoa: 8.4% of children under 5, 21.2% of populationSouth Africa: 24.4% of children under 5, 78.4% of populationZambia: 32.3% of children under 5, 17.1% of populationZimbabwe: 23.7% of children under 5, 41.6% of populationAGOBDIGTMIRLKORMYSNERNLDPNGTKMTUVWSM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.7823.0e-33155
By rank (Spearman), not adjusted-0.7682.0e-31155
Standard (Pearson), adjusted for national income-0.3761.6e-6155
By rank (Spearman), adjusted for national income-0.2510.002155

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: +0.406 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.420 (without TKM) to -0.349 (without PSE). 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: TKM (-0.045).

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 & Pacific26-0.22
Europe & Central Asia32-0.03
Latin America & Caribbean24-0.46
Middle East, North Africa, Afghanistan & Pakistan20-0.73
Sub-Saharan Africa46-0.43

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 third52-0.47
Middle third51-0.31
Richest third52+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.

nr
Christians86-0.47
Muslims48-0.46

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
France25-0.25
Never a European colony21-0.34
Spain18-0.59
United Kingdom52-0.26

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 = -0.374 after dropping 1 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.

Within countries over time, there is no link that is clearly more than chance (r = +0.098, 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 internet users move with it.

Across countries (adjusted)-0.376for comparison
Within countries-0.623each country vs itself
…and vs the same year elsewhere+0.098q = 0.305 · 161 countries
Year-on-year changes+0.031q = 0.518
The direction flips. Comparing each country only with itself gives -0.62. Also taking out what happened to the whole world each year gives +0.10. So the first figure was picking up a trend both measures share with worldwide progress, not a link between them.
Read with care.
  • Almost all of the second indicator's variation is between countries, so the within-country estimate rests on a small part of the data.
  • Much of the within-country association disappears once shared global year effects are removed, which points to a common worldwide trend rather than a country-level relationship.

3,843 country-years (one country in one year), 161 countries, 2000–2024, about 24 years each on average. Share of the variation that happens within countries over time: 52% for Child stunting, 9% for Internet users. 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

0.50−0.5-100+10years Internet users trails Child stunting →lag -10: r = 0.465 (n = 3,321)lag -9: r = 0.463 (n = 3,321)lag -8: r = 0.445 (n = 3,457)lag -7: r = 0.424 (n = 3,577)lag -6: r = 0.397 (n = 3,684)lag -5: r = 0.365 (n = 3,774)lag -4: r = 0.324 (n = 3,827)lag -3: r = 0.279 (n = 3,843)lag -2: r = 0.221 (n = 3,848)lag -1: r = 0.161 (n = 3,848)lag +0: r = 0.098 (n = 3,843)lag +1: r = 0.057 (n = 3,693)lag +2: r = 0.014 (n = 3,538)lag +3: r = -0.022 (n = 3,383)lag +4: r = -0.060 (n = 3,234)lag +5: r = -0.096 (n = 3,078)lag +6: r = -0.130 (n = 2,923)lag +7: r = -0.163 (n = 2,768)lag +8: r = -0.190 (n = 2,611)lag +9: r = -0.214 (n = 2,454)lag +10: r = -0.231 (n = 2,298)

Same year (lag 0): +0.098. 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.

This curve peaks at the edge of the window (lag -10), so it is still drifting where the search stops. That pattern usually reflects a slow trend left over in the data, not a link with real timing. The peak value should not be read as the “true” link at the right lag.

The data


% of children under 5
% of population		Years
Burundi BDI55.3%8.6%2024
Niger NER48.3%15.6%2024
Angola AGO47.7%40.7%2024
Papua New Guinea PNG47.6%18.8%2024
Timor-Leste TLS45.4%35%2024, 2021
Guatemala GTM44.6%60.2%2024
Congo, Dem. Rep. COD44.1%19.7%2024
Afghanistan AFG42%16.1%2024
Central African Republic CAF38.9%13.8%2024
Madagascar MDG38.4%18.7%2024
Mozambique MOZ37%20.5%2024
Ethiopia ETH35.5%21.9%2024
Sudan SDN35.4%18.6%2024, 2017
Lesotho LSO35%51.8%2024
Nigeria NGA33.8%41.2%2024

World Bank, World Development Indicators
World Bank, World Development Indicators

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.

Internet users

Individuals using the Internet (% of population)

International Telecommunication Union · CC BY 4.0 · updated quarterly

How this was computed

Data used: most recent value in 2010-2025; values come from 2014–2025. 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 Child stunting and Internet users

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

More links with Child stunting or Internet users