placestats

Child stunting vs. Labour score

Fades after adjusting for income

Across 155 countries, Child stunting and Labour score rise and fall together at r = -0.53 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.03, which could easily be chance (q = 0.82, 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. Caution: sign flips when a single country is removed.

Comparing countries across the middle half of child stunting, 5.7% to 23.8% of children under 5, labour score is worse by 0.502 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0308 typical gaps.

Link before adjusting (r)-0.530p = 1.4e-12 · 155 countries
After adjusting for national income-0.028p = 0.729 · likely range [-0.19, +0.13]
p, allowing for regions0.701standard error 0.070 · 7 regions
Check for luck (q)0.822across 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
Labour score · typical gaps (standard deviations)link with income +0.79 · 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 →Labour score · typical gaps (standard deviations) →1%55.3%-1.971.36Afghanistan: 42% of children under 5, -1.26 typical gaps (standard deviations)Angola: 47.7% of children under 5, -0.939 typical gaps (standard deviations)Albania: 7.4% of children under 5, -0.39 typical gaps (standard deviations)Argentina: 10.7% of children under 5, 0.34 typical gaps (standard deviations)Armenia: 6.2% of children under 5, -0.302 typical gaps (standard deviations)Australia: 3.1% of children under 5, 0.867 typical gaps (standard deviations)Azerbaijan: 6.8% of children under 5, -0.0868 typical gaps (standard deviations)Burundi: 55.3% of children under 5, -0.275 typical gaps (standard deviations)Belgium: 2.6% of children under 5, 0.682 typical gaps (standard deviations)Benin: 33.2% of children under 5, -0.233 typical gaps (standard deviations)Burkina Faso: 19.5% of children under 5, -0.52 typical gaps (standard deviations)Bangladesh: 25.1% of children under 5, -0.0147 typical gaps (standard deviations)Bulgaria: 5.5% of children under 5, 0.954 typical gaps (standard deviations)Bahrain: 4.6% of children under 5, 1.27 typical gaps (standard deviations)Bosnia and Herzegovina: 7.9% of children under 5, 0.126 typical gaps (standard deviations)Belarus: 1.1% of children under 5, 0.978 typical gaps (standard deviations)Belize: 11.7% of children under 5, 0.0851 typical gaps (standard deviations)Bolivia: 10.7% of children under 5, -0.0485 typical gaps (standard deviations)Brazil: 8.9% of children under 5, 0.16 typical gaps (standard deviations)Barbados: 5.8% of children under 5, 0.485 typical gaps (standard deviations)Brunei Darussalam: 9.9% of children under 5, 0.857 typical gaps (standard deviations)Bhutan: 17.9% of children under 5, -0.0349 typical gaps (standard deviations)Botswana: 21% of children under 5, -1.12 typical gaps (standard deviations)Central African Republic: 38.9% of children under 5, -0.633 typical gaps (standard deviations)Chile: 1.7% of children under 5, 0.344 typical gaps (standard deviations)China: 4.5% of children under 5, 0.367 typical gaps (standard deviations)Cote d'Ivoire: 20.3% of children under 5, -0.122 typical gaps (standard deviations)Cameroon: 27.2% of children under 5, -0.192 typical gaps (standard deviations)Congo, Dem. Rep.: 44.1% of children under 5, -0.523 typical gaps (standard deviations)Congo, Rep.: 16.3% of children under 5, -1.69 typical gaps (standard deviations)Colombia: 11.6% of children under 5, -0.377 typical gaps (standard deviations)Comoros: 17.4% of children under 5, -0.00862 typical gaps (standard deviations)Cabo Verde: 5.3% of children under 5, -0.252 typical gaps (standard deviations)Costa Rica: 10.6% of children under 5, 0.133 typical gaps (standard deviations)Czechia: 2.4% of children under 5, 0.889 typical gaps (standard deviations)Germany: 2.2% of children under 5, 0.988 typical gaps (standard deviations)Djibouti: 20.9% of children under 5, -1.82 typical gaps (standard deviations)Dominican Republic: 5.6% of children under 5, -0.0819 typical gaps (standard deviations)Algeria: 8.9% of children under 5, -0.0627 typical gaps (standard deviations)Ecuador: 17.7% of children under 5, -0.398 typical gaps (standard deviations)Egypt, Arab Rep.: 12.9% of children under 5, 0.367 typical gaps (standard deviations)Estonia: 1.3% of children under 5, 0.558 typical gaps (standard deviations)Ethiopia: 35.5% of children under 5, -0.481 typical gaps (standard deviations)Finland: 1.7% of children under 5, 0.419 typical gaps (standard deviations)Fiji: 7.2% of children under 5, 0.318 typical gaps (standard deviations)Gabon: 13.7% of children under 5, -0.844 typical gaps (standard deviations)United Kingdom: 3.5% of children under 5, 0.635 typical gaps (standard deviations)Georgia: 4.7% of children under 5, -0.418 typical gaps (standard deviations)Ghana: 15.6% of children under 5, 0.00187 typical gaps (standard deviations)Guinea: 26.6% of children under 5, -0.539 typical gaps (standard deviations)Gambia, The: 14% of children under 5, -0.899 typical gaps (standard deviations)Guinea-Bissau: 28.3% of children under 5, -0.255 typical gaps (standard deviations)Equatorial Guinea: 17.1% of children under 5, 0.255 typical gaps (standard deviations)Greece: 2% of children under 5, 0.426 typical gaps (standard deviations)Guatemala: 44.6% of children under 5, 0.48 typical gaps (standard deviations)Guyana: 7.1% of children under 5, -0.0857 typical gaps (standard deviations)Honduras: 17.9% of children under 5, -0.175 typical gaps (standard deviations)Haiti: 21.6% of children under 5, -1.28 typical gaps (standard deviations)Indonesia: 22.6% of children under 5, 0.169 typical gaps (standard deviations)India: 32.9% of children under 5, -0.486 typical gaps (standard deviations)Ireland: 2.2% of children under 5, 0.813 typical gaps (standard deviations)Iran, Islamic Rep.: 4.8% of children under 5, -0.0514 typical gaps (standard deviations)Iraq: 9.4% of children under 5, -0.409 typical gaps (standard deviations)Jamaica: 6.9% of children under 5, 0.511 typical gaps (standard deviations)Jordan: 7.7% of children under 5, -0.133 typical gaps (standard deviations)Japan: 5.2% of children under 5, 1.03 typical gaps (standard deviations)Kazakhstan: 4.4% of children under 5, 0.516 typical gaps (standard deviations)Kenya: 17.9% of children under 5, -0.274 typical gaps (standard deviations)Kyrgyz Republic: 11% of children under 5, 0.54 typical gaps (standard deviations)Cambodia: 22% of children under 5, 0.369 typical gaps (standard deviations)Kiribati: 14.7% of children under 5, -1.29 typical gaps (standard deviations)Korea, Rep.: 1.8% of children under 5, 0.822 typical gaps (standard deviations)Kuwait: 4.5% of children under 5, 1.15 typical gaps (standard deviations)Lao PDR: 29.9% of children under 5, -0.16 typical gaps (standard deviations)Lebanon: 10.1% of children under 5, 0.107 typical gaps (standard deviations)Liberia: 26.9% of children under 5, -0.308 typical gaps (standard deviations)Libya: 9.2% of children under 5, -0.574 typical gaps (standard deviations)St. Lucia: 2.8% of children under 5, -0.149 typical gaps (standard deviations)Sri Lanka: 10.1% of children under 5, 0.307 typical gaps (standard deviations)Lesotho: 35% of children under 5, -0.581 typical gaps (standard deviations)Lithuania: 1.6% of children under 5, 0.626 typical gaps (standard deviations)Latvia: 1.7% of children under 5, 0.673 typical gaps (standard deviations)Morocco: 13.7% of children under 5, -0.0339 typical gaps (standard deviations)Moldova: 4.2% of children under 5, 0.412 typical gaps (standard deviations)Madagascar: 38.4% of children under 5, -0.463 typical gaps (standard deviations)Maldives: 14.2% of children under 5, 0.686 typical gaps (standard deviations)Mexico: 13.1% of children under 5, 0.513 typical gaps (standard deviations)Marshall Islands: 30% of children under 5, -1.09 typical gaps (standard deviations)North Macedonia: 3.8% of children under 5, 0.0322 typical gaps (standard deviations)Mali: 23.2% of children under 5, -0.283 typical gaps (standard deviations)Malta: 3.5% of children under 5, 0.947 typical gaps (standard deviations)Myanmar: 24.5% of children under 5, -0.0589 typical gaps (standard deviations)Montenegro: 8% of children under 5, -0.0101 typical gaps (standard deviations)Mongolia: 7.1% of children under 5, 0.223 typical gaps (standard deviations)Mozambique: 37% of children under 5, -0.745 typical gaps (standard deviations)Mauritania: 21.5% of children under 5, -0.477 typical gaps (standard deviations)Mauritius: 7.8% of children under 5, 0.632 typical gaps (standard deviations)Malawi: 33.2% of children under 5, -0.169 typical gaps (standard deviations)Malaysia: 24.3% of children under 5, 0.654 typical gaps (standard deviations)Namibia: 16.4% of children under 5, -0.775 typical gaps (standard deviations)Niger: 48.3% of children under 5, -0.233 typical gaps (standard deviations)Nigeria: 33.8% of children under 5, -0.128 typical gaps (standard deviations)Netherlands: 1.6% of children under 5, 0.804 typical gaps (standard deviations)Nepal: 26% of children under 5, -0.934 typical gaps (standard deviations)Naoero: 16% of children under 5, -1.38 typical gaps (standard deviations)Oman: 12.9% of children under 5, 1.04 typical gaps (standard deviations)Pakistan: 33.6% of children under 5, -0.988 typical gaps (standard deviations)Panama: 14% of children under 5, 0.0819 typical gaps (standard deviations)Peru: 10.6% of children under 5, -0.454 typical gaps (standard deviations)Philippines: 27.7% of children under 5, 0.559 typical gaps (standard deviations)Papua New Guinea: 47.6% of children under 5, -0.175 typical gaps (standard deviations)Poland: 1% of children under 5, 0.842 typical gaps (standard deviations)Portugal: 3.2% of children under 5, 0.843 typical gaps (standard deviations)Paraguay: 3.2% of children under 5, -0.242 typical gaps (standard deviations)West Bank and Gaza: 8% of children under 5, -0.578 typical gaps (standard deviations)Qatar: 5.4% of children under 5, 1.36 typical gaps (standard deviations)Romania: 7% of children under 5, 0.637 typical gaps (standard deviations)Rwanda: 29.8% of children under 5, -0.108 typical gaps (standard deviations)Saudi Arabia: 11.1% of children under 5, 0.782 typical gaps (standard deviations)Sudan: 35.4% of children under 5, -1.35 typical gaps (standard deviations)Senegal: 17.2% of children under 5, -0.0349 typical gaps (standard deviations)Singapore: 2.8% of children under 5, 1.05 typical gaps (standard deviations)Solomon Islands: 29.8% of children under 5, -0.0344 typical gaps (standard deviations)Sierra Leone: 25.2% of children under 5, -0.503 typical gaps (standard deviations)El Salvador: 9.4% of children under 5, 0.523 typical gaps (standard deviations)Somalia, Fed. Rep.: 23.9% of children under 5, -1.05 typical gaps (standard deviations)Serbia: 4.6% of children under 5, 0.409 typical gaps (standard deviations)Sao Tome and Principe: 10% of children under 5, -0.0345 typical gaps (standard deviations)Suriname: 8% of children under 5, 0.385 typical gaps (standard deviations)Eswatini: 18.9% of children under 5, -1.97 typical gaps (standard deviations)Seychelles: 6.2% of children under 5, 0.418 typical gaps (standard deviations)Syrian Arab Republic: 23.5% of children under 5, -0.472 typical gaps (standard deviations)Chad: 31.5% of children under 5, -0.409 typical gaps (standard deviations)Togo: 23% of children under 5, -0.201 typical gaps (standard deviations)Thailand: 12.3% of children under 5, 0.466 typical gaps (standard deviations)Tajikistan: 13.1% of children under 5, 0.278 typical gaps (standard deviations)Turkmenistan: 6.5% of children under 5, 0.492 typical gaps (standard deviations)Timor-Leste: 45.4% of children under 5, 0.141 typical gaps (standard deviations)Tonga: 1.6% of children under 5, 0.576 typical gaps (standard deviations)Trinidad and Tobago: 7.8% of children under 5, 0.701 typical gaps (standard deviations)Tunisia: 8.9% of children under 5, -0.205 typical gaps (standard deviations)Turkiye: 5.5% of children under 5, 0.224 typical gaps (standard deviations)Tuvalu: 5.3% of children under 5, -0.6 typical gaps (standard deviations)Tanzania: 29.9% of children under 5, -0.328 typical gaps (standard deviations)Uganda: 23.5% of children under 5, -0.25 typical gaps (standard deviations)Ukraine: 11.7% of children under 5, 0.208 typical gaps (standard deviations)Uruguay: 6.5% of children under 5, 0.298 typical gaps (standard deviations)United States: 4.2% of children under 5, 0.862 typical gaps (standard deviations)Uzbekistan: 6.7% of children under 5, 0.368 typical gaps (standard deviations)Viet Nam: 19.2% of children under 5, 0.283 typical gaps (standard deviations)Vanuatu: 31% of children under 5, -0.495 typical gaps (standard deviations)Samoa: 8.4% of children under 5, 0.181 typical gaps (standard deviations)South Africa: 24.4% of children under 5, -1.51 typical gaps (standard deviations)Zambia: 32.3% of children under 5, -0.432 typical gaps (standard deviations)Zimbabwe: 23.7% of children under 5, -0.673 typical gaps (standard deviations)AFGAGOBDIBHRBLRCOGDJIGTMQATSDNSWZTLS

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5301.4e-12155
By rank (Spearman), not adjusted-0.6412.6e-19155
Standard (Pearson), adjusted for national income-0.0280.729155
By rank (Spearman), adjusted for national income-0.1250.122155

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: +0.501 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.054 (without GTM) to +0.012 (without AGO). 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: AGO (+0.040).

Fragile: this link may not hold up.
  • sign flips when a single country is removed
  • 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.

nr
East Asia & Pacific26+0.07
Europe & Central Asia32-0.21
Latin America & Caribbean24+0.10
Middle East, North Africa, Afghanistan & Pakistan20-0.11
Sub-Saharan Africa46-0.13

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+0.14
Middle third51-0.29
Richest third52+0.03

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
Christians86-0.06
Muslims48+0.00

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+0.15
Never a European colony21-0.22
Spain18+0.40
United Kingdom52-0.14

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 = -0.048 after dropping 3 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

typical gaps (standard deviations)
Years
Burundi BDI55.3%-0.2752024, 2025
Niger NER48.3%-0.2332024, 2025
Angola AGO47.7%-0.9392024, 2025
Papua New Guinea PNG47.6%-0.1752024, 2025
Timor-Leste TLS45.4%0.1412024, 2025
Guatemala GTM44.6%0.482024, 2025
Congo, Dem. Rep. COD44.1%-0.5232024, 2025
Afghanistan AFG42%-1.262024, 2025
Central African Republic CAF38.9%-0.6332024, 2025
Madagascar MDG38.4%-0.4632024, 2025
Mozambique MOZ37%-0.7452024, 2025
Ethiopia ETH35.5%-0.4812024, 2025
Sudan SDN35.4%-1.352024, 2022
Lesotho LSO35%-0.5812024, 2025
Nigeria NGA33.8%-0.1282024, 2025

World Bank, World Development Indicators
un_sdg; wdi

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.

Labour score

Labour score

PlaceStats · via PlaceStats · Derived work; each member keeps its own licence · updated recomputed with the panel

The average of 4 measures from 2 publishers. Each measure is first put on a common scale: 0 is the average country in an average year, and 1 is a typical gap between countries (a standard deviation). Each is turned so that higher is better. Measures are averaged within each publisher first, so a publisher with many measures does not count for more. Members: Informal employment, Vulnerable employment, Youth not in work or study, Unemployment.

How this was computed

Data used: most recent value in 2010-2025; values come from 2021–2025. 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 Labour score

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

More links with Child stunting or Labour score