placestats

Child stunting vs. Physicians

Fades after adjusting for income

Across 155 countries, Child stunting and Physicians rise and fall together at r = -0.69 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.28, which could easily be chance (q = 0.16, 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 child stunting, 5.7% to 23.8% of children under 5, physicians is worse by 1.62 per 1,000 people at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.685 per 1,000 people.

Link before adjusting (r)-0.694p = 1.5e-23 · 155 countries
After adjusting for national income-0.283p = 0.000 · likely range [-0.42, -0.13]
p, allowing for regions0.042standard error 0.110 · 7 regions
Check for luck (q)0.165across 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
Physicians · per 1,000 peoplelink 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 →Physicians · per 1,000 people →1%55.3%0.0386.6Afghanistan: 42% of children under 5, 0.317 per 1,000 peopleAngola: 47.7% of children under 5, 0.244 per 1,000 peopleAlbania: 7.4% of children under 5, 1.88 per 1,000 peopleArgentina: 10.7% of children under 5, 5.11 per 1,000 peopleArmenia: 6.2% of children under 5, 3.36 per 1,000 peopleAustralia: 3.1% of children under 5, 4.09 per 1,000 peopleAzerbaijan: 6.8% of children under 5, 3.19 per 1,000 peopleBurundi: 55.3% of children under 5, 0.078 per 1,000 peopleBelgium: 2.6% of children under 5, 3.57 per 1,000 peopleBenin: 33.2% of children under 5, 0.216 per 1,000 peopleBurkina Faso: 19.5% of children under 5, 0.148 per 1,000 peopleBangladesh: 25.1% of children under 5, 0.722 per 1,000 peopleBulgaria: 5.5% of children under 5, 4.33 per 1,000 peopleBahrain: 4.6% of children under 5, 0.741 per 1,000 peopleBosnia and Herzegovina: 7.9% of children under 5, 2.58 per 1,000 peopleBelarus: 1.1% of children under 5, 4.72 per 1,000 peopleBelize: 11.7% of children under 5, 1.09 per 1,000 peopleBolivia: 10.7% of children under 5, 1.28 per 1,000 peopleBrazil: 8.9% of children under 5, 2.36 per 1,000 peopleBarbados: 5.8% of children under 5, 2.96 per 1,000 peopleBrunei Darussalam: 9.9% of children under 5, 1.89 per 1,000 peopleBhutan: 17.9% of children under 5, 0.553 per 1,000 peopleBotswana: 21% of children under 5, 0.379 per 1,000 peopleCentral African Republic: 38.9% of children under 5, 0.074 per 1,000 peopleChile: 1.7% of children under 5, 3.33 per 1,000 peopleChina: 4.5% of children under 5, 3.11 per 1,000 peopleCote d'Ivoire: 20.3% of children under 5, 0.166 per 1,000 peopleCameroon: 27.2% of children under 5, 0.136 per 1,000 peopleCongo, Dem. Rep.: 44.1% of children under 5, 0.208 per 1,000 peopleCongo, Rep.: 16.3% of children under 5, 0.173 per 1,000 peopleColombia: 11.6% of children under 5, 2.54 per 1,000 peopleComoros: 17.4% of children under 5, 0.424 per 1,000 peopleCabo Verde: 5.3% of children under 5, 0.73 per 1,000 peopleCosta Rica: 10.6% of children under 5, 2.69 per 1,000 peopleCzechia: 2.4% of children under 5, 4.35 per 1,000 peopleGermany: 2.2% of children under 5, 4.53 per 1,000 peopleDjibouti: 20.9% of children under 5, 0.211 per 1,000 peopleDominican Republic: 5.6% of children under 5, 2.43 per 1,000 peopleAlgeria: 8.9% of children under 5, 1.66 per 1,000 peopleEcuador: 17.7% of children under 5, 2.31 per 1,000 peopleEgypt, Arab Rep.: 12.9% of children under 5, 0.671 per 1,000 peopleEstonia: 1.3% of children under 5, 3.47 per 1,000 peopleEthiopia: 35.5% of children under 5, 0.143 per 1,000 peopleFinland: 1.7% of children under 5, 3.61 per 1,000 peopleFiji: 7.2% of children under 5, 0.813 per 1,000 peopleGabon: 13.7% of children under 5, 0.521 per 1,000 peopleUnited Kingdom: 3.5% of children under 5, 3.3 per 1,000 peopleGeorgia: 4.7% of children under 5, 5.64 per 1,000 peopleGhana: 15.6% of children under 5, 0.266 per 1,000 peopleGuinea: 26.6% of children under 5, 0.21 per 1,000 peopleGambia, The: 14% of children under 5, 0.09 per 1,000 peopleGuinea-Bissau: 28.3% of children under 5, 0.252 per 1,000 peopleEquatorial Guinea: 17.1% of children under 5, 0.153 per 1,000 peopleGreece: 2% of children under 5, 6.58 per 1,000 peopleGuatemala: 44.6% of children under 5, 1.28 per 1,000 peopleGuyana: 7.1% of children under 5, 1.39 per 1,000 peopleHonduras: 17.9% of children under 5, 0.489 per 1,000 peopleHaiti: 21.6% of children under 5, 0.292 per 1,000 peopleIndonesia: 22.6% of children under 5, 0.524 per 1,000 peopleIndia: 32.9% of children under 5, 0.723 per 1,000 peopleIreland: 2.2% of children under 5, 3.88 per 1,000 peopleIran, Islamic Rep.: 4.8% of children under 5, 1.81 per 1,000 peopleIraq: 9.4% of children under 5, 1.02 per 1,000 peopleJamaica: 6.9% of children under 5, 0.46 per 1,000 peopleJordan: 7.7% of children under 5, 2.85 per 1,000 peopleJapan: 5.2% of children under 5, 2.65 per 1,000 peopleKazakhstan: 4.4% of children under 5, 3.75 per 1,000 peopleKenya: 17.9% of children under 5, 0.289 per 1,000 peopleKyrgyz Republic: 11% of children under 5, 1.57 per 1,000 peopleCambodia: 22% of children under 5, 0.211 per 1,000 peopleKiribati: 14.7% of children under 5, 0.193 per 1,000 peopleKorea, Rep.: 1.8% of children under 5, 2.61 per 1,000 peopleKuwait: 4.5% of children under 5, 2.27 per 1,000 peopleLao PDR: 29.9% of children under 5, 0.331 per 1,000 peopleLebanon: 10.1% of children under 5, 2.68 per 1,000 peopleLiberia: 26.9% of children under 5, 0.178 per 1,000 peopleLibya: 9.2% of children under 5, 2.04 per 1,000 peopleSt. Lucia: 2.8% of children under 5, 4.23 per 1,000 peopleSri Lanka: 10.1% of children under 5, 1.14 per 1,000 peopleLesotho: 35% of children under 5, 0.235 per 1,000 peopleLithuania: 1.6% of children under 5, 4.47 per 1,000 peopleLatvia: 1.7% of children under 5, 3.4 per 1,000 peopleMorocco: 13.7% of children under 5, 0.74 per 1,000 peopleMoldova: 4.2% of children under 5, 4.02 per 1,000 peopleMadagascar: 38.4% of children under 5, 0.172 per 1,000 peopleMaldives: 14.2% of children under 5, 2.23 per 1,000 peopleMexico: 13.1% of children under 5, 2.59 per 1,000 peopleMarshall Islands: 30% of children under 5, 0.467 per 1,000 peopleNorth Macedonia: 3.8% of children under 5, 2.94 per 1,000 peopleMali: 23.2% of children under 5, 0.188 per 1,000 peopleMalta: 3.5% of children under 5, 4.51 per 1,000 peopleMyanmar: 24.5% of children under 5, 0.757 per 1,000 peopleMontenegro: 8% of children under 5, 2.78 per 1,000 peopleMongolia: 7.1% of children under 5, 4.13 per 1,000 peopleMozambique: 37% of children under 5, 0.175 per 1,000 peopleMauritania: 21.5% of children under 5, 0.261 per 1,000 peopleMauritius: 7.8% of children under 5, 1.44 per 1,000 peopleMalawi: 33.2% of children under 5, 0.054 per 1,000 peopleMalaysia: 24.3% of children under 5, 2.34 per 1,000 peopleNamibia: 16.4% of children under 5, 0.553 per 1,000 peopleNiger: 48.3% of children under 5, 0.038 per 1,000 peopleNigeria: 33.8% of children under 5, 0.38 per 1,000 peopleNetherlands: 1.6% of children under 5, 3.88 per 1,000 peopleNepal: 26% of children under 5, 1.01 per 1,000 peopleNaoero: 16% of children under 5, 1.27 per 1,000 peopleOman: 12.9% of children under 5, 1.99 per 1,000 peoplePakistan: 33.6% of children under 5, 1.16 per 1,000 peoplePanama: 14% of children under 5, 1.63 per 1,000 peoplePeru: 10.6% of children under 5, 1.69 per 1,000 peoplePhilippines: 27.7% of children under 5, 0.792 per 1,000 peoplePapua New Guinea: 47.6% of children under 5, 0.061 per 1,000 peoplePoland: 1% of children under 5, 4.03 per 1,000 peoplePortugal: 3.2% of children under 5, 5.85 per 1,000 peopleParaguay: 3.2% of children under 5, 3.89 per 1,000 peopleWest Bank and Gaza: 8% of children under 5, 2.17 per 1,000 peopleQatar: 5.4% of children under 5, 3.02 per 1,000 peopleRomania: 7% of children under 5, 3.63 per 1,000 peopleRwanda: 29.8% of children under 5, 0.09 per 1,000 peopleSaudi Arabia: 11.1% of children under 5, 3.41 per 1,000 peopleSudan: 35.4% of children under 5, 0.25 per 1,000 peopleSenegal: 17.2% of children under 5, 0.109 per 1,000 peopleSingapore: 2.8% of children under 5, 2.83 per 1,000 peopleSolomon Islands: 29.8% of children under 5, 0.238 per 1,000 peopleSierra Leone: 25.2% of children under 5, 0.134 per 1,000 peopleEl Salvador: 9.4% of children under 5, 1.62 per 1,000 peopleSomalia, Fed. Rep.: 23.9% of children under 5, 0.048 per 1,000 peopleSerbia: 4.6% of children under 5, 3.1 per 1,000 peopleSao Tome and Principe: 10% of children under 5, 0.464 per 1,000 peopleSuriname: 8% of children under 5, 1.35 per 1,000 peopleEswatini: 18.9% of children under 5, 0.557 per 1,000 peopleSeychelles: 6.2% of children under 5, 6.6 per 1,000 peopleSyrian Arab Republic: 23.5% of children under 5, 1.52 per 1,000 peopleChad: 31.5% of children under 5, 0.085 per 1,000 peopleTogo: 23% of children under 5, 0.08 per 1,000 peopleThailand: 12.3% of children under 5, 0.541 per 1,000 peopleTajikistan: 13.1% of children under 5, 1.87 per 1,000 peopleTurkmenistan: 6.5% of children under 5, 1.93 per 1,000 peopleTimor-Leste: 45.4% of children under 5, 0.752 per 1,000 peopleTonga: 1.6% of children under 5, 1.01 per 1,000 peopleTrinidad and Tobago: 7.8% of children under 5, 4.16 per 1,000 peopleTunisia: 8.9% of children under 5, 1.31 per 1,000 peopleTurkiye: 5.5% of children under 5, 2.24 per 1,000 peopleTuvalu: 5.3% of children under 5, 1.35 per 1,000 peopleTanzania: 29.9% of children under 5, 0.134 per 1,000 peopleUganda: 23.5% of children under 5, 0.191 per 1,000 peopleUkraine: 11.7% of children under 5, 3.53 per 1,000 peopleUruguay: 6.5% of children under 5, 4.67 per 1,000 peopleUnited States: 4.2% of children under 5, 3.68 per 1,000 peopleUzbekistan: 6.7% of children under 5, 2.81 per 1,000 peopleViet Nam: 19.2% of children under 5, 1.11 per 1,000 peopleVanuatu: 31% of children under 5, 0.164 per 1,000 peopleSamoa: 8.4% of children under 5, 0.561 per 1,000 peopleSouth Africa: 24.4% of children under 5, 0.794 per 1,000 peopleZambia: 32.3% of children under 5, 0.324 per 1,000 peopleZimbabwe: 23.7% of children under 5, 0.136 per 1,000 peopleBDIBHRGRCGTMJAMNERPNGPRTSYCTON

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.6941.5e-23155
By rank (Spearman), not adjusted-0.8163.6e-38155
Standard (Pearson), adjusted for national income-0.2830.000155
By rank (Spearman), adjusted for national income-0.4332.0e-8155

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: +0.411 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.303 (without BDI) to -0.268 (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: BDI (-0.021).

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 & Pacific26-0.31
Europe & Central Asia32-0.40
Latin America & Caribbean24-0.26
Middle East, North Africa, Afghanistan & Pakistan20-0.23
Sub-Saharan Africa46-0.07

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 third52-0.23
Middle third51-0.40
Richest third52-0.44

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
Christians86-0.18
Muslims48-0.35

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.

nr
France25-0.26
Never a European colony21-0.42
Spain18-0.31
United Kingdom52-0.24

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 = -0.303 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 24years. 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 also shows up within countries over time (r = +0.322). It holds even when looking only at changes from one year to the next (r = +0.084). This is the strongest kind of evidence available here: it holds when each country is compared only with itself, and it is not just a product of shared trends.

Across countries (adjusted)-0.283for comparison
Within countries-0.199each country vs itself
…and vs the same year elsewhere+0.322q = 1.0e-5 · 152 countries
Year-on-year changes+0.084q = 0.000
The direction flips. Comparing each country only with itself gives -0.20. Also taking out what happened to the whole world each year gives +0.32. 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 this indicator's variation is between countries, not within them, so the within-country estimate rests on a small part of the data.
  • The association is much weaker in year-on-year changes than in levels, which points to shared country-specific trends.

2,279 country-years (one country in one year), 152 countries, 2000–2023, about 15 years each on average. Share of the variation that happens within countries over time: 7% for Child stunting, 8% for Physicians. 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 Physicians trails Child stunting →lag -10: r = 0.394 (n = 2,128)lag -9: r = 0.410 (n = 2,105)lag -8: r = 0.400 (n = 2,140)lag -7: r = 0.385 (n = 2,180)lag -6: r = 0.361 (n = 2,235)lag -5: r = 0.344 (n = 2,290)lag -4: r = 0.352 (n = 2,309)lag -3: r = 0.345 (n = 2,336)lag -2: r = 0.328 (n = 2,360)lag -1: r = 0.324 (n = 2,343)lag +0: r = 0.322 (n = 2,279)lag +1: r = 0.314 (n = 2,186)lag +2: r = 0.293 (n = 2,112)lag +3: r = 0.275 (n = 2,035)lag +4: r = 0.261 (n = 1,955)lag +5: r = 0.247 (n = 1,831)lag +6: r = 0.232 (n = 1,738)lag +7: r = 0.212 (n = 1,657)lag +8: r = 0.187 (n = 1,565)lag +9: r = 0.187 (n = 1,439)lag +10: r = 0.163 (n = 1,331)

Same year (lag 0): +0.322. 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 (+0.41 at lag -9) is higher than the same-year one by 0.09. That gap is not a finding. It is the largest of 21 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
per 1,000 people		Years
Burundi BDI55.3%0.0782024, 2022
Niger NER48.3%0.0382024, 2023
Angola AGO47.7%0.2442024, 2022
Papua New Guinea PNG47.6%0.0612024, 2023
Timor-Leste TLS45.4%0.7522024, 2020
Guatemala GTM44.6%1.282024, 2020
Congo, Dem. Rep. COD44.1%0.2082024, 2022
Afghanistan AFG42%0.3172024, 2023
Central African Republic CAF38.9%0.0742024, 2023
Madagascar MDG38.4%0.1722024, 2022
Mozambique MOZ37%0.1752024, 2022
Ethiopia ETH35.5%0.1432024, 2023
Sudan SDN35.4%0.252024, 2017
Lesotho LSO35%0.2352024, 2022
Nigeria NGA33.8%0.382024, 2023

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.

Physicians

Physicians (per 1,000 people)

World Health Organization · CC BY 4.0 · updated quarterly

Reported irregularly, so the latest value in the time window used is from a different year for different countries. Hospital beds, already on the site, have no "better" direction, since more beds is not plainly better. More doctors is closer to plainly better, so a direction is set on that basis.

How this was computed

Data used: most recent value in 2010-2025; values come from 2012–2024. 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 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 Physicians

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

More links with Child stunting or Physicians