placestats

Food insecurity vs. Under-5 mortality

Fades after adjusting for income

Across 155 countries, Food insecurity and Under-5 mortality rise and fall together at r = +0.81 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.41, which could easily be chance (q = 0.11, 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 under-5 mortality, 5.4 to 36.9 per 1,000 live births, food insecurity is worse by 23.7% of population at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 11.4% of population.

Link before adjusting (r)+0.809p = 3.6e-37 · 155 countries
After adjusting for national income+0.409p = 1.4e-7 · likely range [+0.27, +0.53]
p, allowing for regions0.001standard error 0.069 · 7 regions
Check for luck (q)0.114across 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.

Food insecurity · % of populationlink with income -0.83 · proxy
Under-5 mortality · per 1,000 live birthslink with income -0.86 · 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

Food insecurity · % of population →Under-5 mortality · per 1,000 live births →1.1%89.8%2116Afghanistan: 80.8% of population, 53 per 1,000 live birthsAngola: 78.5% of population, 49 per 1,000 live birthsAlbania: 33% of population, 9.2 per 1,000 live birthsUnited Arab Emirates: 3.6% of population, 4.8 per 1,000 live birthsArgentina: 33.8% of population, 9.5 per 1,000 live birthsArmenia: 7.8% of population, 9.6 per 1,000 live birthsAntigua and Barbuda: 13.5% of population, 9.1 per 1,000 live birthsAustralia: 13.8% of population, 3.6 per 1,000 live birthsAustria: 4.7% of population, 3.3 per 1,000 live birthsAzerbaijan: 14% of population, 17.9 per 1,000 live birthsBurundi: 70.8% of population, 47.1 per 1,000 live birthsBelgium: 8.1% of population, 3.7 per 1,000 live birthsBenin: 65.6% of population, 74.7 per 1,000 live birthsBurkina Faso: 41.4% of population, 74.9 per 1,000 live birthsBulgaria: 11.6% of population, 5.7 per 1,000 live birthsBahamas, The: 17.2% of population, 12.4 per 1,000 live birthsBosnia and Herzegovina: 9.9% of population, 6.9 per 1,000 live birthsBelarus: 1.1% of population, 2.3 per 1,000 live birthsBelize: 45.5% of population, 12.7 per 1,000 live birthsBrazil: 13.5% of population, 14.2 per 1,000 live birthsBarbados: 31.1% of population, 9.8 per 1,000 live birthsBotswana: 53.9% of population, 33.3 per 1,000 live birthsCentral African Republic: 88.1% of population, 89.7 per 1,000 live birthsCanada: 10.2% of population, 5.4 per 1,000 live birthsSwitzerland: 2% of population, 3.9 per 1,000 live birthsChile: 19.2% of population, 6.8 per 1,000 live birthsCote d'Ivoire: 38.4% of population, 64.5 per 1,000 live birthsCameroon: 61.2% of population, 64.8 per 1,000 live birthsCongo, Dem. Rep.: 81.5% of population, 89.7 per 1,000 live birthsColombia: 27.8% of population, 11.5 per 1,000 live birthsComoros: 79.7% of population, 39 per 1,000 live birthsCabo Verde: 32.1% of population, 11.1 per 1,000 live birthsCosta Rica: 15.4% of population, 10.4 per 1,000 live birthsCyprus: 1.4% of population, 5 per 1,000 live birthsCzechia: 10% of population, 2.6 per 1,000 live birthsGermany: 4.1% of population, 3.7 per 1,000 live birthsDjibouti: 49.2% of population, 48.9 per 1,000 live birthsDominica: 34.4% of population, 35.7 per 1,000 live birthsDenmark: 6.9% of population, 4 per 1,000 live birthsDominican Republic: 43.8% of population, 30.6 per 1,000 live birthsAlgeria: 17.6% of population, 21.6 per 1,000 live birthsEcuador: 33.3% of population, 12.9 per 1,000 live birthsEgypt, Arab Rep.: 30.8% of population, 22.4 per 1,000 live birthsSpain: 6.5% of population, 3.2 per 1,000 live birthsEstonia: 10.8% of population, 2 per 1,000 live birthsEthiopia: 61.4% of population, 44.5 per 1,000 live birthsFinland: 13.4% of population, 2.4 per 1,000 live birthsFiji: 29.2% of population, 29.1 per 1,000 live birthsFrance: 8.4% of population, 4.3 per 1,000 live birthsUnited Kingdom: 6.9% of population, 4.7 per 1,000 live birthsGeorgia: 26.6% of population, 8.6 per 1,000 live birthsGhana: 44.5% of population, 35.9 per 1,000 live birthsGambia, The: 54.8% of population, 42.4 per 1,000 live birthsGuinea-Bissau: 62.5% of population, 67.3 per 1,000 live birthsGreece: 6.6% of population, 3.8 per 1,000 live birthsGrenada: 17.3% of population, 18 per 1,000 live birthsGuatemala: 48.8% of population, 20.5 per 1,000 live birthsGuyana: 25.5% of population, 25.2 per 1,000 live birthsHonduras: 41.3% of population, 15 per 1,000 live birthsCroatia: 6% of population, 5.6 per 1,000 live birthsHaiti: 83.2% of population, 52.8 per 1,000 live birthsHungary: 15.6% of population, 3.7 per 1,000 live birthsIndonesia: 4.5% of population, 17.7 per 1,000 live birthsIreland: 4.8% of population, 3.9 per 1,000 live birthsIran, Islamic Rep.: 38.8% of population, 11.3 per 1,000 live birthsIceland: 7.8% of population, 2.8 per 1,000 live birthsIsrael: 9.2% of population, 3.3 per 1,000 live birthsItaly: 1.7% of population, 2.7 per 1,000 live birthsJamaica: 56.4% of population, 17.8 per 1,000 live birthsJapan: 5.8% of population, 2.4 per 1,000 live birthsKazakhstan: 2% of population, 9.4 per 1,000 live birthsKenya: 73.9% of population, 38.8 per 1,000 live birthsKyrgyz Republic: 7% of population, 16.8 per 1,000 live birthsCambodia: 40% of population, 18.4 per 1,000 live birthsKiribati: 42.9% of population, 53.1 per 1,000 live birthsSt. Kitts and Nevis: 21.1% of population, 15.9 per 1,000 live birthsKorea, Rep.: 5.4% of population, 2.8 per 1,000 live birthsKuwait: 8.4% of population, 8.1 per 1,000 live birthsLao PDR: 35.6% of population, 29.4 per 1,000 live birthsLebanon: 42.4% of population, 17.6 per 1,000 live birthsLiberia: 80.8% of population, 86.4 per 1,000 live birthsLibya: 35.1% of population, 9.8 per 1,000 live birthsSt. Lucia: 22.2% of population, 17.2 per 1,000 live birthsSri Lanka: 11.2% of population, 5.9 per 1,000 live birthsLesotho: 59.9% of population, 60 per 1,000 live birthsLithuania: 6.5% of population, 3.4 per 1,000 live birthsLuxembourg: 2.6% of population, 2.2 per 1,000 live birthsLatvia: 11.2% of population, 2.5 per 1,000 live birthsMoldova: 25.1% of population, 16.5 per 1,000 live birthsMadagascar: 72.6% of population, 62.4 per 1,000 live birthsMaldives: 13.4% of population, 5.4 per 1,000 live birthsMexico: 19.3% of population, 13.1 per 1,000 live birthsNorth Macedonia: 15.2% of population, 2.8 per 1,000 live birthsMali: 20.6% of population, 73 per 1,000 live birthsMalta: 9.2% of population, 5.3 per 1,000 live birthsMyanmar: 32.7% of population, 36.9 per 1,000 live birthsMontenegro: 10.4% of population, 2.4 per 1,000 live birthsMongolia: 4.8% of population, 13.4 per 1,000 live birthsMauritania: 66.3% of population, 36.9 per 1,000 live birthsMauritius: 31.1% of population, 15.4 per 1,000 live birthsMalawi: 81.7% of population, 48.8 per 1,000 live birthsMalaysia: 16.7% of population, 8.3 per 1,000 live birthsNamibia: 55.9% of population, 39.5 per 1,000 live birthsNiger: 50.9% of population, 111 per 1,000 live birthsNigeria: 74.8% of population, 116 per 1,000 live birthsNetherlands: 7.5% of population, 3.9 per 1,000 live birthsNorway: 7.8% of population, 2.5 per 1,000 live birthsNepal: 36.6% of population, 25.1 per 1,000 live birthsNaoero: 29.9% of population, 8.3 per 1,000 live birthsNew Zealand: 17.3% of population, 4.7 per 1,000 live birthsPakistan: 42.1% of population, 56 per 1,000 live birthsPeru: 41% of population, 12.9 per 1,000 live birthsPhilippines: 32.9% of population, 26.5 per 1,000 live birthsPalau: 28.1% of population, 21.4 per 1,000 live birthsPapua New Guinea: 57.3% of population, 39.4 per 1,000 live birthsPoland: 3.4% of population, 4.2 per 1,000 live birthsPortugal: 11.9% of population, 3.2 per 1,000 live birthsParaguay: 26.2% of population, 16.3 per 1,000 live birthsWest Bank and Gaza: 27% of population, 37.9 per 1,000 live birthsRomania: 18.6% of population, 7.3 per 1,000 live birthsRussian Federation: 2.8% of population, 5.2 per 1,000 live birthsSenegal: 29.1% of population, 36.5 per 1,000 live birthsSingapore: 9.5% of population, 2.7 per 1,000 live birthsSierra Leone: 89.8% of population, 90.5 per 1,000 live birthsEl Salvador: 45.5% of population, 10 per 1,000 live birthsSomalia, Fed. Rep.: 79.5% of population, 101 per 1,000 live birthsSerbia: 9.5% of population, 5.4 per 1,000 live birthsSao Tome and Principe: 54.6% of population, 13.6 per 1,000 live birthsSuriname: 35.8% of population, 15.8 per 1,000 live birthsSlovak Republic: 7.5% of population, 6.3 per 1,000 live birthsSlovenia: 8.2% of population, 2.3 per 1,000 live birthsSweden: 6.9% of population, 2.4 per 1,000 live birthsEswatini: 59% of population, 45.1 per 1,000 live birthsSeychelles: 14.3% of population, 14 per 1,000 live birthsChad: 66.3% of population, 97.3 per 1,000 live birthsTogo: 58.5% of population, 56.1 per 1,000 live birthsThailand: 5.4% of population, 9 per 1,000 live birthsTajikistan: 25.1% of population, 28.1 per 1,000 live birthsTimor-Leste: 53.7% of population, 47.6 per 1,000 live birthsTonga: 14.8% of population, 9.5 per 1,000 live birthsTrinidad and Tobago: 27.6% of population, 18.8 per 1,000 live birthsTunisia: 25.4% of population, 12.1 per 1,000 live birthsTanzania: 58% of population, 37 per 1,000 live birthsUganda: 54.6% of population, 48.7 per 1,000 live birthsUkraine: 32.5% of population, 7.9 per 1,000 live birthsUruguay: 16.2% of population, 7.4 per 1,000 live birthsUnited States: 10.3% of population, 6.5 per 1,000 live birthsUzbekistan: 24.4% of population, 13.4 per 1,000 live birthsSt. Vincent and the Grenadines: 33.3% of population, 11.3 per 1,000 live birthsViet Nam: 10.7% of population, 17.3 per 1,000 live birthsVanuatu: 23.3% of population, 17.1 per 1,000 live birthsSamoa: 18.6% of population, 14.9 per 1,000 live birthsSouth Africa: 20.7% of population, 35.1 per 1,000 live birthsZambia: 45.3% of population, 48.4 per 1,000 live birthsZimbabwe: 68.8% of population, 64.7 per 1,000 live birthsBLRCOMITAJAMLUXMLINERNGASLESOMSTP

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.8093.6e-37155
By rank (Spearman), not adjusted+0.8402.1e-42155
Standard (Pearson), adjusted for national income+0.4091.4e-7155
By rank (Spearman), adjusted for national income+0.4071.6e-7155

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: +0.400 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.363 (without NGA) to +0.454 (without NER). 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: NGA (-0.047).

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 & Pacific23+0.60
Europe & Central Asia46+0.06
Latin America & Caribbean28+0.51
Middle East, North Africa, Afghanistan & Pakistan14-0.01
Sub-Saharan Africa39+0.23

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+0.41
Middle third51+0.35
Richest third52+0.65

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
Christians98+0.53
Muslims35+0.34

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
France21-0.25
Never a European colony16+0.52
Spain14+0.40
United Kingdom52+0.61

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 = +0.356 after dropping 8 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 9years. 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 = -0.059, 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 food insecurity moved did not tend to see their under-5 mortality move with it.

Across countries (adjusted)+0.409for comparison
Within countries-0.144each country vs itself
…and vs the same year elsewhere-0.059q = 0.532 · 126 countries
Year-on-year changes-0.025q = 0.689
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.

1,051 country-years (one country in one year), 126 countries, 2015–2023, about 8 years each on average. Share of the variation that happens within countries over time: 4% for Food insecurity, 3% for Under-5 mortality. 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

0.20−0.2-100+5years Under-5 mortality trails Food insecurity →lag -10: r = -0.152 (n = 1,051)lag -9: r = -0.123 (n = 1,051)lag -8: r = -0.096 (n = 1,051)lag -7: r = -0.074 (n = 1,051)lag -6: r = -0.061 (n = 1,051)lag -5: r = -0.064 (n = 1,051)lag -4: r = -0.062 (n = 1,051)lag -3: r = -0.058 (n = 1,051)lag -2: r = -0.047 (n = 1,051)lag -1: r = -0.046 (n = 1,051)lag +0: r = -0.059 (n = 1,051)lag +1: r = -0.129 (n = 1,051)lag +2: r = -0.131 (n = 900)lag +3: r = -0.132 (n = 749)lag +4: r = -0.145 (n = 586)lag +5: r = -0.133 (n = 480)

Same year (lag 0): -0.059. 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 population

per 1,000 live births
Years
Sierra Leone SLE89.8%90.52023, 2024
Central African Republic CAF88.1%89.72022, 2024
Haiti HTI83.2%52.82023, 2024
Malawi MWI81.7%48.82023, 2024
Congo, Dem. Rep. COD81.5%89.72023, 2024
Liberia LBR80.8%86.42023, 2024
Afghanistan AFG80.8%532023, 2024
Comoros COM79.7%392023, 2024
Somalia, Fed. Rep. SOM79.5%1012021, 2024
Angola AGO78.5%492021, 2024
Nigeria NGA74.8%1162023, 2024
Kenya KEN73.9%38.82023, 2024
Madagascar MDG72.6%62.42023, 2024
Burundi BDI70.8%47.12023, 2024
Zimbabwe ZWE68.8%64.72023, 2024

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

Sources

Food insecurity

Prevalence of moderate or severe food insecurity in the population (%)

Food and Agriculture Organization, Food Insecurity Experience Scale · CC BY 4.0 · updated quarterly

Asked of people, in a survey about running out of food, and reported as a three-year average from 2015. It is the one measure of hunger here that comes from what people say they went through, rather than from a model.

Under-5 mortality

Mortality rate, under-5 (per 1,000 live births)

World Bank · CC BY 4.0 · updated quarterly

How this was computed

Data used: most recent value in 2010-2025; values come from 2017–2024. 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 Food insecurity and Under-5 mortality

This page shows that two measures go together. It does not show that Food insecurity changes Under-5 mortality, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Food insecurity or Under-5 mortality