placestats

Food insecurity vs. Hospital beds

Fades after adjusting for income

Across 145 countries, Food insecurity and Hospital beds 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 -0.20, 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. Caution: direction is not consistent across regions.

Comparing countries across the middle half of hospital beds, 1.3 to 4.04 per 1,000 people, food insecurity is better by 14.4% of population at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 3.47% of population.

Link before adjusting (r)-0.533p = 5.4e-12 · 145 countries
After adjusting for national income-0.201p = 0.016 · likely range [-0.35, -0.04]
p, allowing for regions0.202standard error 0.140 · 7 regions
Check for luck (q)0.109across 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
Hospital beds · per 1,000 peoplelink with income +0.63 · 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

Food insecurity · % of population →Hospital beds · per 1,000 people →1.1%88.1%0.1512.8Afghanistan: 80.8% of population, 0.35 per 1,000 peopleAngola: 78.5% of population, 0.75 per 1,000 peopleAlbania: 33% of population, 2.9 per 1,000 peopleUnited Arab Emirates: 3.6% of population, 1.87 per 1,000 peopleArgentina: 33.8% of population, 3.36 per 1,000 peopleArmenia: 7.8% of population, 4.24 per 1,000 peopleAntigua and Barbuda: 13.5% of population, 3.42 per 1,000 peopleAustralia: 13.8% of population, 3.82 per 1,000 peopleAustria: 4.7% of population, 6.7 per 1,000 peopleAzerbaijan: 14% of population, 3.68 per 1,000 peopleBurundi: 70.8% of population, 0.69 per 1,000 peopleBelgium: 8.1% of population, 5.42 per 1,000 peopleBenin: 65.6% of population, 0.43 per 1,000 peopleBurkina Faso: 41.4% of population, 0.2 per 1,000 peopleBulgaria: 11.6% of population, 8.2 per 1,000 peopleBahamas, The: 17.2% of population, 2.17 per 1,000 peopleBosnia and Herzegovina: 9.9% of population, 2.35 per 1,000 peopleBelarus: 1.1% of population, 9.77 per 1,000 peopleBelize: 45.5% of population, 1 per 1,000 peopleBrazil: 13.5% of population, 2.52 per 1,000 peopleBarbados: 31.1% of population, 6.4 per 1,000 peopleBotswana: 53.9% of population, 2.36 per 1,000 peopleCentral African Republic: 88.1% of population, 1 per 1,000 peopleCanada: 10.2% of population, 2.54 per 1,000 peopleSwitzerland: 2% of population, 4.38 per 1,000 peopleChile: 19.2% of population, 1.94 per 1,000 peopleCameroon: 61.2% of population, 2.65 per 1,000 peopleColombia: 27.8% of population, 1.7 per 1,000 peopleComoros: 79.7% of population, 2.16 per 1,000 peopleCabo Verde: 32.1% of population, 2.21 per 1,000 peopleCosta Rica: 15.4% of population, 1.14 per 1,000 peopleCyprus: 1.4% of population, 2.15 per 1,000 peopleCzechia: 10% of population, 6.54 per 1,000 peopleGermany: 4.1% of population, 7.55 per 1,000 peopleDjibouti: 49.2% of population, 1.4 per 1,000 peopleDominica: 34.4% of population, 3.97 per 1,000 peopleDenmark: 6.9% of population, 2.43 per 1,000 peopleDominican Republic: 43.8% of population, 0.75 per 1,000 peopleAlgeria: 17.6% of population, 1.61 per 1,000 peopleEcuador: 33.3% of population, 1.32 per 1,000 peopleEgypt, Arab Rep.: 30.8% of population, 1.06 per 1,000 peopleSpain: 6.5% of population, 2.91 per 1,000 peopleEstonia: 10.8% of population, 4.13 per 1,000 peopleEthiopia: 61.4% of population, 0.33 per 1,000 peopleFinland: 13.4% of population, 2.61 per 1,000 peopleFiji: 29.2% of population, 1.89 per 1,000 peopleFrance: 8.4% of population, 5.65 per 1,000 peopleUnited Kingdom: 6.9% of population, 2.42 per 1,000 peopleGeorgia: 26.6% of population, 4.04 per 1,000 peopleGhana: 44.5% of population, 0.69 per 1,000 peopleGambia, The: 54.8% of population, 1.11 per 1,000 peopleGreece: 6.6% of population, 4.27 per 1,000 peopleGrenada: 17.3% of population, 3.01 per 1,000 peopleGuatemala: 48.8% of population, 0.45 per 1,000 peopleGuyana: 25.5% of population, 3.24 per 1,000 peopleHonduras: 41.3% of population, 0.53 per 1,000 peopleCroatia: 6% of population, 5.6 per 1,000 peopleHaiti: 83.2% of population, 4.9 per 1,000 peopleHungary: 15.6% of population, 6.63 per 1,000 peopleIndonesia: 4.5% of population, 1.37 per 1,000 peopleIreland: 4.8% of population, 2.96 per 1,000 peopleIran, Islamic Rep.: 38.8% of population, 1.85 per 1,000 peopleIceland: 7.8% of population, 2.83 per 1,000 peopleIsrael: 9.2% of population, 3.14 per 1,000 peopleItaly: 1.7% of population, 3.06 per 1,000 peopleJamaica: 56.4% of population, 1.65 per 1,000 peopleJapan: 5.8% of population, 12.6 per 1,000 peopleKazakhstan: 2% of population, 6.54 per 1,000 peopleKenya: 73.9% of population, 1.33 per 1,000 peopleKyrgyz Republic: 7% of population, 3.73 per 1,000 peopleCambodia: 40% of population, 0.73 per 1,000 peopleKiribati: 42.9% of population, 1.86 per 1,000 peopleSt. Kitts and Nevis: 21.1% of population, 3.98 per 1,000 peopleKorea, Rep.: 5.4% of population, 12.8 per 1,000 peopleKuwait: 8.4% of population, 2.33 per 1,000 peopleLao PDR: 35.6% of population, 1.71 per 1,000 peopleLebanon: 42.4% of population, 2.73 per 1,000 peopleLiberia: 80.8% of population, 1.59 per 1,000 peopleLibya: 35.1% of population, 3.5 per 1,000 peopleSt. Lucia: 22.2% of population, 1.09 per 1,000 peopleSri Lanka: 11.2% of population, 3.93 per 1,000 peopleLithuania: 6.5% of population, 5.71 per 1,000 peopleLuxembourg: 2.6% of population, 3.95 per 1,000 peopleLatvia: 11.2% of population, 4.95 per 1,000 peopleMoldova: 25.1% of population, 5.54 per 1,000 peopleMadagascar: 72.6% of population, 0.32 per 1,000 peopleMaldives: 13.4% of population, 4.56 per 1,000 peopleMexico: 19.3% of population, 1.01 per 1,000 peopleNorth Macedonia: 15.2% of population, 4.74 per 1,000 peopleMali: 20.6% of population, 0.25 per 1,000 peopleMalta: 9.2% of population, 4.09 per 1,000 peopleMyanmar: 32.7% of population, 1.07 per 1,000 peopleMontenegro: 10.4% of population, 3.82 per 1,000 peopleMongolia: 4.8% of population, 8.58 per 1,000 peopleMauritius: 31.1% of population, 3.8 per 1,000 peopleMalawi: 81.7% of population, 1.3 per 1,000 peopleMalaysia: 16.7% of population, 1.96 per 1,000 peopleNiger: 50.9% of population, 0.28 per 1,000 peopleNetherlands: 7.5% of population, 2.42 per 1,000 peopleNorway: 7.8% of population, 3.3 per 1,000 peopleNepal: 36.6% of population, 0.54 per 1,000 peopleNaoero: 29.9% of population, 4.97 per 1,000 peopleNew Zealand: 17.3% of population, 2.51 per 1,000 peoplePakistan: 42.1% of population, 0.63 per 1,000 peoplePeru: 41% of population, 1.56 per 1,000 peoplePhilippines: 32.9% of population, 0.97 per 1,000 peoplePalau: 28.1% of population, 4.34 per 1,000 peoplePapua New Guinea: 57.3% of population, 0.62 per 1,000 peoplePoland: 3.4% of population, 6.04 per 1,000 peoplePortugal: 11.9% of population, 3.48 per 1,000 peopleParaguay: 26.2% of population, 1.04 per 1,000 peopleWest Bank and Gaza: 27% of population, 1.3 per 1,000 peopleRomania: 18.6% of population, 7.23 per 1,000 peopleRussian Federation: 2.8% of population, 6.81 per 1,000 peopleSenegal: 29.1% of population, 0.71 per 1,000 peopleSingapore: 9.5% of population, 2.81 per 1,000 peopleEl Salvador: 45.5% of population, 1.21 per 1,000 peopleSomalia, Fed. Rep.: 79.5% of population, 0.87 per 1,000 peopleSerbia: 9.5% of population, 5.78 per 1,000 peopleSao Tome and Principe: 54.6% of population, 2.91 per 1,000 peopleSuriname: 35.8% of population, 2.87 per 1,000 peopleSlovak Republic: 7.5% of population, 5.57 per 1,000 peopleSlovenia: 8.2% of population, 4.11 per 1,000 peopleSweden: 6.9% of population, 1.9 per 1,000 peopleEswatini: 59% of population, 2.02 per 1,000 peopleSeychelles: 14.3% of population, 2.63 per 1,000 peopleChad: 66.3% of population, 0.15 per 1,000 peopleTogo: 58.5% of population, 0.33 per 1,000 peopleThailand: 5.4% of population, 2.39 per 1,000 peopleTajikistan: 25.1% of population, 4.04 per 1,000 peopleTimor-Leste: 53.7% of population, 0.38 per 1,000 peopleTonga: 14.8% of population, 2.48 per 1,000 peopleTrinidad and Tobago: 27.6% of population, 2.37 per 1,000 peopleTunisia: 25.4% of population, 1.82 per 1,000 peopleTanzania: 58% of population, 0.84 per 1,000 peopleUganda: 54.6% of population, 0.5 per 1,000 peopleUkraine: 32.5% of population, 6.14 per 1,000 peopleUruguay: 16.2% of population, 2.44 per 1,000 peopleUnited States: 10.3% of population, 2.68 per 1,000 peopleUzbekistan: 24.4% of population, 4.89 per 1,000 peopleSt. Vincent and the Grenadines: 33.3% of population, 3.21 per 1,000 peopleViet Nam: 10.7% of population, 2.52 per 1,000 peopleSouth Africa: 20.7% of population, 2.25 per 1,000 peopleZambia: 45.3% of population, 2 per 1,000 peopleZimbabwe: 68.8% of population, 1.95 per 1,000 peopleAFGAGOAREBLRCAFCYPHTIIDNJPNKOR

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5335.4e-12145
By rank (Spearman), not adjusted-0.6386.2e-18145
Standard (Pearson), adjusted for national income-0.2010.016145
By rank (Spearman), adjusted for national income-0.2670.001145

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 145 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: +0.332 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.235 (without HTI) to -0.171 (without MNG). 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: HTI (-0.034).

Fragile: this link may not hold up.
  • 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 & Pacific21-0.30
Europe & Central Asia46-0.12
Latin America & Caribbean28+0.14
Middle East, North Africa, Afghanistan & Pakistan14+0.11
Sub-Saharan Africa31+0.25

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 third49-0.04
Middle third48-0.31
Richest third48-0.30

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
Christians93-0.26
Muslims30-0.13

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
France19+0.57
Never a European colony16-0.03
Spain14+0.03
United Kingdom47-0.13

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 = -0.143 after dropping 5 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.

Loading…

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 = +0.068, 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 hospital beds move with it.

Across countries (adjusted)-0.201for comparison
Within countries-0.004each country vs itself
…and vs the same year elsewhere+0.068q = 0.627 · 89 countries
Year-on-year changes+0.009q = 0.944
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.

694 country-years (one country in one year), 89 countries, 2015–2023, about 8 years each on average. Share of the variation that happens within countries over time: 1% for Food insecurity, 3% for Hospital beds. 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

0.30−0.3-100+3years Hospital beds trails Food insecurity →lag -10: r = 0.047 (n = 722)lag -9: r = 0.017 (n = 755)lag -8: r = 0.003 (n = 788)lag -7: r = -0.010 (n = 804)lag -6: r = -0.021 (n = 817)lag -5: r = 0.001 (n = 816)lag -4: r = 0.013 (n = 810)lag -3: r = -0.001 (n = 798)lag -2: r = -0.018 (n = 775)lag -1: r = -0.001 (n = 759)lag +0: r = 0.068 (n = 694)lag +1: r = 0.129 (n = 571)lag +2: r = 0.156 (n = 460)lag +3: r = 0.226 (n = 365)

Same year (lag 0): +0.068. 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 +3), 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 people		Years
Central African Republic CAF88.1%12022, 2011
Haiti HTI83.2%4.92023
Malawi MWI81.7%1.32023, 2011
Liberia LBR80.8%1.592023, 2021
Afghanistan AFG80.8%0.352023
Comoros COM79.7%2.162023, 2010
Somalia, Fed. Rep. SOM79.5%0.872021, 2019
Angola AGO78.5%0.752021, 2019
Kenya KEN73.9%1.332023, 2019
Madagascar MDG72.6%0.322023, 2014
Burundi BDI70.8%0.692023, 2014
Zimbabwe ZWE68.8%1.952023, 2014
Chad TCD66.3%0.152023, 2020
Benin BEN65.6%0.432023, 2021
Ethiopia ETH61.4%0.332023, 2016

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.

Hospital beds

Hospital beds (per 1,000 people)

World Bank · CC BY 4.0 · updated quarterly

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2023. 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 Hospital beds

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

More links with Food insecurity or Hospital beds