placestats

Hospital beds vs. Median age

Holds up after adjusting for income

Across 171 countries, Hospital beds and Median age rise and fall together at r = +0.66 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.49 (q = 0.0027, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a moderate positive link remains.

Comparing countries across the middle half of median age, 22.5 to 38.2 years, hospital beds is 2.49 per 1,000 people higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 2.95 per 1,000 people.

Link before adjusting (r)+0.659p = 1.1e-22 · 171 countries
After adjusting for national income+0.491p = 1.1e-11 · likely range [+0.37, +0.60]
p, allowing for regions0.003standard error 0.105 · 7 regions
Check for luck (q)0.003across 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.

Hospital beds · per 1,000 peoplelink with income +0.63 · high
Median age · yearslink 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

Hospital beds · per 1,000 people →Median age · years →0.1512.814.349Afghanistan: 0.35 per 1,000 people, 16.9 yearsAngola: 0.75 per 1,000 people, 16.5 yearsAlbania: 2.9 per 1,000 people, 36.3 yearsUnited Arab Emirates: 1.87 per 1,000 people, 31.2 yearsArgentina: 3.36 per 1,000 people, 32.1 yearsArmenia: 4.24 per 1,000 people, 35.8 yearsAntigua and Barbuda: 3.42 per 1,000 people, 35.5 yearsAustralia: 3.82 per 1,000 people, 37.8 yearsAustria: 6.7 per 1,000 people, 43.1 yearsAzerbaijan: 3.68 per 1,000 people, 32.6 yearsBurundi: 0.69 per 1,000 people, 15.9 yearsBelgium: 5.42 per 1,000 people, 41.4 yearsBenin: 0.43 per 1,000 people, 17.8 yearsBurkina Faso: 0.2 per 1,000 people, 17.3 yearsBangladesh: 0.92 per 1,000 people, 25.3 yearsBulgaria: 8.2 per 1,000 people, 44.3 yearsBahrain: 1.84 per 1,000 people, 32.9 yearsBahamas, The: 2.17 per 1,000 people, 34.6 yearsBosnia and Herzegovina: 2.35 per 1,000 people, 44.9 yearsBelarus: 9.77 per 1,000 people, 40.5 yearsBelize: 1 per 1,000 people, 25.9 yearsBolivia: 1.49 per 1,000 people, 24.7 yearsBrazil: 2.52 per 1,000 people, 33.9 yearsBarbados: 6.4 per 1,000 people, 38.9 yearsBrunei Darussalam: 3.58 per 1,000 people, 31.8 yearsBhutan: 2.16 per 1,000 people, 29.4 yearsBotswana: 2.36 per 1,000 people, 22.9 yearsCentral African Republic: 1 per 1,000 people, 14.3 yearsCanada: 2.54 per 1,000 people, 40.3 yearsSwitzerland: 4.38 per 1,000 people, 42.3 yearsChile: 1.94 per 1,000 people, 36 yearsChina: 5.63 per 1,000 people, 39.1 yearsCameroon: 2.65 per 1,000 people, 17.8 yearsColombia: 1.7 per 1,000 people, 31.6 yearsComoros: 2.16 per 1,000 people, 20.3 yearsCabo Verde: 2.21 per 1,000 people, 27.9 yearsCosta Rica: 1.14 per 1,000 people, 34.1 yearsCyprus: 2.15 per 1,000 people, 37.8 yearsCzechia: 6.54 per 1,000 people, 42.7 yearsGermany: 7.55 per 1,000 people, 45.1 yearsDjibouti: 1.4 per 1,000 people, 24.4 yearsDominica: 3.97 per 1,000 people, 35.6 yearsDenmark: 2.43 per 1,000 people, 41.2 yearsDominican Republic: 0.75 per 1,000 people, 27.7 yearsAlgeria: 1.61 per 1,000 people, 28.2 yearsEcuador: 1.32 per 1,000 people, 28.4 yearsEgypt, Arab Rep.: 1.06 per 1,000 people, 24 yearsSpain: 2.91 per 1,000 people, 44.9 yearsEstonia: 4.13 per 1,000 people, 41.9 yearsEthiopia: 0.33 per 1,000 people, 18.7 yearsFinland: 2.61 per 1,000 people, 42.8 yearsFiji: 1.89 per 1,000 people, 27.7 yearsFrance: 5.65 per 1,000 people, 41.8 yearsGabon: 1.95 per 1,000 people, 21.5 yearsUnited Kingdom: 2.42 per 1,000 people, 39.8 yearsGeorgia: 4.04 per 1,000 people, 36.8 yearsGhana: 0.69 per 1,000 people, 20.9 yearsGuinea: 0.3 per 1,000 people, 18 yearsGambia, The: 1.11 per 1,000 people, 18.2 yearsEquatorial Guinea: 2.1 per 1,000 people, 21 yearsGreece: 4.27 per 1,000 people, 45.7 yearsGrenada: 3.01 per 1,000 people, 33.4 yearsGuatemala: 0.45 per 1,000 people, 22.6 yearsGuyana: 3.24 per 1,000 people, 25.6 yearsHonduras: 0.53 per 1,000 people, 23.5 yearsCroatia: 5.6 per 1,000 people, 44.8 yearsHaiti: 4.9 per 1,000 people, 23.5 yearsHungary: 6.63 per 1,000 people, 43.3 yearsIndonesia: 1.37 per 1,000 people, 29.8 yearsIndia: 1.59 per 1,000 people, 28.1 yearsIreland: 2.96 per 1,000 people, 38.4 yearsIran, Islamic Rep.: 1.85 per 1,000 people, 32.9 yearsIraq: 1.06 per 1,000 people, 20.3 yearsIceland: 2.83 per 1,000 people, 35.8 yearsIsrael: 3.14 per 1,000 people, 29.1 yearsItaly: 3.06 per 1,000 people, 47.5 yearsJamaica: 1.65 per 1,000 people, 31.7 yearsJordan: 1.41 per 1,000 people, 24.3 yearsJapan: 12.6 per 1,000 people, 49 yearsKazakhstan: 6.54 per 1,000 people, 29.5 yearsKenya: 1.33 per 1,000 people, 19.5 yearsKyrgyz Republic: 3.73 per 1,000 people, 25.1 yearsCambodia: 0.73 per 1,000 people, 25.8 yearsKiribati: 1.86 per 1,000 people, 22.7 yearsSt. Kitts and Nevis: 3.98 per 1,000 people, 35.3 yearsKorea, Rep.: 12.8 per 1,000 people, 44.5 yearsKuwait: 2.33 per 1,000 people, 34.5 yearsLao PDR: 1.71 per 1,000 people, 24.3 yearsLebanon: 2.73 per 1,000 people, 28.3 yearsLiberia: 1.59 per 1,000 people, 18.4 yearsLibya: 3.5 per 1,000 people, 27.2 yearsSt. Lucia: 1.09 per 1,000 people, 33.7 yearsSri Lanka: 3.93 per 1,000 people, 32.8 yearsLithuania: 5.71 per 1,000 people, 42.1 yearsLuxembourg: 3.95 per 1,000 people, 38.9 yearsLatvia: 4.95 per 1,000 people, 43.1 yearsMorocco: 0.73 per 1,000 people, 29.2 yearsMoldova: 5.54 per 1,000 people, 37.8 yearsMadagascar: 0.32 per 1,000 people, 18.9 yearsMaldives: 4.56 per 1,000 people, 31.1 yearsMexico: 1.01 per 1,000 people, 28.9 yearsMarshall Islands: 2.8 per 1,000 people, 20.7 yearsNorth Macedonia: 4.74 per 1,000 people, 40.3 yearsMali: 0.25 per 1,000 people, 15.5 yearsMalta: 4.09 per 1,000 people, 40.3 yearsMyanmar: 1.07 per 1,000 people, 29.5 yearsMontenegro: 3.82 per 1,000 people, 39.3 yearsMongolia: 8.58 per 1,000 people, 26.8 yearsMozambique: 0.74 per 1,000 people, 16.3 yearsMauritius: 3.8 per 1,000 people, 36.9 yearsMalawi: 1.3 per 1,000 people, 17.6 yearsMalaysia: 1.96 per 1,000 people, 30.1 yearsNiger: 0.28 per 1,000 people, 15.3 yearsNicaragua: 0.97 per 1,000 people, 25.3 yearsNetherlands: 2.42 per 1,000 people, 41.4 yearsNorway: 3.3 per 1,000 people, 39.5 yearsNepal: 0.54 per 1,000 people, 24.7 yearsNaoero: 4.97 per 1,000 people, 20.4 yearsNew Zealand: 2.51 per 1,000 people, 37.3 yearsOman: 0.99 per 1,000 people, 29.3 yearsPakistan: 0.63 per 1,000 people, 20.3 yearsPanama: 1.95 per 1,000 people, 29.6 yearsPeru: 1.56 per 1,000 people, 29.5 yearsPhilippines: 0.97 per 1,000 people, 25.3 yearsPalau: 4.34 per 1,000 people, 37.8 yearsPapua New Guinea: 0.62 per 1,000 people, 22.3 yearsPoland: 6.04 per 1,000 people, 41.3 yearsPortugal: 3.48 per 1,000 people, 46.2 yearsParaguay: 1.04 per 1,000 people, 26.3 yearsWest Bank and Gaza: 1.3 per 1,000 people, 19.8 yearsQatar: 1.25 per 1,000 people, 33.2 yearsRomania: 7.23 per 1,000 people, 42.6 yearsRussian Federation: 6.81 per 1,000 people, 39.5 yearsRwanda: 0.75 per 1,000 people, 19.4 yearsSaudi Arabia: 2.41 per 1,000 people, 29.2 yearsSudan: 0.66 per 1,000 people, 18.3 yearsSenegal: 0.71 per 1,000 people, 19.1 yearsSingapore: 2.81 per 1,000 people, 35.1 yearsEl Salvador: 1.21 per 1,000 people, 27 yearsSan Marino: 3.35 per 1,000 people, 47.4 yearsSomalia, Fed. Rep.: 0.87 per 1,000 people, 15.4 yearsSerbia: 5.78 per 1,000 people, 43.9 yearsSao Tome and Principe: 2.91 per 1,000 people, 19.1 yearsSuriname: 2.87 per 1,000 people, 28.1 yearsSlovak Republic: 5.57 per 1,000 people, 41.3 yearsSlovenia: 4.11 per 1,000 people, 43.9 yearsSweden: 1.9 per 1,000 people, 39.9 yearsEswatini: 2.02 per 1,000 people, 22 yearsSeychelles: 2.63 per 1,000 people, 33.7 yearsSyrian Arab Republic: 1.43 per 1,000 people, 22.2 yearsChad: 0.15 per 1,000 people, 15.4 yearsTogo: 0.33 per 1,000 people, 18.1 yearsThailand: 2.39 per 1,000 people, 39.7 yearsTajikistan: 4.04 per 1,000 people, 21.9 yearsTurkmenistan: 3.6 per 1,000 people, 26.2 yearsTimor-Leste: 0.38 per 1,000 people, 21 yearsTonga: 2.48 per 1,000 people, 20.7 yearsTrinidad and Tobago: 2.37 per 1,000 people, 36.7 yearsTunisia: 1.82 per 1,000 people, 32.1 yearsTurkiye: 3.05 per 1,000 people, 32.5 yearsTanzania: 0.84 per 1,000 people, 17.2 yearsUganda: 0.5 per 1,000 people, 16.5 yearsUkraine: 6.14 per 1,000 people, 42 yearsUruguay: 2.44 per 1,000 people, 35.8 yearsUnited States: 2.68 per 1,000 people, 38 yearsUzbekistan: 4.89 per 1,000 people, 26.9 yearsSt. Vincent and the Grenadines: 3.21 per 1,000 people, 33.9 yearsViet Nam: 2.52 per 1,000 people, 32.4 yearsSouth Africa: 2.25 per 1,000 people, 28.2 yearsZambia: 2 per 1,000 people, 17.5 yearsZimbabwe: 1.95 per 1,000 people, 17.8 yearsBIHBLRITAJPNKORMLIMNGNERSMRTCD

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.6591.1e-22171
By rank (Spearman), not adjusted+0.7301.0e-29171
Standard (Pearson), adjusted for national income+0.4911.1e-11171
By rank (Spearman), adjusted for national income+0.4701.0e-10171

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 171 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: +0.169 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.466 (without JPN) to +0.521 (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: MNG (+0.031).

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 & Pacific24+0.47
Europe & Central Asia49+0.27
Latin America & Caribbean31+0.51
Middle East, North Africa, Afghanistan & Pakistan22+0.45
Sub-Saharan Africa37+0.38

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 third57+0.17
Middle third57+0.37
Richest third57+0.52

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
Christians100+0.60
Muslims44+0.21

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
France22+0.44
Never a European colony21+0.49
Spain19+0.11
United Kingdom56+0.33

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 = +0.489 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.

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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 34years. 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 = +0.212, 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 hospital beds moved did not tend to see their median age move with it.

Across countries (adjusted)+0.491for comparison
Within countries-0.369each country vs itself
…and vs the same year elsewhere+0.212q = 0.119 · 154 countries
Year-on-year changes+0.105q = 0.099
The direction flips. Comparing each country only with itself gives -0.37. Also taking out what happened to the whole world each year gives +0.21. So the first figure was picking up a trend both measures share with worldwide progress, not a link between them.

3,659 country-years (one country in one year), 154 countries, 1990–2023, about 24 years each on average. Share of the variation that happens within countries over time: 11% for Hospital beds, 17% for Median age. 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+10years Median age trails Hospital beds →lag -10: r = 0.187 (n = 2,883)lag -9: r = 0.204 (n = 2,941)lag -8: r = 0.209 (n = 3,002)lag -7: r = 0.220 (n = 3,069)lag -6: r = 0.211 (n = 3,167)lag -5: r = 0.227 (n = 3,234)lag -4: r = 0.232 (n = 3,303)lag -3: r = 0.229 (n = 3,393)lag -2: r = 0.237 (n = 3,461)lag -1: r = 0.243 (n = 3,529)lag +0: r = 0.212 (n = 3,659)lag +1: r = 0.218 (n = 3,587)lag +2: r = 0.219 (n = 3,476)lag +3: r = 0.223 (n = 3,347)lag +4: r = 0.225 (n = 3,217)lag +5: r = 0.230 (n = 3,076)lag +6: r = 0.231 (n = 2,941)lag +7: r = 0.230 (n = 2,804)lag +8: r = 0.228 (n = 2,668)lag +9: r = 0.225 (n = 2,520)lag +10: r = 0.229 (n = 2,371)

Same year (lag 0): +0.212. 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 data


per 1,000 people
years		Years
Korea, Rep. KOR12.844.52022, 2023
Japan JPN12.6492022, 2023
Belarus BLR9.7740.52023
Mongolia MNG8.5826.82023
Bulgaria BGR8.244.32023
Germany DEU7.5545.12023
Romania ROU7.2342.62022, 2023
Russian Federation RUS6.8139.52023
Austria AUT6.743.12022, 2023
Hungary HUN6.6343.32022, 2023
Kazakhstan KAZ6.5429.52020, 2023
Czechia CZE6.5442.72022, 2023
Barbados BRB6.438.92023
Ukraine UKR6.14422022, 2023
Poland POL6.0441.32022, 2023

World Bank, World Development Indicators
United Nations, Department of Economic and Social Affairs, Population Division: World Population Prospects 2024 and Estimates and Projections of Women of Reproductive Age Who Are Married or in a Union

Sources

Hospital beds

Hospital beds (per 1,000 people)

World Bank · CC BY 4.0 · updated quarterly

Median age

Median age of the population

United Nations Department of Economic and Social Affairs, Population Division · via Our World in Data · CC BY 3.0 IGO · updated biennial

The age that splits a population in half: half are older and half are younger. The shares aged under 15 and over 65 are already on the site. All three are treated as measuring the same thing. They are readings of the same age pyramid, so they are bound to match, and their agreement is not a finding. No "better" direction is set.

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 Hospital beds and Median age

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

More links with Hospital beds or Median age