placestats

Hospital beds vs. Population 65+

Holds up after adjusting for income

Across 171 countries, Hospital beds and Population 65+ rise and fall together at r = +0.65 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.48 (q = 0.013, 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 population 65+, 4.24% to 17% of population, hospital beds is 2.54 per 1,000 people higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 2.26 per 1,000 people.

Link before adjusting (r)+0.652p = 4.7e-22 · 171 countries
After adjusting for national income+0.475p = 5.8e-11 · likely range [+0.35, +0.58]
p, allowing for regions0.014standard error 0.139 · 7 regions
Check for luck (q)0.013across 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
Population 65+ · % of populationlink with income +0.76 · 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

Hospital beds · per 1,000 people →Population 65+ · % of population →0.1512.81.7%30%Afghanistan: 0.35 per 1,000 people, 2.43% of populationAngola: 0.75 per 1,000 people, 2.89% of populationAlbania: 2.9 per 1,000 people, 17.6% of populationUnited Arab Emirates: 1.87 per 1,000 people, 1.79% of populationArgentina: 3.36 per 1,000 people, 12.6% of populationArmenia: 4.24 per 1,000 people, 14.4% of populationAntigua and Barbuda: 3.42 per 1,000 people, 12.3% of populationAustralia: 3.82 per 1,000 people, 18.1% of populationAustria: 6.7 per 1,000 people, 21.1% of populationAzerbaijan: 3.68 per 1,000 people, 9.17% of populationBurundi: 0.69 per 1,000 people, 2.55% of populationBelgium: 5.42 per 1,000 people, 21% of populationBenin: 0.43 per 1,000 people, 3.15% of populationBurkina Faso: 0.2 per 1,000 people, 2.68% of populationBangladesh: 0.92 per 1,000 people, 6.67% of populationBulgaria: 8.2 per 1,000 people, 22.2% of populationBahrain: 1.84 per 1,000 people, 4.02% of populationBahamas, The: 2.17 per 1,000 people, 12.1% of populationBosnia and Herzegovina: 2.35 per 1,000 people, 22.9% of populationBelarus: 9.77 per 1,000 people, 18.3% of populationBelize: 1 per 1,000 people, 5.23% of populationBolivia: 1.49 per 1,000 people, 5.74% of populationBrazil: 2.52 per 1,000 people, 11.5% of populationBarbados: 6.4 per 1,000 people, 17.1% of populationBrunei Darussalam: 3.58 per 1,000 people, 7.24% of populationBhutan: 2.16 per 1,000 people, 6.63% of populationBotswana: 2.36 per 1,000 people, 4.08% of populationCentral African Republic: 1 per 1,000 people, 2.2% of populationCanada: 2.54 per 1,000 people, 20.3% of populationSwitzerland: 4.38 per 1,000 people, 20.4% of populationChile: 1.94 per 1,000 people, 14.6% of populationChina: 5.63 per 1,000 people, 14.9% of populationCameroon: 2.65 per 1,000 people, 2.82% of populationColombia: 1.7 per 1,000 people, 10.2% of populationComoros: 2.16 per 1,000 people, 4.45% of populationCabo Verde: 2.21 per 1,000 people, 7.15% of populationCosta Rica: 1.14 per 1,000 people, 12.8% of populationCyprus: 2.15 per 1,000 people, 14.9% of populationCzechia: 6.54 per 1,000 people, 21.2% of populationGermany: 7.55 per 1,000 people, 23.7% of populationDjibouti: 1.4 per 1,000 people, 4.97% of populationDominica: 3.97 per 1,000 people, 13.2% of populationDenmark: 2.43 per 1,000 people, 21.1% of populationDominican Republic: 0.75 per 1,000 people, 8.19% of populationAlgeria: 1.61 per 1,000 people, 6.81% of populationEcuador: 1.32 per 1,000 people, 8.6% of populationEgypt, Arab Rep.: 1.06 per 1,000 people, 5.27% of populationSpain: 2.91 per 1,000 people, 21.6% of populationEstonia: 4.13 per 1,000 people, 21.8% of populationEthiopia: 0.33 per 1,000 people, 3.3% of populationFinland: 2.61 per 1,000 people, 24.2% of populationFiji: 1.89 per 1,000 people, 6.63% of populationFrance: 5.65 per 1,000 people, 22.5% of populationGabon: 1.95 per 1,000 people, 4.13% of populationUnited Kingdom: 2.42 per 1,000 people, 19.7% of populationGeorgia: 4.04 per 1,000 people, 16% of populationGhana: 0.69 per 1,000 people, 3.79% of populationGuinea: 0.3 per 1,000 people, 3.47% of populationGambia, The: 1.11 per 1,000 people, 3.18% of populationEquatorial Guinea: 2.1 per 1,000 people, 3.76% of populationGreece: 4.27 per 1,000 people, 24.4% of populationGrenada: 3.01 per 1,000 people, 12.6% of populationGuatemala: 0.45 per 1,000 people, 4.96% of populationGuyana: 3.24 per 1,000 people, 6.98% of populationHonduras: 0.53 per 1,000 people, 4.54% of populationCroatia: 5.6 per 1,000 people, 23.6% of populationHaiti: 4.9 per 1,000 people, 4.79% of populationHungary: 6.63 per 1,000 people, 21.2% of populationIndonesia: 1.37 per 1,000 people, 7.54% of populationIndia: 1.59 per 1,000 people, 7.38% of populationIreland: 2.96 per 1,000 people, 16.2% of populationIran, Islamic Rep.: 1.85 per 1,000 people, 8.58% of populationIraq: 1.06 per 1,000 people, 3.45% of populationIceland: 2.83 per 1,000 people, 16% of populationIsrael: 3.14 per 1,000 people, 12.7% of populationItaly: 3.06 per 1,000 people, 25.1% of populationJamaica: 1.65 per 1,000 people, 8.58% of populationJordan: 1.41 per 1,000 people, 4.75% of populationJapan: 12.6 per 1,000 people, 30% of populationKazakhstan: 6.54 per 1,000 people, 9% of populationKenya: 1.33 per 1,000 people, 3.02% of populationKyrgyz Republic: 3.73 per 1,000 people, 5.97% of populationCambodia: 0.73 per 1,000 people, 6.38% of populationKiribati: 1.86 per 1,000 people, 4.38% of populationSt. Kitts and Nevis: 3.98 per 1,000 people, 11.7% of populationKorea, Rep.: 12.8 per 1,000 people, 20.3% of populationKuwait: 2.33 per 1,000 people, 3.17% of populationLao PDR: 1.71 per 1,000 people, 4.81% of populationLebanon: 2.73 per 1,000 people, 10.4% of populationLiberia: 1.59 per 1,000 people, 3.33% of populationLibya: 3.5 per 1,000 people, 5.19% of populationSt. Lucia: 1.09 per 1,000 people, 9.96% of populationSri Lanka: 3.93 per 1,000 people, 12.5% of populationLithuania: 5.71 per 1,000 people, 20.7% of populationLuxembourg: 3.95 per 1,000 people, 15.8% of populationLatvia: 4.95 per 1,000 people, 22.2% of populationMorocco: 0.73 per 1,000 people, 8.45% of populationMoldova: 5.54 per 1,000 people, 16.9% of populationMadagascar: 0.32 per 1,000 people, 3.47% of populationMaldives: 4.56 per 1,000 people, 4.96% of populationMexico: 1.01 per 1,000 people, 8.52% of populationMarshall Islands: 2.8 per 1,000 people, 4.88% of populationNorth Macedonia: 4.74 per 1,000 people, 18.5% of populationMali: 0.25 per 1,000 people, 2.36% of populationMalta: 4.09 per 1,000 people, 20.5% of populationMyanmar: 1.07 per 1,000 people, 7.52% of populationMontenegro: 3.82 per 1,000 people, 18.3% of populationMongolia: 8.58 per 1,000 people, 5.43% of populationMozambique: 0.74 per 1,000 people, 2.73% of populationMauritius: 3.8 per 1,000 people, 14.1% of populationMalawi: 1.3 per 1,000 people, 2.59% of populationMalaysia: 1.96 per 1,000 people, 8.03% of populationNiger: 0.28 per 1,000 people, 2.62% of populationNicaragua: 0.97 per 1,000 people, 5.7% of populationNetherlands: 2.42 per 1,000 people, 20.9% of populationNorway: 3.3 per 1,000 people, 19.1% of populationNepal: 0.54 per 1,000 people, 6.62% of populationNaoero: 4.97 per 1,000 people, 3.01% of populationNew Zealand: 2.51 per 1,000 people, 17.6% of populationOman: 0.99 per 1,000 people, 2.69% of populationPakistan: 0.63 per 1,000 people, 4.36% of populationPanama: 1.95 per 1,000 people, 9.66% of populationPeru: 1.56 per 1,000 people, 9.47% of populationPhilippines: 0.97 per 1,000 people, 5.72% of populationPalau: 4.34 per 1,000 people, 11.8% of populationPapua New Guinea: 0.62 per 1,000 people, 3.59% of populationPoland: 6.04 per 1,000 people, 20.8% of populationPortugal: 3.48 per 1,000 people, 24.9% of populationParaguay: 1.04 per 1,000 people, 6.72% of populationWest Bank and Gaza: 1.3 per 1,000 people, 3.85% of populationQatar: 1.25 per 1,000 people, 1.7% of populationRomania: 7.23 per 1,000 people, 20.1% of populationRussian Federation: 6.81 per 1,000 people, 17.8% of populationRwanda: 0.75 per 1,000 people, 4.02% of populationSaudi Arabia: 2.41 per 1,000 people, 3.06% of populationSudan: 0.66 per 1,000 people, 3.39% of populationSenegal: 0.71 per 1,000 people, 3.65% of populationSingapore: 2.81 per 1,000 people, 14.2% of populationEl Salvador: 1.21 per 1,000 people, 8.31% of populationSan Marino: 3.35 per 1,000 people, 23.1% of populationSomalia, Fed. Rep.: 0.87 per 1,000 people, 2.62% of populationSerbia: 5.78 per 1,000 people, 23.1% of populationSao Tome and Principe: 2.91 per 1,000 people, 3.94% of populationSuriname: 2.87 per 1,000 people, 8.19% of populationSlovak Republic: 5.57 per 1,000 people, 19% of populationSlovenia: 4.11 per 1,000 people, 22.2% of populationSweden: 1.9 per 1,000 people, 20.9% of populationEswatini: 2.02 per 1,000 people, 4.35% of populationSeychelles: 2.63 per 1,000 people, 8.75% of populationSyrian Arab Republic: 1.43 per 1,000 people, 4.84% of populationChad: 0.15 per 1,000 people, 2.12% of populationTogo: 0.33 per 1,000 people, 3.48% of populationThailand: 2.39 per 1,000 people, 16% of populationTajikistan: 4.04 per 1,000 people, 4.07% of populationTurkmenistan: 3.6 per 1,000 people, 4.81% of populationTimor-Leste: 0.38 per 1,000 people, 5.23% of populationTonga: 2.48 per 1,000 people, 6.85% of populationTrinidad and Tobago: 2.37 per 1,000 people, 12.9% of populationTunisia: 1.82 per 1,000 people, 9.94% of populationTurkiye: 3.05 per 1,000 people, 10.6% of populationTanzania: 0.84 per 1,000 people, 3.04% of populationUganda: 0.5 per 1,000 people, 2.23% of populationUkraine: 6.14 per 1,000 people, 19% of populationUruguay: 2.44 per 1,000 people, 16.3% of populationUnited States: 2.68 per 1,000 people, 18.4% of populationUzbekistan: 4.89 per 1,000 people, 6.07% of populationSt. Vincent and the Grenadines: 3.21 per 1,000 people, 12.3% of populationViet Nam: 2.52 per 1,000 people, 9.49% of populationSouth Africa: 2.25 per 1,000 people, 6.89% of populationZambia: 2 per 1,000 people, 2% of populationZimbabwe: 1.95 per 1,000 people, 3.56% of populationBFABIHBLRFINITAJPNKORMLIMNGTCD

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.6524.7e-22171
By rank (Spearman), not adjusted+0.7001.8e-26171
Standard (Pearson), adjusted for national income+0.4755.8e-11171
By rank (Spearman), adjusted for national income+0.4421.6e-9171

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: +0.177 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.435 (without JPN) to +0.510 (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: JPN (-0.041).

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+0.52
Europe & Central Asia49+0.21
Latin America & Caribbean31+0.55
Middle East, North Africa, Afghanistan & Pakistan22+0.67
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+0.16
Middle third57+0.34
Richest third57+0.50

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+0.59
Muslims44+0.27

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+0.35
Never a European colony21+0.61
Spain19+0.26
United Kingdom56+0.38

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 = +0.474 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 = +0.006, 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 population 65+ move with it.

Across countries (adjusted)+0.475for comparison
Within countries-0.356each country vs itself
…and vs the same year elsewhere+0.006q = 0.977 · 154 countries
Year-on-year changes+0.053q = 0.676
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.
  • Much of the within-country association disappears once shared global year effects are removed, which points to a common worldwide trend rather than a country-level relationship.

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: 9% for Hospital beds, 17% for Population 65+. 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

0.10−0.1-100+10years Population 65+ trails Hospital beds →lag -10: r = -0.005 (n = 2,883)lag -9: r = -0.008 (n = 2,941)lag -8: r = -0.010 (n = 3,002)lag -7: r = -0.011 (n = 3,069)lag -6: r = -0.025 (n = 3,167)lag -5: r = -0.007 (n = 3,234)lag -4: r = 0.005 (n = 3,303)lag -3: r = 0.005 (n = 3,393)lag -2: r = 0.016 (n = 3,461)lag -1: r = 0.031 (n = 3,529)lag +0: r = 0.006 (n = 3,659)lag +1: r = 0.014 (n = 3,659)lag +2: r = 0.021 (n = 3,659)lag +3: r = 0.029 (n = 3,587)lag +4: r = 0.034 (n = 3,476)lag +5: r = 0.039 (n = 3,347)lag +6: r = 0.043 (n = 3,217)lag +7: r = 0.053 (n = 3,076)lag +8: r = 0.060 (n = 2,941)lag +9: r = 0.060 (n = 2,804)lag +10: r = 0.061 (n = 2,668)

Same year (lag 0): +0.006. 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


per 1,000 people
% of population		Years
Korea, Rep. KOR12.820.3%2022, 2025
Japan JPN12.630%2022, 2025
Belarus BLR9.7718.3%2023, 2025
Mongolia MNG8.585.43%2023, 2025
Bulgaria BGR8.222.2%2023, 2025
Germany DEU7.5523.7%2023, 2025
Romania ROU7.2320.1%2022, 2025
Russian Federation RUS6.8117.8%2023, 2025
Austria AUT6.721.1%2022, 2025
Hungary HUN6.6321.2%2022, 2025
Kazakhstan KAZ6.549%2020, 2025
Czechia CZE6.5421.2%2022, 2025
Barbados BRB6.417.1%2023, 2025
Ukraine UKR6.1419%2022, 2025
Poland POL6.0420.8%2022, 2025

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

Sources

Hospital beds

Hospital beds (per 1,000 people)

World Bank · CC BY 4.0 · updated quarterly

Population 65+

Population ages 65 and above (% of total)

World Bank · CC BY 4.0 · updated quarterly

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2025. 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 Hospital beds and Population 65+

This page shows that two measures go together. It does not show that Hospital beds changes Population 65+, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Hospital beds or Population 65+