placestats

Fertility rate vs. Hospital beds

Fades after adjusting for income

Across 171 countries, Fertility rate and Hospital beds rise and fall together at r = -0.50 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.17, which could easily be chance (q = 0.22, 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 fertility rate, 1.45 to 2.87 births per woman, hospital beds is 1.34 per 1,000 people lower at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.667 per 1,000 people.

Link before adjusting (r)-0.503p = 2.3e-12 · 171 countries
After adjusting for national income-0.166p = 0.031 · likely range [-0.31, -0.02]
p, allowing for regions0.070standard error 0.075 · 7 regions
Check for luck (q)0.219across 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.

Fertility rate · births per womanlink with income -0.81 · 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

Fertility rate · births per woman →Hospital beds · per 1,000 people →0.7486.030.1512.8Afghanistan: 4.76 births per woman, 0.35 per 1,000 peopleAngola: 5.05 births per woman, 0.75 per 1,000 peopleAlbania: 1.34 births per woman, 2.9 per 1,000 peopleUnited Arab Emirates: 1.21 births per woman, 1.87 per 1,000 peopleArgentina: 1.5 births per woman, 3.36 per 1,000 peopleArmenia: 1.7 births per woman, 4.24 per 1,000 peopleAntigua and Barbuda: 1.58 births per woman, 3.42 per 1,000 peopleAustralia: 1.48 births per woman, 3.82 per 1,000 peopleAustria: 1.31 births per woman, 6.7 per 1,000 peopleAzerbaijan: 1.43 births per woman, 3.68 per 1,000 peopleBurundi: 4.79 births per woman, 0.69 per 1,000 peopleBelgium: 1.44 births per woman, 5.42 per 1,000 peopleBenin: 4.48 births per woman, 0.43 per 1,000 peopleBurkina Faso: 4.11 births per woman, 0.2 per 1,000 peopleBangladesh: 2.14 births per woman, 0.92 per 1,000 peopleBulgaria: 1.72 births per woman, 8.2 per 1,000 peopleBahrain: 1.8 births per woman, 1.84 per 1,000 peopleBahamas, The: 1.37 births per woman, 2.17 per 1,000 peopleBosnia and Herzegovina: 1.49 births per woman, 2.35 per 1,000 peopleBelarus: 1.22 births per woman, 9.77 per 1,000 peopleBelize: 2.02 births per woman, 1 per 1,000 peopleBolivia: 2.52 births per woman, 1.49 per 1,000 peopleBrazil: 1.61 births per woman, 2.52 per 1,000 peopleBarbados: 1.71 births per woman, 6.4 per 1,000 peopleBrunei Darussalam: 1.73 births per woman, 3.58 per 1,000 peopleBhutan: 1.45 births per woman, 2.16 per 1,000 peopleBotswana: 2.7 births per woman, 2.36 per 1,000 peopleCentral African Republic: 5.95 births per woman, 1 per 1,000 peopleCanada: 1.25 births per woman, 2.54 per 1,000 peopleSwitzerland: 1.29 births per woman, 4.38 per 1,000 peopleChile: 1.14 births per woman, 1.94 per 1,000 peopleChina: 1.01 births per woman, 5.63 per 1,000 peopleCameroon: 4.26 births per woman, 2.65 per 1,000 peopleColombia: 1.63 births per woman, 1.7 per 1,000 peopleComoros: 3.82 births per woman, 2.16 per 1,000 peopleCabo Verde: 1.51 births per woman, 2.21 per 1,000 peopleCosta Rica: 1.32 births per woman, 1.14 per 1,000 peopleCyprus: 1.38 births per woman, 2.15 per 1,000 peopleCzechia: 1.36 births per woman, 6.54 per 1,000 peopleGermany: 1.36 births per woman, 7.55 per 1,000 peopleDjibouti: 2.62 births per woman, 1.4 per 1,000 peopleDominica: 1.48 births per woman, 3.97 per 1,000 peopleDenmark: 1.47 births per woman, 2.43 per 1,000 peopleDominican Republic: 2.22 births per woman, 0.75 per 1,000 peopleAlgeria: 2.72 births per woman, 1.61 per 1,000 peopleEcuador: 1.81 births per woman, 1.32 per 1,000 peopleEgypt, Arab Rep.: 2.73 births per woman, 1.06 per 1,000 peopleSpain: 1.1 births per woman, 2.91 per 1,000 peopleEstonia: 1.18 births per woman, 4.13 per 1,000 peopleEthiopia: 3.91 births per woman, 0.33 per 1,000 peopleFinland: 1.25 births per woman, 2.61 per 1,000 peopleFiji: 2.27 births per woman, 1.89 per 1,000 peopleFrance: 1.61 births per woman, 5.65 per 1,000 peopleGabon: 3.59 births per woman, 1.95 per 1,000 peopleUnited Kingdom: 1.55 births per woman, 2.42 per 1,000 peopleGeorgia: 1.8 births per woman, 4.04 per 1,000 peopleGhana: 3.34 births per woman, 0.69 per 1,000 peopleGuinea: 4.13 births per woman, 0.3 per 1,000 peopleGambia, The: 3.91 births per woman, 1.11 per 1,000 peopleEquatorial Guinea: 4.12 births per woman, 2.1 per 1,000 peopleGreece: 1.24 births per woman, 4.27 per 1,000 peopleGrenada: 1.47 births per woman, 3.01 per 1,000 peopleGuatemala: 2.29 births per woman, 0.45 per 1,000 peopleGuyana: 2.4 births per woman, 3.24 per 1,000 peopleHonduras: 2.48 births per woman, 0.53 per 1,000 peopleCroatia: 1.46 births per woman, 5.6 per 1,000 peopleHaiti: 2.63 births per woman, 4.9 per 1,000 peopleHungary: 1.41 births per woman, 6.63 per 1,000 peopleIndonesia: 2.12 births per woman, 1.37 per 1,000 peopleIndia: 1.96 births per woman, 1.59 per 1,000 peopleIreland: 1.47 births per woman, 2.96 per 1,000 peopleIran, Islamic Rep.: 1.68 births per woman, 1.85 per 1,000 peopleIraq: 3.22 births per woman, 1.06 per 1,000 peopleIceland: 1.56 births per woman, 2.83 per 1,000 peopleIsrael: 2.87 births per woman, 3.14 per 1,000 peopleItaly: 1.18 births per woman, 3.06 per 1,000 peopleJamaica: 1.35 births per woman, 1.65 per 1,000 peopleJordan: 2.6 births per woman, 1.41 per 1,000 peopleJapan: 1.15 births per woman, 12.6 per 1,000 peopleKazakhstan: 2.98 births per woman, 6.54 per 1,000 peopleKenya: 3.17 births per woman, 1.33 per 1,000 peopleKyrgyz Republic: 2.6 births per woman, 3.73 per 1,000 peopleCambodia: 2.55 births per woman, 0.73 per 1,000 peopleKiribati: 3.12 births per woman, 1.86 per 1,000 peopleSt. Kitts and Nevis: 1.53 births per woman, 3.98 per 1,000 peopleKorea, Rep.: 0.748 births per woman, 12.8 per 1,000 peopleKuwait: 1.56 births per woman, 2.33 per 1,000 peopleLao PDR: 2.4 births per woman, 1.71 per 1,000 peopleLebanon: 2.23 births per woman, 2.73 per 1,000 peopleLiberia: 3.86 births per woman, 1.59 per 1,000 peopleLibya: 2.3 births per woman, 3.5 per 1,000 peopleSt. Lucia: 1.39 births per woman, 1.09 per 1,000 peopleSri Lanka: 1.95 births per woman, 3.93 per 1,000 peopleLithuania: 1.11 births per woman, 5.71 per 1,000 peopleLuxembourg: 1.25 births per woman, 3.95 per 1,000 peopleLatvia: 1.24 births per woman, 4.95 per 1,000 peopleMorocco: 2.21 births per woman, 0.73 per 1,000 peopleMoldova: 1.73 births per woman, 5.54 per 1,000 peopleMadagascar: 3.91 births per woman, 0.32 per 1,000 peopleMaldives: 1.56 births per woman, 4.56 per 1,000 peopleMexico: 1.89 births per woman, 1.01 per 1,000 peopleMarshall Islands: 2.86 births per woman, 2.8 per 1,000 peopleNorth Macedonia: 1.4 births per woman, 4.74 per 1,000 peopleMali: 5.51 births per woman, 0.25 per 1,000 peopleMalta: 1.01 births per woman, 4.09 per 1,000 peopleMyanmar: 2.1 births per woman, 1.07 per 1,000 peopleMontenegro: 1.8 births per woman, 3.82 per 1,000 peopleMongolia: 2.5 births per woman, 8.58 per 1,000 peopleMozambique: 4.69 births per woman, 0.74 per 1,000 peopleMauritius: 1.44 births per woman, 3.8 per 1,000 peopleMalawi: 3.59 births per woman, 1.3 per 1,000 peopleMalaysia: 1.54 births per woman, 1.96 per 1,000 peopleNiger: 5.93 births per woman, 0.28 per 1,000 peopleNicaragua: 2.21 births per woman, 0.97 per 1,000 peopleNetherlands: 1.43 births per woman, 2.42 per 1,000 peopleNorway: 1.45 births per woman, 3.3 per 1,000 peopleNepal: 1.96 births per woman, 0.54 per 1,000 peopleNaoero: 3.29 births per woman, 4.97 per 1,000 peopleNew Zealand: 1.57 births per woman, 2.51 per 1,000 peopleOman: 2.51 births per woman, 0.99 per 1,000 peoplePakistan: 3.55 births per woman, 0.63 per 1,000 peoplePanama: 2.11 births per woman, 1.95 per 1,000 peoplePeru: 1.97 births per woman, 1.56 per 1,000 peoplePhilippines: 1.89 births per woman, 0.97 per 1,000 peoplePalau: 1.88 births per woman, 4.34 per 1,000 peoplePapua New Guinea: 3.07 births per woman, 0.62 per 1,000 peoplePoland: 1.14 births per woman, 6.04 per 1,000 peoplePortugal: 1.41 births per woman, 3.48 per 1,000 peopleParaguay: 2.42 births per woman, 1.04 per 1,000 peopleWest Bank and Gaza: 3.25 births per woman, 1.3 per 1,000 peopleQatar: 1.72 births per woman, 1.25 per 1,000 peopleRomania: 1.39 births per woman, 7.23 per 1,000 peopleRussian Federation: 1.42 births per woman, 6.81 per 1,000 peopleRwanda: 3.65 births per woman, 0.75 per 1,000 peopleSaudi Arabia: 2.31 births per woman, 2.41 per 1,000 peopleSudan: 4.26 births per woman, 0.66 per 1,000 peopleSenegal: 3.77 births per woman, 0.71 per 1,000 peopleSingapore: 0.97 births per woman, 2.81 per 1,000 peopleEl Salvador: 1.77 births per woman, 1.21 per 1,000 peopleSan Marino: 1.16 births per woman, 3.35 per 1,000 peopleSomalia, Fed. Rep.: 6.01 births per woman, 0.87 per 1,000 peopleSerbia: 1.64 births per woman, 5.78 per 1,000 peopleSao Tome and Principe: 3.6 births per woman, 2.91 per 1,000 peopleSuriname: 2.23 births per woman, 2.87 per 1,000 peopleSlovak Republic: 1.46 births per woman, 5.57 per 1,000 peopleSlovenia: 1.52 births per woman, 4.11 per 1,000 peopleSweden: 1.43 births per woman, 1.9 per 1,000 peopleEswatini: 2.72 births per woman, 2.02 per 1,000 peopleSeychelles: 1.85 births per woman, 2.63 per 1,000 peopleSyrian Arab Republic: 2.7 births per woman, 1.43 per 1,000 peopleChad: 6.03 births per woman, 0.15 per 1,000 peopleTogo: 4.12 births per woman, 0.33 per 1,000 peopleThailand: 1.2 births per woman, 2.39 per 1,000 peopleTajikistan: 3.04 births per woman, 4.04 per 1,000 peopleTurkmenistan: 2.66 births per woman, 3.6 per 1,000 peopleTimor-Leste: 2.63 births per woman, 0.38 per 1,000 peopleTonga: 3.1 births per woman, 2.48 per 1,000 peopleTrinidad and Tobago: 1.54 births per woman, 2.37 per 1,000 peopleTunisia: 1.82 births per woman, 1.82 per 1,000 peopleTurkiye: 1.48 births per woman, 3.05 per 1,000 peopleTanzania: 4.54 births per woman, 0.84 per 1,000 peopleUganda: 4.17 births per woman, 0.5 per 1,000 peopleUkraine: 0.988 births per woman, 6.14 per 1,000 peopleUruguay: 1.4 births per woman, 2.44 per 1,000 peopleUnited States: 1.63 births per woman, 2.68 per 1,000 peopleUzbekistan: 3.49 births per woman, 4.89 per 1,000 peopleSt. Vincent and the Grenadines: 1.76 births per woman, 3.21 per 1,000 peopleViet Nam: 1.9 births per woman, 2.52 per 1,000 peopleSouth Africa: 2.21 births per woman, 2.25 per 1,000 peopleZambia: 4.04 births per woman, 2 per 1,000 peopleZimbabwe: 3.67 births per woman, 1.95 per 1,000 peopleBLRCHLCRIJPNKORLCAMNGNERSOMTCD

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5032.3e-12171
By rank (Spearman), not adjusted-0.6211.4e-19171
Standard (Pearson), adjusted for national income-0.1660.031171
By rank (Spearman), adjusted for national income-0.2430.001171

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: +0.337 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.189 (without KAZ) to -0.146 (without HTI). 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: KAZ (-0.023).

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 & Pacific24-0.10
Europe & Central Asia49-0.09
Latin America & Caribbean31-0.12
Middle East, North Africa, Afghanistan & Pakistan22-0.35
Sub-Saharan Africa37-0.35

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 third57-0.24
Middle third57-0.04
Richest third57-0.29

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
Christians100-0.20
Muslims44-0.13

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
France22-0.48
Never a European colony21-0.14
Spain19+0.13
United Kingdom56-0.15

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 = -0.152 after dropping 11 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.

The link shows up within countries over time (r = -0.265) but mostly disappears in year-to-year changes (r = +0.015). That points to slow trends particular to each country, not the two measures moving together from year to year.

Across countries (adjusted)-0.166for comparison
Within countries+0.146each country vs itself
…and vs the same year elsewhere-0.265q = 0.000 · 154 countries
Year-on-year changes+0.015q = 0.731
Read with care.
  • The association is much weaker in year-on-year changes than in levels, which points to shared country-specific trends.

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: 14% for Fertility rate, 17% 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

0.40−0.4-100+10years Hospital beds trails Fertility rate →lag -10: r = -0.387 (n = 2,520)lag -9: r = -0.386 (n = 2,668)lag -8: r = -0.384 (n = 2,804)lag -7: r = -0.375 (n = 2,941)lag -6: r = -0.366 (n = 3,076)lag -5: r = -0.352 (n = 3,217)lag -4: r = -0.337 (n = 3,347)lag -3: r = -0.319 (n = 3,476)lag -2: r = -0.298 (n = 3,587)lag -1: r = -0.281 (n = 3,659)lag +0: r = -0.265 (n = 3,659)lag +1: r = -0.222 (n = 3,529)lag +2: r = -0.214 (n = 3,461)lag +3: r = -0.207 (n = 3,393)lag +4: r = -0.203 (n = 3,303)lag +5: r = -0.194 (n = 3,234)lag +6: r = -0.210 (n = 3,167)lag +7: r = -0.201 (n = 3,069)lag +8: r = -0.204 (n = 3,002)lag +9: r = -0.209 (n = 2,941)lag +10: r = -0.212 (n = 2,883)

Same year (lag 0): -0.265. 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


births per woman
per 1,000 people		Years
Chad TCD6.030.152024, 2020
Somalia, Fed. Rep. SOM6.010.872024, 2019
Central African Republic CAF5.9512024, 2011
Niger NER5.930.282024, 2020
Mali MLI5.510.252024, 2018
Angola AGO5.050.752024, 2019
Burundi BDI4.790.692024, 2014
Afghanistan AFG4.760.352024, 2023
Mozambique MOZ4.690.742024, 2021
Tanzania TZA4.540.842024, 2022
Benin BEN4.480.432024, 2021
Sudan SDN4.260.662024, 2021
Cameroon CMR4.262.652024, 2016
Uganda UGA4.170.52024, 2010
Guinea GIN4.130.32024, 2011

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

Sources

Fertility rate

Fertility rate, total (births per woman)

World Bank · CC BY 4.0 · updated quarterly

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 2010–2024. 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 Fertility rate and Hospital beds

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

More links with Fertility rate or Hospital beds