placestats

Skilled birth attendance vs. Tertiary enrollment

Fades after adjusting for income

Across 162 countries, Skilled birth attendance and Tertiary enrollment rise and fall together at r = +0.57 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.15, which could easily be chance (q = 0.12, 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 tertiary enrollment, 15.9% to 70.5% gross, skilled birth attendance is better by 13.9% of births at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 3.82% of births.

Link before adjusting (r)+0.570p = 2.6e-15 · 162 countries
After adjusting for national income+0.146p = 0.065 · likely range [-0.01, +0.29]
p, allowing for regions0.033standard error 0.053 · 7 regions
Check for luck (q)0.118across 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.

Skilled birth attendance · % of birthslink with income +0.69 · high
Tertiary enrollment · % grosslink with income +0.75 · 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

Skilled birth attendance · % of births →Tertiary enrollment · % gross →40.3%100%2.57%165%Afghanistan: 61.8% of births, 10.9% grossAngola: 49.6% of births, 9.95% grossAlbania: 99.8% of births, 84.1% grossAndorra: 100% of births, 67.7% grossUnited Arab Emirates: 99.2% of births, 63.7% grossArgentina: 98.8% of births, 108% grossArmenia: 99.8% of births, 52.8% grossAntigua and Barbuda: 99% of births, 25.1% grossAustralia: 96% of births, 108% grossAustria: 98.1% of births, 92.6% grossAzerbaijan: 99.9% of births, 41.3% grossBurundi: 76.5% of births, 6.38% grossBenin: 78.1% of births, 10.2% grossBurkina Faso: 79.8% of births, 10% grossBangladesh: 59% of births, 23.7% grossBulgaria: 94.5% of births, 69.5% grossBahrain: 99.6% of births, 58.4% grossBosnia and Herzegovina: 99.9% of births, 45.5% grossBelarus: 99.9% of births, 70.1% grossBelize: 94.6% of births, 24.8% grossBermuda: 99.4% of births, 17.3% grossBrazil: 98.4% of births, 69.7% grossBarbados: 98.4% of births, 50.8% grossBrunei Darussalam: 99.6% of births, 36.4% grossBhutan: 98.9% of births, 13% grossBotswana: 99.8% of births, 21.4% grossCentral African Republic: 40.3% of births, 2.78% grossCanada: 98% of births, 76.3% grossChile: 99.8% of births, 110% grossChina: 99.9% of births, 76.9% grossCote d'Ivoire: 84% of births, 12.3% grossCameroon: 69% of births, 16.7% grossCongo, Dem. Rep.: 85.2% of births, 6.38% grossCongo, Rep.: 91.2% of births, 10.4% grossColombia: 98.8% of births, 59.3% grossComoros: 82.2% of births, 18.8% grossCabo Verde: 97.3% of births, 24.3% grossCosta Rica: 99% of births, 55% grossCyprus: 99.3% of births, 121% grossCzechia: 99.8% of births, 66.7% grossGermany: 96.2% of births, 76.7% grossDjibouti: 87.4% of births, 5.16% grossDenmark: 95.3% of births, 79% grossDominican Republic: 99.2% of births, 57.7% grossAlgeria: 98.8% of births, 54.4% grossEcuador: 99.4% of births, 67.9% grossEgypt, Arab Rep.: 97.1% of births, 38% grossSpain: 99.9% of births, 93.8% grossEstonia: 99.6% of births, 65.7% grossEthiopia: 49.8% of births, 5.92% grossFinland: 99.5% of births, 110% grossFiji: 99.8% of births, 75% grossFrance: 98.2% of births, 71.5% grossGeorgia: 99.8% of births, 89.5% grossGhana: 78.9% of births, 21.3% grossGuinea: 55.3% of births, 10.9% grossGambia, The: 83.8% of births, 13.5% grossGreece: 99.9% of births, 165% grossGrenada: 100% of births, 100% grossGuatemala: 69.6% of births, 27.3% grossGuyana: 97.6% of births, 26.4% grossHonduras: 94.1% of births, 23.3% grossCroatia: 99.9% of births, 81.2% grossHungary: 99.7% of births, 60.5% grossIndonesia: 94.7% of births, 44.9% grossIndia: 89.4% of births, 34.4% grossIreland: 99.7% of births, 77.6% grossIran, Islamic Rep.: 99% of births, 58.7% grossIceland: 97.4% of births, 76.5% grossItaly: 99.8% of births, 75.9% grossJamaica: 99.7% of births, 26.2% grossJordan: 99.7% of births, 35.9% grossJapan: 99.8% of births, 64.5% grossKazakhstan: 99.9% of births, 52.9% grossKenya: 70.2% of births, 10.4% grossKyrgyz Republic: 100% of births, 53.9% grossCambodia: 98.7% of births, 21.4% grossKiribati: 91.9% of births, 4.96% grossSt. Kitts and Nevis: 100% of births, 93.9% grossKorea, Rep.: 100% of births, 112% grossKuwait: 99.9% of births, 51.9% grossLao PDR: 64.4% of births, 14.9% grossLiberia: 84.4% of births, 10.8% grossSt. Lucia: 100% of births, 15% grossSri Lanka: 99.5% of births, 20.7% grossLesotho: 86.6% of births, 9.94% grossLithuania: 100% of births, 75.6% grossLatvia: 99.9% of births, 82.9% grossMorocco: 86.6% of births, 48.2% grossMoldova: 99.6% of births, 74.7% grossMadagascar: 45.8% of births, 6.15% grossMaldives: 99.5% of births, 48.5% grossMexico: 96.6% of births, 48.2% grossMarshall Islands: 92.4% of births, 37.7% grossNorth Macedonia: 100% of births, 55% grossMali: 67.3% of births, 5.13% grossMalta: 99.8% of births, 80.5% grossMyanmar: 60.2% of births, 20.4% grossMontenegro: 98.8% of births, 55.2% grossMongolia: 99.3% of births, 69% grossMozambique: 73% of births, 7.46% grossMauritania: 70.4% of births, 5.97% grossMauritius: 99.7% of births, 45.8% grossMalawi: 96.4% of births, 2.71% grossMalaysia: 99.6% of births, 38.5% grossNamibia: 88.2% of births, 26.1% grossNiger: 43.7% of births, 4.15% grossNigeria: 50.7% of births, 9.74% grossNicaragua: 94.1% of births, 30.4% grossNorway: 99.2% of births, 95.5% grossNepal: 77.2% of births, 21.3% grossNew Zealand: 96.5% of births, 77.2% grossOman: 99.9% of births, 42.2% grossPakistan: 68% of births, 10.9% grossPanama: 95% of births, 53.7% grossPeru: 94.9% of births, 71.2% grossPhilippines: 84.4% of births, 47.4% grossPalau: 97.2% of births, 71.8% grossPoland: 99.6% of births, 80.9% grossPortugal: 98.6% of births, 77.7% grossParaguay: 92.2% of births, 37.6% grossWest Bank and Gaza: 99.7% of births, 44.5% grossQatar: 100% of births, 43% grossRomania: 93% of births, 55.2% grossRussian Federation: 99.6% of births, 60.4% grossRwanda: 94.2% of births, 9.41% grossSaudi Arabia: 94.8% of births, 83.9% grossSudan: 77.7% of births, 15.9% grossSenegal: 74.5% of births, 15.3% grossSingapore: 99.6% of births, 97.3% grossEl Salvador: 99.9% of births, 32.8% grossSerbia: 99.9% of births, 70.6% grossSao Tome and Principe: 96.8% of births, 12.8% grossSuriname: 98.4% of births, 2.57% grossSlovak Republic: 98% of births, 54.5% grossSlovenia: 99.8% of births, 80.1% grossEswatini: 88.3% of births, 6.44% grossSeychelles: 99.5% of births, 14.5% grossTurks and Caicos Islands: 100% of births, 25.3% grossChad: 47.2% of births, 4.4% grossTogo: 69.4% of births, 14.9% grossThailand: 99.1% of births, 49.1% grossTajikistan: 94.8% of births, 35.6% grossTurkmenistan: 100% of births, 20.4% grossTimor-Leste: 56.7% of births, 31% grossTonga: 98.3% of births, 42.9% grossTrinidad and Tobago: 100% of births, 23.8% grossTunisia: 99.5% of births, 38.1% grossTurkiye: 97% of births, 106% grossTuvalu: 99.5% of births, 19.4% grossTanzania: 63.5% of births, 4.02% grossUganda: 74.2% of births, 4.62% grossUkraine: 99.9% of births, 87.2% grossUruguay: 100% of births, 80% grossUnited States: 99.1% of births, 79.4% grossUzbekistan: 99% of births, 59.8% grossSt. Vincent and the Grenadines: 98.6% of births, 41.5% grossViet Nam: 96.1% of births, 37.6% grossSamoa: 88.9% of births, 16% grossSouth Africa: 96.7% of births, 23.5% grossZambia: 80.4% of births, 3.96% grossZimbabwe: 86% of births, 7.75% grossCAFCYPGRCKORLCAMDGMWINERSUR

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5702.6e-15162
By rank (Spearman), not adjusted+0.6331.5e-19162
Standard (Pearson), adjusted for national income+0.1460.065162
By rank (Spearman), adjusted for national income+0.2410.002162

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 162 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: +0.424 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.128 (without AGO) to +0.159 (without CAF). 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: AGO (-0.018).

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+0.08
Europe & Central Asia43+0.12
Latin America & Caribbean28+0.18
Middle East, North Africa, Afghanistan & Pakistan17+0.33
Sub-Saharan Africa41+0.30

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 third54+0.36
Middle third54+0.12
Richest third54-0.03

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
Christians94+0.09
Muslims42+0.41

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+0.16
Never a European colony21+0.14
Spain17+0.28
United Kingdom53+0.11

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 = +0.157 after dropping 19 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 33years. 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 = -0.122, 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 skilled birth attendance moved did not tend to see their tertiary enrollment move with it.

Across countries (adjusted)+0.146for comparison
Within countries+0.236each country vs itself
…and vs the same year elsewhere-0.122q = 0.111 · 124 countries
Year-on-year changes-0.001q = 0.984
The direction flips. Comparing each country only with itself gives +0.24. Also taking out what happened to the whole world each year gives -0.12. So the first figure was picking up a trend both measures share with worldwide progress, not a link between them.

1,706 country-years (one country in one year), 124 countries, 1990–2022, about 14 years each on average. Share of the variation that happens within countries over time: 19% for Skilled birth attendance, 13% for Tertiary enrollment. 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 Tertiary enrollment trails Skilled birth attendance →lag -10: r = -0.265 (n = 936)lag -9: r = -0.257 (n = 1,017)lag -8: r = -0.234 (n = 1,053)lag -7: r = -0.250 (n = 1,161)lag -6: r = -0.237 (n = 1,207)lag -5: r = -0.234 (n = 1,297)lag -4: r = -0.195 (n = 1,376)lag -3: r = -0.158 (n = 1,442)lag -2: r = -0.166 (n = 1,540)lag -1: r = -0.131 (n = 1,606)lag +0: r = -0.122 (n = 1,706)lag +1: r = -0.104 (n = 1,702)lag +2: r = -0.107 (n = 1,738)lag +3: r = -0.090 (n = 1,777)lag +4: r = -0.092 (n = 1,769)lag +5: r = -0.080 (n = 1,763)lag +6: r = -0.070 (n = 1,722)lag +7: r = -0.060 (n = 1,679)lag +8: r = -0.041 (n = 1,646)lag +9: r = -0.017 (n = 1,601)lag +10: r = -0.001 (n = 1,558)

Same year (lag 0): -0.122. 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 births
% gross		Years
Uruguay URY100%80%2020, 2023
Trinidad and Tobago TTO100%23.8%2017, 2024
Turkmenistan TKM100%20.4%2019, 2024
Turks and Caicos Islands TCA100%25.3%2020, 2023
Qatar QAT100%43%2019, 2024
North Macedonia MKD100%55%2021, 2023
Lithuania LTU100%75.6%2021, 2024
St. Lucia LCA100%15%2019, 2023
Korea, Rep. KOR100%112%2015, 2024
St. Kitts and Nevis KNA100%93.9%2020, 2015
Kyrgyz Republic KGZ100%53.9%2020, 2025
Grenada GRD100%100%2017, 2018
Andorra AND100%67.7%2017, 2024
Ukraine UKR99.9%87.2%2014, 2024
Serbia SRB99.9%70.6%2019, 2024

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

Sources

Skilled birth attendance

Births attended by skilled health staff (% of total)

UNICEF and WHO · CC BY 4.0 · updated quarterly

Based on surveys, so a country reports it every few years rather than yearly.

Tertiary enrollment

School enrollment, tertiary (% gross)

UNESCO Institute for Statistics · 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 Skilled birth attendance and Tertiary enrollment

This page shows that two measures go together. It does not show that Skilled birth attendance changes Tertiary enrollment, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Skilled birth attendance or Tertiary enrollment