placestats

Free and fair elections vs. Skilled birth attendance

Fades after adjusting for income

Across 158 countries, Free and fair elections and Skilled birth attendance rise and fall together at r = +0.51 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.21, which could easily be chance (q = 0.48, 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 free and fair elections, 0.216 to 0.86 points, skilled birth attendance is better by 16% of births at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 5.61% of births.

Link before adjusting (r)+0.512p = 6.2e-12 · 158 countries
After adjusting for national income+0.211p = 0.008 · likely range [+0.06, +0.36]
p, allowing for regions0.273standard error 0.175 · 7 regions
Check for luck (q)0.477across 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.

Free and fair elections · index (0-1)link with income +0.61 · high
Skilled birth attendance · % of birthslink with income +0.69 · 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

Free and fair elections · index (0-1) →Skilled birth attendance · % of births →00.96631.9%100%Afghanistan: 0 index (0-1), 61.8% of birthsAngola: 0.293 index (0-1), 49.6% of birthsAlbania: 0.467 index (0-1), 99.8% of birthsUnited Arab Emirates: 0.543 index (0-1), 99.2% of birthsArgentina: 0.878 index (0-1), 98.8% of birthsArmenia: 0.673 index (0-1), 99.8% of birthsAustralia: 0.962 index (0-1), 96% of birthsAustria: 0.938 index (0-1), 98.1% of birthsAzerbaijan: 0.111 index (0-1), 99.9% of birthsBurundi: 0.107 index (0-1), 76.5% of birthsBenin: 0.638 index (0-1), 78.1% of birthsBurkina Faso: 0 index (0-1), 79.8% of birthsBangladesh: 0 index (0-1), 59% of birthsBulgaria: 0.64 index (0-1), 94.5% of birthsBahrain: 0.274 index (0-1), 99.6% of birthsBosnia and Herzegovina: 0.511 index (0-1), 99.9% of birthsBelarus: 0.194 index (0-1), 99.9% of birthsBolivia: 0.765 index (0-1), 81.1% of birthsBrazil: 0.838 index (0-1), 98.4% of birthsBarbados: 0.875 index (0-1), 98.4% of birthsBhutan: 0.865 index (0-1), 98.9% of birthsBotswana: 0.803 index (0-1), 99.8% of birthsCentral African Republic: 0.123 index (0-1), 40.3% of birthsCanada: 0.944 index (0-1), 98% of birthsChile: 0.956 index (0-1), 99.8% of birthsChina: 0 index (0-1), 99.9% of birthsCote d'Ivoire: 0.333 index (0-1), 84% of birthsCameroon: 0.12 index (0-1), 69% of birthsCongo, Dem. Rep.: 0.18 index (0-1), 85.2% of birthsCongo, Rep.: 0.076 index (0-1), 91.2% of birthsColombia: 0.756 index (0-1), 98.8% of birthsComoros: 0.183 index (0-1), 82.2% of birthsCabo Verde: 0.836 index (0-1), 97.3% of birthsCosta Rica: 0.944 index (0-1), 99% of birthsCyprus: 0.909 index (0-1), 99.3% of birthsCzechia: 0.94 index (0-1), 99.8% of birthsGermany: 0.957 index (0-1), 96.2% of birthsDjibouti: 0.167 index (0-1), 87.4% of birthsDenmark: 0.961 index (0-1), 95.3% of birthsDominican Republic: 0.768 index (0-1), 99.2% of birthsAlgeria: 0.307 index (0-1), 98.8% of birthsEcuador: 0.827 index (0-1), 99.4% of birthsEgypt, Arab Rep.: 0.137 index (0-1), 97.1% of birthsSpain: 0.956 index (0-1), 99.9% of birthsEstonia: 0.952 index (0-1), 99.6% of birthsEthiopia: 0.324 index (0-1), 49.8% of birthsFinland: 0.961 index (0-1), 99.5% of birthsFiji: 0.54 index (0-1), 99.8% of birthsFrance: 0.941 index (0-1), 98.2% of birthsGabon: 0.186 index (0-1), 89.3% of birthsGeorgia: 0.32 index (0-1), 99.8% of birthsGhana: 0.709 index (0-1), 78.9% of birthsGuinea: 0.002 index (0-1), 55.3% of birthsGambia, The: 0.777 index (0-1), 83.8% of birthsGuinea-Bissau: 0 index (0-1), 53.8% of birthsEquatorial Guinea: 0.078 index (0-1), 68.3% of birthsGreece: 0.944 index (0-1), 99.9% of birthsGuatemala: 0.666 index (0-1), 69.6% of birthsGuyana: 0.489 index (0-1), 97.6% of birthsHonduras: 0.351 index (0-1), 94.1% of birthsCroatia: 0.875 index (0-1), 99.9% of birthsHaiti: 0 index (0-1), 41.6% of birthsHungary: 0.597 index (0-1), 99.7% of birthsIndonesia: 0.518 index (0-1), 94.7% of birthsIndia: 0.495 index (0-1), 89.4% of birthsIreland: 0.945 index (0-1), 99.7% of birthsIran, Islamic Rep.: 0.235 index (0-1), 99% of birthsIraq: 0.372 index (0-1), 95.6% of birthsIceland: 0.929 index (0-1), 97.4% of birthsItaly: 0.945 index (0-1), 99.8% of birthsJamaica: 0.884 index (0-1), 99.7% of birthsJordan: 0.592 index (0-1), 99.7% of birthsJapan: 0.937 index (0-1), 99.8% of birthsKazakhstan: 0.339 index (0-1), 99.9% of birthsKenya: 0.493 index (0-1), 70.2% of birthsKyrgyz Republic: 0.426 index (0-1), 100% of birthsCambodia: 0.092 index (0-1), 98.7% of birthsKorea, Rep.: 0.935 index (0-1), 100% of birthsKuwait: 0 index (0-1), 99.9% of birthsLao PDR: 0.236 index (0-1), 64.4% of birthsLiberia: 0.592 index (0-1), 84.4% of birthsLibya: 0 index (0-1), 99.9% of birthsSri Lanka: 0.914 index (0-1), 99.5% of birthsLesotho: 0.785 index (0-1), 86.6% of birthsLithuania: 0.882 index (0-1), 100% of birthsLatvia: 0.92 index (0-1), 99.9% of birthsMorocco: 0.455 index (0-1), 86.6% of birthsMoldova: 0.662 index (0-1), 99.6% of birthsMadagascar: 0.183 index (0-1), 45.8% of birthsMaldives: 0.643 index (0-1), 99.5% of birthsMexico: 0.545 index (0-1), 96.6% of birthsNorth Macedonia: 0.701 index (0-1), 100% of birthsMali: 0 index (0-1), 67.3% of birthsMalta: 0.903 index (0-1), 99.8% of birthsMyanmar: 0 index (0-1), 60.2% of birthsMontenegro: 0.608 index (0-1), 98.8% of birthsMongolia: 0.586 index (0-1), 99.3% of birthsMozambique: 0.089 index (0-1), 73% of birthsMauritania: 0.288 index (0-1), 70.4% of birthsMauritius: 0.865 index (0-1), 99.7% of birthsMalawi: 0.596 index (0-1), 96.4% of birthsMalaysia: 0.598 index (0-1), 99.6% of birthsNamibia: 0.604 index (0-1), 88.2% of birthsNiger: 0 index (0-1), 43.7% of birthsNigeria: 0.355 index (0-1), 50.7% of birthsNicaragua: 0.137 index (0-1), 94.1% of birthsNorway: 0.966 index (0-1), 99.2% of birthsNepal: 0.693 index (0-1), 77.2% of birthsNew Zealand: 0.954 index (0-1), 96.5% of birthsOman: 0.689 index (0-1), 99.9% of birthsPakistan: 0.174 index (0-1), 68% of birthsPanama: 0.84 index (0-1), 95% of birthsPeru: 0.861 index (0-1), 94.9% of birthsPhilippines: 0.271 index (0-1), 84.4% of birthsPapua New Guinea: 0.27 index (0-1), 56.4% of birthsPoland: 0.825 index (0-1), 99.6% of birthsPortugal: 0.94 index (0-1), 98.6% of birthsParaguay: 0.633 index (0-1), 92.2% of birthsQatar: 0 index (0-1), 100% of birthsRomania: 0.658 index (0-1), 93% of birthsRussian Federation: 0.135 index (0-1), 99.6% of birthsRwanda: 0.227 index (0-1), 94.2% of birthsSaudi Arabia: 0 index (0-1), 94.8% of birthsSudan: 0 index (0-1), 77.7% of birthsSenegal: 0.701 index (0-1), 74.5% of birthsSingapore: 0.782 index (0-1), 99.6% of birthsSolomon Islands: 0.748 index (0-1), 86.2% of birthsSierra Leone: 0.319 index (0-1), 86.9% of birthsEl Salvador: 0.307 index (0-1), 99.9% of birthsSomalia, Fed. Rep.: 0 index (0-1), 31.9% of birthsSerbia: 0.212 index (0-1), 99.9% of birthsSao Tome and Principe: 0.753 index (0-1), 96.8% of birthsSuriname: 0.864 index (0-1), 98.4% of birthsSlovak Republic: 0.938 index (0-1), 98% of birthsSlovenia: 0.916 index (0-1), 99.8% of birthsEswatini: 0.376 index (0-1), 88.3% of birthsSeychelles: 0.884 index (0-1), 99.5% of birthsChad: 0.079 index (0-1), 47.2% of birthsTogo: 0.309 index (0-1), 69.4% of birthsThailand: 0.457 index (0-1), 99.1% of birthsTajikistan: 0.094 index (0-1), 94.8% of birthsTurkmenistan: 0.071 index (0-1), 100% of birthsTimor-Leste: 0.857 index (0-1), 56.7% of birthsTrinidad and Tobago: 0.872 index (0-1), 100% of birthsTunisia: 0.445 index (0-1), 99.5% of birthsTurkiye: 0.417 index (0-1), 97% of birthsTanzania: 0.364 index (0-1), 63.5% of birthsUganda: 0.129 index (0-1), 74.2% of birthsUkraine: 0.604 index (0-1), 99.9% of birthsUruguay: 0.947 index (0-1), 100% of birthsUnited States: 0.902 index (0-1), 99.1% of birthsUzbekistan: 0.304 index (0-1), 99% of birthsViet Nam: 0.527 index (0-1), 96.1% of birthsVanuatu: 0.853 index (0-1), 89.4% of birthsKosovo: 0.699 index (0-1), 99% of birthsSouth Africa: 0.849 index (0-1), 96.7% of birthsZambia: 0.461 index (0-1), 80.4% of birthsZimbabwe: 0.171 index (0-1), 86% of birthsCHLCHNESPFINHTIKWTNERNGAQATSOMTLS

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5126.2e-12158
By rank (Spearman), not adjusted+0.4175.0e-8158
Standard (Pearson), adjusted for national income+0.2110.008158
By rank (Spearman), adjusted for national income+0.0070.931158

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 158 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: +0.301 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.192 (without MWI) to +0.237 (without TLS). 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: TLS (+0.026).

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 & Pacific20+0.08
Europe & Central Asia43-0.03
Latin America & Caribbean23+0.26
Middle East, North Africa, Afghanistan & Pakistan18+0.27
Sub-Saharan Africa46+0.47

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 third53+0.34
Middle third52+0.22
Richest third53+0.04

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+0.25
Muslims46+0.34

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
France23+0.15
Never a European colony21+0.01
Spain19+0.24
United Kingdom48+0.42

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 = +0.134 after dropping 15 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 = +0.123, 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 free and fair elections moved did not tend to see their skilled birth attendance move with it.

Across countries (adjusted)+0.211for comparison
Within countries+0.185each country vs itself
…and vs the same year elsewhere+0.123q = 0.302 · 150 countries
Year-on-year changes-0.021q = 0.624

2,544 country-years (one country in one year), 150 countries, 1990–2022, about 17 years each on average. Share of the variation that happens within countries over time: 13% for Free and fair elections, 13% for Skilled birth attendance. 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

0.20−0.2-100+10years Skilled birth attendance trails Free and fair elections →lag -10: r = 0.004 (n = 2,111)lag -9: r = -0.030 (n = 2,215)lag -8: r = -0.021 (n = 2,300)lag -7: r = 0.033 (n = 2,392)lag -6: r = 0.055 (n = 2,472)lag -5: r = 0.073 (n = 2,516)lag -4: r = 0.112 (n = 2,541)lag -3: r = 0.114 (n = 2,544)lag -2: r = 0.136 (n = 2,544)lag -1: r = 0.149 (n = 2,544)lag +0: r = 0.123 (n = 2,544)lag +1: r = 0.124 (n = 2,490)lag +2: r = 0.133 (n = 2,443)lag +3: r = 0.136 (n = 2,391)lag +4: r = 0.147 (n = 2,330)lag +5: r = 0.119 (n = 2,276)lag +6: r = 0.096 (n = 2,207)lag +7: r = 0.104 (n = 2,139)lag +8: r = 0.103 (n = 2,056)lag +9: r = 0.070 (n = 1,981)lag +10: r = 0.056 (n = 1,896)

Same year (lag 0): +0.123. 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


index (0-1)

% of births
Years
Norway NOR0.96699.2%2025, 2021
Australia AUS0.96296%2025, 2020
Finland FIN0.96199.5%2025, 2021
Denmark DNK0.96195.3%2025, 2018
Germany DEU0.95796.2%2025, 2019
Spain ESP0.95699.9%2025, 2020
Chile CHL0.95699.8%2025, 2019
New Zealand NZL0.95496.5%2025, 2019
Estonia EST0.95299.6%2025, 2020
Uruguay URY0.947100%2025, 2020
Italy ITA0.94599.8%2025, 2020
Ireland IRL0.94599.7%2025, 2017
Greece GRC0.94499.9%2025, 2018
Costa Rica CRI0.94499%2025, 2019
Canada CAN0.94498%2025, 2020

Coppedge, M. et al., V-Dem Dataset, Varieties of Democracy (V-Dem) Project
World Bank, World Development Indicators

Sources

Free and fair elections

Free and fair elections index

V-Dem Institute, University of Gothenburg · via Our World in Data · CC BY 4.0 · updated annual

Whether elections are run without voter-registration fraud, widespread irregularities, government threats against the opposition, vote buying or election violence. This asks a narrower question than whether a country is a democracy, and one that is easier to answer. A state can run clean elections while barring the opposition from standing. It can also run dirty elections and still change government. It is the clean-elections part of the electoral democracy index. So its pair with that index, and with liberal and participatory democracy, is built from the same numbers and flagged as such.

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.

How this was computed

Data used: most recent value in 2010-2025; values come from 2011–2025. 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 Free and fair elections and Skilled birth attendance

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

More links with Free and fair elections or Skilled birth attendance