placestats

Abortion rate (estimate) vs. Women in parliament

Holds up after adjusting for income

Across 140 countries, Abortion rate (estimate) and Women in parliament rise and fall together at r = -0.35 (on a scale from −1 to +1, where 0 means no link). It holds up almost unchanged when only countries with similar income (GDP per person) are compared (r = -0.24, q = 0.031, allowing for the many pairs tested). Caution: direction is not consistent across regions.

Comparing countries across the middle half of abortion rate (estimate), 15.3 to 36.5 per 1,000 women aged 15-49, women in parliament is worse by 6.36% of seats at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 4.69% of seats.

Link before adjusting (r)-0.346p = 2.9e-5 · 140 countries
After adjusting for national income-0.244p = 0.004 · likely range [-0.39, -0.08]
p, allowing for regions0.002standard error 0.048 · 7 regions
Check for luck (q)0.031across 14,952 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.

Abortion rate (estimate) · per 1,000 women aged 15-49link with income -0.50 · moderate
Women in parliament · % of seatslink with income +0.28 · independent

“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.

Every country as a dot

Abortion rate (estimate) · per 1,000 women aged 15-49 →Women in parliament · % of seats →580.31.92%63.8%Angola: 33.4 per 1,000 women aged 15-49, 39.1% of seatsAlbania: 9.45 per 1,000 women aged 15-49, 35% of seatsArgentina: 33.2 per 1,000 women aged 15-49, 41.2% of seatsArmenia: 42.8 per 1,000 women aged 15-49, 38.3% of seatsAustralia: 16.1 per 1,000 women aged 15-49, 46% of seatsAzerbaijan: 71.9 per 1,000 women aged 15-49, 20.8% of seatsBurundi: 25.6 per 1,000 women aged 15-49, 39.6% of seatsBelgium: 7.78 per 1,000 women aged 15-49, 41.3% of seatsBenin: 31.9 per 1,000 women aged 15-49, 26.6% of seatsBurkina Faso: 30.5 per 1,000 women aged 15-49, 18.3% of seatsBangladesh: 35.3 per 1,000 women aged 15-49, 20.9% of seatsBulgaria: 10.2 per 1,000 women aged 15-49, 25% of seatsBosnia and Herzegovina: 11 per 1,000 women aged 15-49, 19% of seatsBelarus: 10.5 per 1,000 women aged 15-49, 33.9% of seatsBelize: 31.8 per 1,000 women aged 15-49, 12.5% of seatsBolivia: 37.8 per 1,000 women aged 15-49, 50.8% of seatsBrazil: 32.3 per 1,000 women aged 15-49, 18.1% of seatsBarbados: 44.6 per 1,000 women aged 15-49, 26.7% of seatsBhutan: 32.1 per 1,000 women aged 15-49, 4.26% of seatsBotswana: 30.7 per 1,000 women aged 15-49, 8.96% of seatsCentral African Republic: 26.8 per 1,000 women aged 15-49, 11.4% of seatsCanada: 11.6 per 1,000 women aged 15-49, 30.3% of seatsSwitzerland: 5.18 per 1,000 women aged 15-49, 39% of seatsChile: 35.9 per 1,000 women aged 15-49, 33.5% of seatsChina: 49 per 1,000 women aged 15-49, 26.5% of seatsCote d'Ivoire: 35.3 per 1,000 women aged 15-49, 13.4% of seatsCameroon: 33.9 per 1,000 women aged 15-49, 33.9% of seatsCongo, Dem. Rep.: 32.7 per 1,000 women aged 15-49, 12.8% of seatsCongo, Rep.: 44.4 per 1,000 women aged 15-49, 14.6% of seatsColombia: 27.1 per 1,000 women aged 15-49, 29.4% of seatsComoros: 30.6 per 1,000 women aged 15-49, 18.2% of seatsCabo Verde: 49.1 per 1,000 women aged 15-49, 44.4% of seatsCosta Rica: 21.1 per 1,000 women aged 15-49, 49.1% of seatsCzechia: 6.86 per 1,000 women aged 15-49, 33.5% of seatsGermany: 5.77 per 1,000 women aged 15-49, 32.4% of seatsDjibouti: 20.6 per 1,000 women aged 15-49, 26.2% of seatsDenmark: 11.6 per 1,000 women aged 15-49, 43.6% of seatsDominican Republic: 36.6 per 1,000 women aged 15-49, 37.4% of seatsEcuador: 27.9 per 1,000 women aged 15-49, 45% of seatsSpain: 8.73 per 1,000 women aged 15-49, 44.3% of seatsEstonia: 15.9 per 1,000 women aged 15-49, 28.7% of seatsEthiopia: 24.4 per 1,000 women aged 15-49, 41.9% of seatsFinland: 8.09 per 1,000 women aged 15-49, 45.5% of seatsFrance: 14.4 per 1,000 women aged 15-49, 36.2% of seatsGabon: 40.6 per 1,000 women aged 15-49, 21.6% of seatsUnited Kingdom: 13.1 per 1,000 women aged 15-49, 40.5% of seatsGeorgia: 80.3 per 1,000 women aged 15-49, 16.8% of seatsGhana: 36.6 per 1,000 women aged 15-49, 14.5% of seatsGuinea: 26.4 per 1,000 women aged 15-49, 29.6% of seatsGambia, The: 16.4 per 1,000 women aged 15-49, 8.62% of seatsGuinea-Bissau: 58.5 per 1,000 women aged 15-49, 9.8% of seatsGreece: 15 per 1,000 women aged 15-49, 22.9% of seatsGuatemala: 18.9 per 1,000 women aged 15-49, 20% of seatsGuyana: 36.4 per 1,000 women aged 15-49, 36.1% of seatsHonduras: 20.7 per 1,000 women aged 15-49, 29.7% of seatsCroatia: 16.5 per 1,000 women aged 15-49, 33.1% of seatsHaiti: 38.1 per 1,000 women aged 15-49, 2.54% of seatsHungary: 13.6 per 1,000 women aged 15-49, 15.6% of seatsIndonesia: 25 per 1,000 women aged 15-49, 21.9% of seatsIndia: 48 per 1,000 women aged 15-49, 13.8% of seatsIceland: 12.7 per 1,000 women aged 15-49, 46% of seatsItaly: 18.9 per 1,000 women aged 15-49, 32.8% of seatsJamaica: 38.1 per 1,000 women aged 15-49, 30.2% of seatsJapan: 6 per 1,000 women aged 15-49, 15.7% of seatsKazakhstan: 47 per 1,000 women aged 15-49, 18.4% of seatsKenya: 42.7 per 1,000 women aged 15-49, 23.4% of seatsKyrgyz Republic: 31.2 per 1,000 women aged 15-49, 33.3% of seatsCambodia: 45 per 1,000 women aged 15-49, 13.6% of seatsKorea, Rep.: 21 per 1,000 women aged 15-49, 20.3% of seatsLao PDR: 34 per 1,000 women aged 15-49, 22% of seatsLiberia: 42.3 per 1,000 women aged 15-49, 11% of seatsSt. Lucia: 37.2 per 1,000 women aged 15-49, 10.5% of seatsSri Lanka: 27.9 per 1,000 women aged 15-49, 9.78% of seatsLesotho: 23.5 per 1,000 women aged 15-49, 25% of seatsLithuania: 7.15 per 1,000 women aged 15-49, 28.4% of seatsLatvia: 10.3 per 1,000 women aged 15-49, 31% of seatsMoldova: 18.2 per 1,000 women aged 15-49, 39.6% of seatsMadagascar: 59.9 per 1,000 women aged 15-49, 14.1% of seatsMaldives: 42 per 1,000 women aged 15-49, 3.23% of seatsMexico: 30.6 per 1,000 women aged 15-49, 50.2% of seatsNorth Macedonia: 14.3 per 1,000 women aged 15-49, 39.2% of seatsMali: 22.5 per 1,000 women aged 15-49, 30.1% of seatsMyanmar: 26 per 1,000 women aged 15-49, 15.3% of seatsMontenegro: 5.89 per 1,000 women aged 15-49, 27.2% of seatsMongolia: 21 per 1,000 women aged 15-49, 25.4% of seatsMozambique: 40.4 per 1,000 women aged 15-49, 38.3% of seatsMauritania: 17 per 1,000 women aged 15-49, 23.3% of seatsMalawi: 31.4 per 1,000 women aged 15-49, 21.4% of seatsNamibia: 29.2 per 1,000 women aged 15-49, 42.3% of seatsNiger: 15.2 per 1,000 women aged 15-49, 19.6% of seatsNigeria: 32.7 per 1,000 women aged 15-49, 4.21% of seatsNicaragua: 15.3 per 1,000 women aged 15-49, 54.9% of seatsNetherlands: 7.15 per 1,000 women aged 15-49, 43.3% of seatsNorway: 10.8 per 1,000 women aged 15-49, 40.2% of seatsNepal: 41.3 per 1,000 women aged 15-49, 33.1% of seatsNew Zealand: 12 per 1,000 women aged 15-49, 45.5% of seatsPakistan: 43.1 per 1,000 women aged 15-49, 17% of seatsPanama: 29.6 per 1,000 women aged 15-49, 21.7% of seatsPeru: 42.4 per 1,000 women aged 15-49, 41.5% of seatsPhilippines: 36 per 1,000 women aged 15-49, 28.3% of seatsPapua New Guinea: 36.4 per 1,000 women aged 15-49, 2.7% of seatsPoland: 10.5 per 1,000 women aged 15-49, 31.3% of seatsPortugal: 6.77 per 1,000 women aged 15-49, 35.7% of seatsParaguay: 34 per 1,000 women aged 15-49, 23.8% of seatsRomania: 31 per 1,000 women aged 15-49, 22.4% of seatsRussian Federation: 45.7 per 1,000 women aged 15-49, 16.4% of seatsRwanda: 27.8 per 1,000 women aged 15-49, 63.8% of seatsSenegal: 15.3 per 1,000 women aged 15-49, 41.2% of seatsSingapore: 5 per 1,000 women aged 15-49, 32.3% of seatsSolomon Islands: 32.1 per 1,000 women aged 15-49, 6% of seatsSierra Leone: 45.4 per 1,000 women aged 15-49, 29.5% of seatsEl Salvador: 24 per 1,000 women aged 15-49, 31.7% of seatsSomalia, Fed. Rep.: 28.7 per 1,000 women aged 15-49, 19% of seatsSerbia: 12.7 per 1,000 women aged 15-49, 37.2% of seatsSao Tome and Principe: 38.5 per 1,000 women aged 15-49, 14.5% of seatsSuriname: 31 per 1,000 women aged 15-49, 31.4% of seatsSlovak Republic: 7.15 per 1,000 women aged 15-49, 23.3% of seatsSlovenia: 8.13 per 1,000 women aged 15-49, 35.6% of seatsSweden: 17.3 per 1,000 women aged 15-49, 45% of seatsEswatini: 29.3 per 1,000 women aged 15-49, 21.6% of seatsChad: 17.4 per 1,000 women aged 15-49, 33.5% of seatsTogo: 32.1 per 1,000 women aged 15-49, 15% of seatsThailand: 25 per 1,000 women aged 15-49, 19.6% of seatsTajikistan: 25.8 per 1,000 women aged 15-49, 28.6% of seatsTurkmenistan: 18.9 per 1,000 women aged 15-49, 25.6% of seatsTimor-Leste: 34 per 1,000 women aged 15-49, 35.4% of seatsTonga: 25 per 1,000 women aged 15-49, 3.85% of seatsTrinidad and Tobago: 48.3 per 1,000 women aged 15-49, 23.8% of seatsTanzania: 37.5 per 1,000 women aged 15-49, 39.5% of seatsUganda: 43 per 1,000 women aged 15-49, 34.1% of seatsUkraine: 20.5 per 1,000 women aged 15-49, 21.2% of seatsUruguay: 11.4 per 1,000 women aged 15-49, 31.3% of seatsUnited States: 11.9 per 1,000 women aged 15-49, 28.9% of seatsUzbekistan: 22.7 per 1,000 women aged 15-49, 38% of seatsViet Nam: 64 per 1,000 women aged 15-49, 31.4% of seatsVanuatu: 39.2 per 1,000 women aged 15-49, 1.92% of seatsSamoa: 42.8 per 1,000 women aged 15-49, 9.8% of seatsSouth Africa: 29.7 per 1,000 women aged 15-49, 44.9% of seatsZambia: 34.6 per 1,000 women aged 15-49, 15% of seatsZimbabwe: 18.2 per 1,000 women aged 15-49, 30.1% of seatsAZECPVFINGEOGMBGNBJPNNICRWATONVNM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.3462.9e-5140
By rank (Spearman), not adjusted-0.3678.3e-6140
Standard (Pearson), adjusted for national income-0.2440.004140
By rank (Spearman), adjusted for national income-0.2340.006140

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 140 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: +0.102 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.266 (without CPV) to -0.227 (without GEO). 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: CPV (-0.022).

Fragile: this link may not hold up.
  • direction is not consistent across regions

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+0.17
Europe & Central Asia43-0.41
Latin America & Caribbean25-0.27
Sub-Saharan Africa42-0.19

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 third47-0.27
Middle third46-0.10
Richest third47-0.32

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
Christians95-0.21
Muslims27-0.39

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
France21-0.45
Never a European colony16-0.22
Spain17+0.07
United Kingdom38-0.18

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 = -0.215 after dropping 3 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 0years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Not enough history inside each country to look at this over time. That needs countries measured for several years in a row, and at least one of these measures is measured too rarely.

The data


per 1,000 women aged 15-49
% of seats		Years
Georgia GEO80.316.8%2019, 2025
Azerbaijan AZE71.920.8%2019, 2025
Viet Nam VNM6431.4%2019, 2025
Madagascar MDG59.914.1%2019, 2025
Guinea-Bissau GNB58.59.8%2019, 2024
Cabo Verde CPV49.144.4%2019, 2025
China CHN4926.5%2019, 2025
Trinidad and Tobago TTO48.323.8%2019, 2025
India IND4813.8%2019, 2025
Kazakhstan KAZ4718.4%2019, 2025
Russian Federation RUS45.716.4%2019, 2025
Sierra Leone SLE45.429.5%2019, 2025
Cambodia KHM4513.6%2019, 2025
Barbados BRB44.626.7%2019, 2025
Congo, Rep. COG44.414.6%2019, 2025

Bearak, J. M., Popinchalk, A., Beavin, C. et al. (2022), 'Country-specific estimates of unintended pregnancy and abortion incidence: a global comparative analysis of levels in 2015-2019', BMJ Global Health 7(3), e007151. Guttmacher Institute. Supplementary appendix, tables A3-A5.
World Bank, World Development Indicators

Sources

Abortion rate (estimate)

Abortions per 1,000 women aged 15-49 (model estimate, 2015-2019)

Guttmacher Institute (Bearak et al. 2022, BMJ Global Health) · CC BY-NC 4.0 · updated one edition (2015-2019 estimates, published 2022)

The Guttmacher Institute's estimate of all abortions, legal or not, per 1,000 women aged 15 to 49 (women of childbearing age), averaged over 2015-2019. Where a country has good counts, the estimate stays close to them. Where it does not, including most countries where abortion is banned, it is worked out by a statistical model from surveys, births, birth control use and similar countries. Only 75 of the 166 countries with any data had counts reliable enough to use directly, so for many countries this is an informed estimate with a wide range: Georgia's is 80, but it could be anywhere from 46 to 133. The official count of legal abortions is shown separately. No "better" direction is set.

Women in parliament

Proportion of seats held by women in national parliaments (%)

Inter-Parliamentary Union · CC BY 4.0 · updated quarterly

How this was computed

Data used: most recent value in 2010-2025; values come from 2019–2025. 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 14,952 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Abortion rate (estimate) and Women in parliament

This page shows that two measures go together. It does not show that Abortion rate (estimate) changes Women in parliament, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Abortion rate (estimate) or Women in parliament