placestats

Abortion rate (estimate) vs. Slum share of urban population

Holds up after adjusting for income

Across 139 countries, Abortion rate (estimate) and Slum share of urban population rise and fall together at r = +0.42 (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 (q = 0.012, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a very weak positive link remains.

Comparing countries across the middle half of abortion rate (estimate), 15.3 to 36.4 per 1,000 women aged 15-49, slum share of urban population is worse by 15.5% of urban population at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 4.04% of urban population.

Link before adjusting (r)+0.418p = 3.2e-7 · 139 countries
After adjusting for national income+0.154p = 0.072 · likely range [-0.01, +0.31]
p, allowing for regions0.000standard error 0.022 · 7 regions
Check for luck (q)0.012across 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
Slum share of urban population · % of urban populationlink with income -0.78 · high

“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 →Slum share of urban population · % of urban population →580.30%92.5%Angola: 33.4 per 1,000 women aged 15-49, 62.7% of urban populationAlbania: 9.45 per 1,000 women aged 15-49, 2.7% of urban populationArgentina: 33.2 per 1,000 women aged 15-49, 14.5% of urban populationArmenia: 42.8 per 1,000 women aged 15-49, 8.39% of urban populationAustralia: 16.1 per 1,000 women aged 15-49, 0.035% of urban populationAzerbaijan: 71.9 per 1,000 women aged 15-49, 26.9% of urban populationBurundi: 25.6 per 1,000 women aged 15-49, 36.8% of urban populationBelgium: 7.78 per 1,000 women aged 15-49, 0% of urban populationBenin: 31.9 per 1,000 women aged 15-49, 64% of urban populationBurkina Faso: 30.5 per 1,000 women aged 15-49, 87.9% of urban populationBangladesh: 35.3 per 1,000 women aged 15-49, 51.5% of urban populationBulgaria: 10.2 per 1,000 women aged 15-49, 0.197% of urban populationBosnia and Herzegovina: 11 per 1,000 women aged 15-49, 0.313% of urban populationBelarus: 10.5 per 1,000 women aged 15-49, 0.004% of urban populationBelize: 31.8 per 1,000 women aged 15-49, 15.7% of urban populationBolivia: 37.8 per 1,000 women aged 15-49, 46.6% of urban populationBrazil: 32.3 per 1,000 women aged 15-49, 14.9% of urban populationBhutan: 32.1 per 1,000 women aged 15-49, 44.7% of urban populationBotswana: 30.7 per 1,000 women aged 15-49, 39.6% of urban populationCentral African Republic: 26.8 per 1,000 women aged 15-49, 68.9% of urban populationCanada: 11.6 per 1,000 women aged 15-49, 1.1% of urban populationSwitzerland: 5.18 per 1,000 women aged 15-49, 0% of urban populationChile: 35.9 per 1,000 women aged 15-49, 7.32% of urban populationChina: 49 per 1,000 women aged 15-49, 26.3% of urban populationCote d'Ivoire: 35.3 per 1,000 women aged 15-49, 48.3% of urban populationCameroon: 33.9 per 1,000 women aged 15-49, 32.7% of urban populationCongo, Dem. Rep.: 32.7 per 1,000 women aged 15-49, 78.4% of urban populationCongo, Rep.: 44.4 per 1,000 women aged 15-49, 75.3% of urban populationColombia: 27.1 per 1,000 women aged 15-49, 9.7% of urban populationComoros: 30.6 per 1,000 women aged 15-49, 48.5% of urban populationCabo Verde: 49.1 per 1,000 women aged 15-49, 46.4% of urban populationCosta Rica: 21.1 per 1,000 women aged 15-49, 3.55% of urban populationCzechia: 6.86 per 1,000 women aged 15-49, 0.0273% of urban populationGermany: 5.77 per 1,000 women aged 15-49, 0% of urban populationDjibouti: 20.6 per 1,000 women aged 15-49, 48.7% of urban populationDenmark: 11.6 per 1,000 women aged 15-49, 0% of urban populationDominican Republic: 36.6 per 1,000 women aged 15-49, 11.2% of urban populationEcuador: 27.9 per 1,000 women aged 15-49, 57.8% of urban populationSpain: 8.73 per 1,000 women aged 15-49, 0.046% of urban populationEstonia: 15.9 per 1,000 women aged 15-49, 0.345% of urban populationEthiopia: 24.4 per 1,000 women aged 15-49, 64.3% of urban populationFinland: 8.09 per 1,000 women aged 15-49, 0% of urban populationFrance: 14.4 per 1,000 women aged 15-49, 0% of urban populationGabon: 40.6 per 1,000 women aged 15-49, 38.8% of urban populationUnited Kingdom: 13.1 per 1,000 women aged 15-49, 0.163% of urban populationGeorgia: 80.3 per 1,000 women aged 15-49, 7.08% of urban populationGhana: 36.6 per 1,000 women aged 15-49, 33.5% of urban populationGuinea: 26.4 per 1,000 women aged 15-49, 44% of urban populationGambia, The: 16.4 per 1,000 women aged 15-49, 37.1% of urban populationGuinea-Bissau: 58.5 per 1,000 women aged 15-49, 59% of urban populationGreece: 15 per 1,000 women aged 15-49, 0.05% of urban populationGuatemala: 18.9 per 1,000 women aged 15-49, 37.6% of urban populationGuyana: 36.4 per 1,000 women aged 15-49, 11.3% of urban populationHonduras: 20.7 per 1,000 women aged 15-49, 31.5% of urban populationCroatia: 16.5 per 1,000 women aged 15-49, 0.527% of urban populationHaiti: 38.1 per 1,000 women aged 15-49, 51.1% of urban populationHungary: 13.6 per 1,000 women aged 15-49, 7.2% of urban populationIndonesia: 25 per 1,000 women aged 15-49, 19.4% of urban populationIndia: 48 per 1,000 women aged 15-49, 5.41% of urban populationIceland: 12.7 per 1,000 women aged 15-49, 0% of urban populationItaly: 18.9 per 1,000 women aged 15-49, 0.02% of urban populationJamaica: 38.1 per 1,000 women aged 15-49, 0.883% of urban populationJapan: 6 per 1,000 women aged 15-49, 2% of urban populationKazakhstan: 47 per 1,000 women aged 15-49, 0.794% of urban populationKenya: 42.7 per 1,000 women aged 15-49, 40.5% of urban populationKyrgyz Republic: 31.2 per 1,000 women aged 15-49, 2.44% of urban populationCambodia: 45 per 1,000 women aged 15-49, 42.3% of urban populationKorea, Rep.: 21 per 1,000 women aged 15-49, 4.5% of urban populationLao PDR: 34 per 1,000 women aged 15-49, 54.8% of urban populationLiberia: 42.3 per 1,000 women aged 15-49, 60.5% of urban populationSt. Lucia: 37.2 per 1,000 women aged 15-49, 0.441% of urban populationSri Lanka: 27.9 per 1,000 women aged 15-49, 44.7% of urban populationLesotho: 23.5 per 1,000 women aged 15-49, 25.6% of urban populationLithuania: 7.15 per 1,000 women aged 15-49, 0.509% of urban populationLatvia: 10.3 per 1,000 women aged 15-49, 0.593% of urban populationMoldova: 18.2 per 1,000 women aged 15-49, 6.5% of urban populationMadagascar: 59.9 per 1,000 women aged 15-49, 65.7% of urban populationMaldives: 42 per 1,000 women aged 15-49, 34.8% of urban populationMexico: 30.6 per 1,000 women aged 15-49, 17.6% of urban populationNorth Macedonia: 14.3 per 1,000 women aged 15-49, 0.278% of urban populationMali: 22.5 per 1,000 women aged 15-49, 92.5% of urban populationMyanmar: 26 per 1,000 women aged 15-49, 58.3% of urban populationMontenegro: 5.89 per 1,000 women aged 15-49, 8.77% of urban populationMongolia: 21 per 1,000 women aged 15-49, 17.9% of urban populationMozambique: 40.4 per 1,000 women aged 15-49, 55% of urban populationMauritania: 17 per 1,000 women aged 15-49, 58.6% of urban populationMalawi: 31.4 per 1,000 women aged 15-49, 38% of urban populationNamibia: 29.2 per 1,000 women aged 15-49, 41.4% of urban populationNiger: 15.2 per 1,000 women aged 15-49, 70.4% of urban populationNigeria: 32.7 per 1,000 women aged 15-49, 48.5% of urban populationNicaragua: 15.3 per 1,000 women aged 15-49, 5.52% of urban populationNetherlands: 7.15 per 1,000 women aged 15-49, 0% of urban populationNorway: 10.8 per 1,000 women aged 15-49, 0% of urban populationNepal: 41.3 per 1,000 women aged 15-49, 40.1% of urban populationNew Zealand: 12 per 1,000 women aged 15-49, 0% of urban populationPakistan: 43.1 per 1,000 women aged 15-49, 56% of urban populationPanama: 29.6 per 1,000 women aged 15-49, 16.3% of urban populationPeru: 42.4 per 1,000 women aged 15-49, 45.1% of urban populationPhilippines: 36 per 1,000 women aged 15-49, 35.9% of urban populationPapua New Guinea: 36.4 per 1,000 women aged 15-49, 22.3% of urban populationPoland: 10.5 per 1,000 women aged 15-49, 4.22% of urban populationPortugal: 6.77 per 1,000 women aged 15-49, 0.059% of urban populationParaguay: 34 per 1,000 women aged 15-49, 15.1% of urban populationRomania: 31 per 1,000 women aged 15-49, 2.52% of urban populationRussian Federation: 45.7 per 1,000 women aged 15-49, 2.62% of urban populationRwanda: 27.8 per 1,000 women aged 15-49, 38.3% of urban populationSenegal: 15.3 per 1,000 women aged 15-49, 46.4% of urban populationSingapore: 5 per 1,000 women aged 15-49, 0% of urban populationSolomon Islands: 32.1 per 1,000 women aged 15-49, 1.95% of urban populationSierra Leone: 45.4 per 1,000 women aged 15-49, 49.3% of urban populationEl Salvador: 24 per 1,000 women aged 15-49, 16.5% of urban populationSomalia, Fed. Rep.: 28.7 per 1,000 women aged 15-49, 48.7% of urban populationSerbia: 12.7 per 1,000 women aged 15-49, 1.42% of urban populationSao Tome and Principe: 38.5 per 1,000 women aged 15-49, 82.4% of urban populationSuriname: 31 per 1,000 women aged 15-49, 15.8% of urban populationSlovak Republic: 7.15 per 1,000 women aged 15-49, 0.066% of urban populationSlovenia: 8.13 per 1,000 women aged 15-49, 0.527% of urban populationSweden: 17.3 per 1,000 women aged 15-49, 0.336% of urban populationEswatini: 29.3 per 1,000 women aged 15-49, 17% of urban populationChad: 17.4 per 1,000 women aged 15-49, 82% of urban populationTogo: 32.1 per 1,000 women aged 15-49, 38.5% of urban populationThailand: 25 per 1,000 women aged 15-49, 2% of urban populationTajikistan: 25.8 per 1,000 women aged 15-49, 0.05% of urban populationTurkmenistan: 18.9 per 1,000 women aged 15-49, 8.38% of urban populationTimor-Leste: 34 per 1,000 women aged 15-49, 33.9% of urban populationTonga: 25 per 1,000 women aged 15-49, 0.308% of urban populationTrinidad and Tobago: 48.3 per 1,000 women aged 15-49, 8.63% of urban populationTanzania: 37.5 per 1,000 women aged 15-49, 70.1% of urban populationUganda: 43 per 1,000 women aged 15-49, 52.7% of urban populationUkraine: 20.5 per 1,000 women aged 15-49, 1.1% of urban populationUruguay: 11.4 per 1,000 women aged 15-49, 1.3% of urban populationUnited States: 11.9 per 1,000 women aged 15-49, 0.0932% of urban populationUzbekistan: 22.7 per 1,000 women aged 15-49, 7.1% of urban populationViet Nam: 64 per 1,000 women aged 15-49, 32.5% of urban populationVanuatu: 39.2 per 1,000 women aged 15-49, 3.06% of urban populationSamoa: 42.8 per 1,000 women aged 15-49, 34.6% of urban populationSouth Africa: 29.7 per 1,000 women aged 15-49, 24.2% of urban populationZambia: 34.6 per 1,000 women aged 15-49, 48.3% of urban populationZimbabwe: 18.2 per 1,000 women aged 15-49, 54.9% of urban populationAZECHEDEUGEOGNBKAZMDGMLINERSGPTCD

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.4183.2e-7139
By rank (Spearman), not adjusted+0.5722.0e-13139
Standard (Pearson), adjusted for national income+0.1540.072139
By rank (Spearman), adjusted for national income+0.3288.7e-5139

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 139 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: +0.264 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.139 (without BDI) to +0.181 (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: GEO (+0.028).

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+0.40
Europe & Central Asia43+0.57
Latin America & Caribbean24+0.22
Sub-Saharan Africa42+0.06

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+0.04
Middle third46+0.36
Richest third46+0.44

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+0.22
Muslims27+0.20

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
France21-0.17
Never a European colony16+0.24
Spain17+0.50
United Kingdom37+0.12

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 = +0.173 after dropping 2 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 urban population		Years
Georgia GEO80.37.08%2019, 2022
Azerbaijan AZE71.926.9%2019, 2012
Viet Nam VNM6432.5%2019, 2022
Madagascar MDG59.965.7%2019, 2022
Guinea-Bissau GNB58.559%2019, 2022
Cabo Verde CPV49.146.4%2019, 2022
China CHN4926.3%2019, 2022
Trinidad and Tobago TTO48.38.63%2019, 2022
India IND485.41%2019
Kazakhstan KAZ470.794%2019, 2022
Russian Federation RUS45.72.62%2019, 2022
Sierra Leone SLE45.449.3%2019, 2022
Cambodia KHM4542.3%2019, 2022
Congo, Rep. COG44.475.3%2019, 2022
Pakistan PAK43.156%2019, 2022

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.

Slum share of urban population

Population living in slums (% of urban population)

UN-Habitat · CC BY 4.0 · updated quarterly

How this was computed

Data used: most recent value in 2010-2025; values come from 2012–2022. 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 Slum share of urban population

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

More links with Abortion rate (estimate) or Slum share of urban population