placestats

Infrastructure score vs. Unintended pregnancies ending in abortion

Holds up after adjusting for income

Across 142 countries, Infrastructure score and Unintended pregnancies ending in abortion rise and fall together at r = +0.23 (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 = +0.30, q = 0.033, allowing for the many pairs tested). Caution: direction is not consistent across regions.

Comparing countries across the middle half of unintended pregnancies ending in abortion, 31.4% to 58.5% of unintended pregnancies, infrastructure score is better by 0.26 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.126 typical gaps.

Link before adjusting (r)+0.228p = 0.006 · 142 countries
After adjusting for national income+0.298p = 0.000 · likely range [+0.14, +0.44]
p, allowing for regions0.016standard error 0.090 · 7 regions
Check for luck (q)0.033across 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.

Infrastructure score · typical gaps (standard deviations)link with income +0.90 · proxy
Unintended pregnancies ending in abortion · % of unintended pregnancieslink with income +0.12 · independent

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

Every country as a dot

Infrastructure score · typical gaps (standard deviations) →Unintended pregnancies ending in abortion · % of unintended pregnancies →-1.011.7219.7%86.1%Angola: -0.152 typical gaps (standard deviations), 28.1% of unintended pregnanciesAlbania: 1.14 typical gaps (standard deviations), 59.2% of unintended pregnanciesArgentina: 1.25 typical gaps (standard deviations), 48.4% of unintended pregnanciesArmenia: 1.09 typical gaps (standard deviations), 81.8% of unintended pregnanciesAustralia: 1.5 typical gaps (standard deviations), 43.1% of unintended pregnanciesAzerbaijan: 1.19 typical gaps (standard deviations), 77.6% of unintended pregnanciesBurundi: -0.835 typical gaps (standard deviations), 26.2% of unintended pregnanciesBelgium: 1.64 typical gaps (standard deviations), 37.1% of unintended pregnanciesBenin: 0.00537 typical gaps (standard deviations), 36.9% of unintended pregnanciesBurkina Faso: -0.245 typical gaps (standard deviations), 40.6% of unintended pregnanciesBangladesh: 0.649 typical gaps (standard deviations), 60.1% of unintended pregnanciesBulgaria: 1.25 typical gaps (standard deviations), 35.7% of unintended pregnanciesBosnia and Herzegovina: 1.29 typical gaps (standard deviations), 57.3% of unintended pregnanciesBelarus: 1.48 typical gaps (standard deviations), 56% of unintended pregnanciesBelize: 0.573 typical gaps (standard deviations), 45.2% of unintended pregnanciesBolivia: 0.886 typical gaps (standard deviations), 36.3% of unintended pregnanciesBrazil: 1.18 typical gaps (standard deviations), 48.4% of unintended pregnanciesBarbados: 1.31 typical gaps (standard deviations), 58% of unintended pregnanciesBhutan: 0.847 typical gaps (standard deviations), 67.9% of unintended pregnanciesBotswana: 0.5 typical gaps (standard deviations), 32.2% of unintended pregnanciesCentral African Republic: -1.01 typical gaps (standard deviations), 30% of unintended pregnanciesCanada: 1.56 typical gaps (standard deviations), 36.8% of unintended pregnanciesSwitzerland: 1.7 typical gaps (standard deviations), 25.5% of unintended pregnanciesChile: 1.25 typical gaps (standard deviations), 52.5% of unintended pregnanciesChina: 1.66 typical gaps (standard deviations), 77.9% of unintended pregnanciesCote d'Ivoire: 0.207 typical gaps (standard deviations), 36.7% of unintended pregnanciesCameroon: 0.557 typical gaps (standard deviations), 40.7% of unintended pregnanciesCongo, Dem. Rep.: -0.672 typical gaps (standard deviations), 27.9% of unintended pregnanciesCongo, Rep.: 0.312 typical gaps (standard deviations), 42.6% of unintended pregnanciesColombia: 1.01 typical gaps (standard deviations), 43.2% of unintended pregnanciesComoros: 0.259 typical gaps (standard deviations), 32.4% of unintended pregnanciesCabo Verde: 0.806 typical gaps (standard deviations), 48.6% of unintended pregnanciesCosta Rica: 1.19 typical gaps (standard deviations), 41% of unintended pregnanciesCzechia: 1.48 typical gaps (standard deviations), 19.7% of unintended pregnanciesGermany: 1.65 typical gaps (standard deviations), 27.1% of unintended pregnanciesDjibouti: 0.0105 typical gaps (standard deviations), 41.4% of unintended pregnanciesDenmark: 1.65 typical gaps (standard deviations), 38.9% of unintended pregnanciesDominican Republic: 0.956 typical gaps (standard deviations), 44% of unintended pregnanciesEcuador: 0.989 typical gaps (standard deviations), 35.1% of unintended pregnanciesSpain: 1.55 typical gaps (standard deviations), 43.1% of unintended pregnanciesEstonia: 1.45 typical gaps (standard deviations), 41.7% of unintended pregnanciesEthiopia: -0.309 typical gaps (standard deviations), 31% of unintended pregnanciesFinland: 1.48 typical gaps (standard deviations), 24.8% of unintended pregnanciesFrance: 1.7 typical gaps (standard deviations), 49.5% of unintended pregnanciesGabon: 0.665 typical gaps (standard deviations), 36.8% of unintended pregnanciesUnited Kingdom: 1.6 typical gaps (standard deviations), 36.2% of unintended pregnanciesGeorgia: 1.29 typical gaps (standard deviations), 86.1% of unintended pregnanciesGhana: 0.59 typical gaps (standard deviations), 35.9% of unintended pregnanciesGuinea: 0.156 typical gaps (standard deviations), 38.1% of unintended pregnanciesGambia, The: 0.215 typical gaps (standard deviations), 31.1% of unintended pregnanciesGuinea-Bissau: -0.158 typical gaps (standard deviations), 58.5% of unintended pregnanciesGreece: 1.57 typical gaps (standard deviations), 45.8% of unintended pregnanciesGuatemala: 0.576 typical gaps (standard deviations), 30.1% of unintended pregnanciesGuyana: 0.809 typical gaps (standard deviations), 47.5% of unintended pregnanciesHong Kong SAR, China: 1.57 typical gaps (standard deviations), 46.1% of unintended pregnanciesHonduras: 0.417 typical gaps (standard deviations), 30.6% of unintended pregnanciesCroatia: 1.28 typical gaps (standard deviations), 49.9% of unintended pregnanciesHaiti: -0.312 typical gaps (standard deviations), 35.5% of unintended pregnanciesHungary: 1.5 typical gaps (standard deviations), 49.4% of unintended pregnanciesIndonesia: 0.742 typical gaps (standard deviations), 63% of unintended pregnanciesIndia: 0.527 typical gaps (standard deviations), 77.1% of unintended pregnanciesIceland: 1.53 typical gaps (standard deviations), 39.1% of unintended pregnanciesItaly: 1.36 typical gaps (standard deviations), 67.1% of unintended pregnanciesJamaica: 1.06 typical gaps (standard deviations), 43.9% of unintended pregnanciesJapan: 1.45 typical gaps (standard deviations), 30.1% of unintended pregnanciesKazakhstan: 1.09 typical gaps (standard deviations), 82.1% of unintended pregnanciesKenya: 0.22 typical gaps (standard deviations), 38% of unintended pregnanciesKyrgyz Republic: 0.943 typical gaps (standard deviations), 79.2% of unintended pregnanciesCambodia: 0.689 typical gaps (standard deviations), 65.3% of unintended pregnanciesKorea, Rep.: 1.72 typical gaps (standard deviations), 61.9% of unintended pregnanciesLao PDR: 0.399 typical gaps (standard deviations), 68.3% of unintended pregnanciesLiberia: -0.767 typical gaps (standard deviations), 40.4% of unintended pregnanciesSt. Lucia: 0.881 typical gaps (standard deviations), 54.6% of unintended pregnanciesSri Lanka: 0.669 typical gaps (standard deviations), 72.3% of unintended pregnanciesLesotho: -0.0187 typical gaps (standard deviations), 23.9% of unintended pregnanciesLithuania: 1.29 typical gaps (standard deviations), 27.7% of unintended pregnanciesLatvia: 1.28 typical gaps (standard deviations), 30.2% of unintended pregnanciesMoldova: 1.23 typical gaps (standard deviations), 70.6% of unintended pregnanciesMadagascar: -0.434 typical gaps (standard deviations), 62.8% of unintended pregnanciesMaldives: 1.11 typical gaps (standard deviations), 70.5% of unintended pregnanciesMexico: 1.13 typical gaps (standard deviations), 50.9% of unintended pregnanciesNorth Macedonia: 1.36 typical gaps (standard deviations), 63.4% of unintended pregnanciesMali: -0.495 typical gaps (standard deviations), 33.5% of unintended pregnanciesMyanmar: 0.298 typical gaps (standard deviations), 74.2% of unintended pregnanciesMontenegro: 1.37 typical gaps (standard deviations), 54.2% of unintended pregnanciesMongolia: 1.03 typical gaps (standard deviations), 65.7% of unintended pregnanciesMozambique: -0.592 typical gaps (standard deviations), 46.7% of unintended pregnanciesMauritania: 0.0018 typical gaps (standard deviations), 25.4% of unintended pregnanciesMalawi: -0.672 typical gaps (standard deviations), 27.4% of unintended pregnanciesNamibia: 0.203 typical gaps (standard deviations), 27.9% of unintended pregnanciesNiger: -0.7 typical gaps (standard deviations), 31.3% of unintended pregnanciesNigeria: -0.0861 typical gaps (standard deviations), 48.2% of unintended pregnanciesNicaragua: 0.574 typical gaps (standard deviations), 27.5% of unintended pregnanciesNetherlands: 1.63 typical gaps (standard deviations), 40.8% of unintended pregnanciesNorway: 1.68 typical gaps (standard deviations), 31.7% of unintended pregnanciesNepal: 0.616 typical gaps (standard deviations), 69.4% of unintended pregnanciesNew Zealand: 1.51 typical gaps (standard deviations), 29.3% of unintended pregnanciesPakistan: 0.386 typical gaps (standard deviations), 60.9% of unintended pregnanciesPanama: 0.927 typical gaps (standard deviations), 41.3% of unintended pregnanciesPeru: 0.907 typical gaps (standard deviations), 47.5% of unintended pregnanciesPhilippines: 0.696 typical gaps (standard deviations), 50.5% of unintended pregnanciesPapua New Guinea: -0.611 typical gaps (standard deviations), 46.3% of unintended pregnanciesPoland: 1.24 typical gaps (standard deviations), 36.6% of unintended pregnanciesPuerto Rico (US): 1.14 typical gaps (standard deviations), 58.3% of unintended pregnanciesPortugal: 1.6 typical gaps (standard deviations), 32.4% of unintended pregnanciesParaguay: 0.928 typical gaps (standard deviations), 51% of unintended pregnanciesRomania: 1.45 typical gaps (standard deviations), 71.2% of unintended pregnanciesRussian Federation: 1.32 typical gaps (standard deviations), 71.8% of unintended pregnanciesRwanda: 0.0662 typical gaps (standard deviations), 28.7% of unintended pregnanciesSenegal: 0.482 typical gaps (standard deviations), 25.1% of unintended pregnanciesSingapore: 1.33 typical gaps (standard deviations), 27.5% of unintended pregnanciesSolomon Islands: 0.0941 typical gaps (standard deviations), 28% of unintended pregnanciesSierra Leone: -0.336 typical gaps (standard deviations), 51.5% of unintended pregnanciesEl Salvador: 0.822 typical gaps (standard deviations), 41.5% of unintended pregnanciesSomalia, Fed. Rep.: -0.395 typical gaps (standard deviations), 29.2% of unintended pregnanciesSerbia: 1.38 typical gaps (standard deviations), 60.8% of unintended pregnanciesSao Tome and Principe: 0.187 typical gaps (standard deviations), 29.6% of unintended pregnanciesSuriname: 0.901 typical gaps (standard deviations), 46.5% of unintended pregnanciesSlovak Republic: 1.4 typical gaps (standard deviations), 26.2% of unintended pregnanciesSlovenia: 1.42 typical gaps (standard deviations), 24.4% of unintended pregnanciesSweden: 1.57 typical gaps (standard deviations), 48.3% of unintended pregnanciesEswatini: 0.534 typical gaps (standard deviations), 26.5% of unintended pregnanciesChad: -0.72 typical gaps (standard deviations), 29.5% of unintended pregnanciesTogo: -0.0274 typical gaps (standard deviations), 32.2% of unintended pregnanciesThailand: 1.06 typical gaps (standard deviations), 64.4% of unintended pregnanciesTajikistan: 0.389 typical gaps (standard deviations), 71% of unintended pregnanciesTurkmenistan: 0.294 typical gaps (standard deviations), 83.4% of unintended pregnanciesTimor-Leste: 0.389 typical gaps (standard deviations), 67.8% of unintended pregnanciesTonga: 0.595 typical gaps (standard deviations), 52% of unintended pregnanciesTrinidad and Tobago: 1.22 typical gaps (standard deviations), 58% of unintended pregnanciesTanzania: -0.0741 typical gaps (standard deviations), 35.9% of unintended pregnanciesUganda: -0.319 typical gaps (standard deviations), 29.7% of unintended pregnanciesUkraine: 0.97 typical gaps (standard deviations), 75.9% of unintended pregnanciesUruguay: 1.41 typical gaps (standard deviations), 27.6% of unintended pregnanciesUnited States: 1.53 typical gaps (standard deviations), 34.2% of unintended pregnanciesUzbekistan: 1.42 typical gaps (standard deviations), 80.2% of unintended pregnanciesViet Nam: 1.17 typical gaps (standard deviations), 74.5% of unintended pregnanciesVanuatu: -0.0444 typical gaps (standard deviations), 45.4% of unintended pregnanciesSamoa: 0.0591 typical gaps (standard deviations), 64.5% of unintended pregnanciesSouth Africa: 0.709 typical gaps (standard deviations), 36.6% of unintended pregnanciesZambia: -0.161 typical gaps (standard deviations), 28.2% of unintended pregnanciesZimbabwe: 0.0863 typical gaps (standard deviations), 24.8% of unintended pregnanciesBDICAFCHECHNCZEDEUGEOMDGMMRMWITKMUZB

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.2280.006142
By rank (Spearman), not adjusted+0.1810.031142
Standard (Pearson), adjusted for national income+0.2980.000142
By rank (Spearman), adjusted for national income+0.1940.021142

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 142 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: -0.070 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.266 (without UZB) to +0.350 (without TKM). 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: TKM (+0.053).

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 & Pacific21+0.39
Europe & Central Asia43-0.14
Latin America & Caribbean26+0.13
Sub-Saharan Africa42+0.10

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 third48+0.32
Middle third47+0.24
Richest third47-0.16

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
Christians96+0.26
Muslims27+0.25

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+0.34
Never a European colony16+0.32
Spain17+0.08
United Kingdom38+0.14

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 = +0.298 after dropping 0 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


typical gaps (standard deviations)
% of unintended pregnancies		Years
Korea, Rep. KOR1.7261.9%2024, 2019
Switzerland CHE1.725.5%2024, 2019
France FRA1.749.5%2024, 2019
Norway NOR1.6831.7%2024, 2019
China CHN1.6677.9%2024, 2019
Denmark DNK1.6538.9%2024, 2019
Germany DEU1.6527.1%2024, 2019
Belgium BEL1.6437.1%2024, 2019
Netherlands NLD1.6340.8%2024, 2019
Portugal PRT1.632.4%2024, 2019
United Kingdom GBR1.636.2%2024, 2019
Greece GRC1.5745.8%2024, 2019
Sweden SWE1.5748.3%2024, 2019
Hong Kong SAR, China HKG1.5746.1%2024, 2019
Canada CAN1.5636.8%2024, 2019

wdi
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.

Sources

Infrastructure score

Infrastructure score

PlaceStats · via PlaceStats · Derived work; each member keeps its own licence · updated recomputed with the panel

The average of 5 measures from 1 publisher. Each measure is first put on a common scale: 0 is the average country in an average year, and 1 is a typical gap between countries (a standard deviation). Each is turned so that higher is better. Measures are averaged within each publisher first, so a publisher with many measures does not count for more. Members: Electricity access, Slum share of urban population, Mobile subscriptions, Fixed broadband, Internet users.

Unintended pregnancies ending in abortion

Share of unintended pregnancies ending in abortion (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)

Of the unintended pregnancies in the abortion rate's model, the share that ended in abortion, averaged over 2015-2019 (Guttmacher Institute). The rest ended in a birth or a miscarriage. Like the other two, it is an estimate with a range. No "better" direction is set.

How this was computed

Data used: most recent value in 2010-2025; values come from 2019–2024. 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 14,952 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Infrastructure score and Unintended pregnancies ending in abortion

This page shows that two measures go together. It does not show that Infrastructure score changes Unintended pregnancies ending in abortion, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Infrastructure score or Unintended pregnancies ending in abortion