placestats

Abortion rate (estimate) vs. Confidence in religious institutions

Holds up after adjusting for income

A country is not a person. Countries where more people are counted as belonging to this group also tend to differ on the other measure, and that is all. It does not follow that the people in the group are the people with the different score. Making that leap is called the ecological fallacy: reading a pattern across places as a fact about individual people. It is the most common misuse of this kind of data. Religion also varies strongly with region, history and national income, so much of what looks religious here is really those. That is what the adjusted figures are for. The religion shares are estimates for two years only, and the survey questions are asked in rounds that can be ten years apart.

Across 85 countries, Abortion rate (estimate) and Confidence in religious institutions rise and fall together at r = +0.46 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.28 (q = 0.0076, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a weak positive link remains. Caution: direction is not consistent across regions.

Comparing countries across the middle half of abortion rate (estimate), 11.4 to 32.7 per 1,000 women aged 15-49, confidence in religious institutions is 13.6% of respondents higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 7.73% of respondents.

Link before adjusting (r)+0.463p = 8.3e-6 · 85 countries
After adjusting for national income+0.285p = 0.009 · likely range [+0.07, +0.47]
p, allowing for regions0.000standard error 0.035 · 7 regions
Check for luck (q)0.008across 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
Confidence in religious institutions · % of respondentslink with income -0.57 · moderate

“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 →Confidence in religious institutions · % of respondents →580.37.91%99.8%Albania: 9.45 per 1,000 women aged 15-49, 52.7% of respondentsArgentina: 33.2 per 1,000 women aged 15-49, 57.9% of respondentsArmenia: 42.8 per 1,000 women aged 15-49, 70.4% of respondentsAustralia: 16.1 per 1,000 women aged 15-49, 31.3% of respondentsAzerbaijan: 71.9 per 1,000 women aged 15-49, 69.6% of respondentsBelgium: 7.78 per 1,000 women aged 15-49, 36.2% of respondentsBurkina Faso: 30.5 per 1,000 women aged 15-49, 77.4% of respondentsBangladesh: 35.3 per 1,000 women aged 15-49, 99.8% of respondentsBulgaria: 10.2 per 1,000 women aged 15-49, 35.1% of respondentsBosnia and Herzegovina: 11 per 1,000 women aged 15-49, 56.5% of respondentsBelarus: 10.5 per 1,000 women aged 15-49, 58.3% of respondentsBolivia: 37.8 per 1,000 women aged 15-49, 49% of respondentsBrazil: 32.3 per 1,000 women aged 15-49, 66.9% of respondentsCanada: 11.6 per 1,000 women aged 15-49, 39.6% of respondentsSwitzerland: 5.18 per 1,000 women aged 15-49, 33.7% of respondentsChile: 35.9 per 1,000 women aged 15-49, 44.6% of respondentsChina: 49 per 1,000 women aged 15-49, 20% of respondentsColombia: 27.1 per 1,000 women aged 15-49, 55.4% of respondentsCzechia: 6.86 per 1,000 women aged 15-49, 22.8% of respondentsGermany: 5.77 per 1,000 women aged 15-49, 31.5% of respondentsDenmark: 11.6 per 1,000 women aged 15-49, 59.1% of respondentsEcuador: 27.9 per 1,000 women aged 15-49, 75% of respondentsSpain: 8.73 per 1,000 women aged 15-49, 32.6% of respondentsEstonia: 15.9 per 1,000 women aged 15-49, 34% of respondentsEthiopia: 24.4 per 1,000 women aged 15-49, 92.2% of respondentsFinland: 8.09 per 1,000 women aged 15-49, 55% of respondentsFrance: 14.4 per 1,000 women aged 15-49, 38.9% of respondentsUnited Kingdom: 13.1 per 1,000 women aged 15-49, 36.9% of respondentsGeorgia: 80.3 per 1,000 women aged 15-49, 77.4% of respondentsGhana: 36.6 per 1,000 women aged 15-49, 89.3% of respondentsGreece: 15 per 1,000 women aged 15-49, 65.4% of respondentsGuatemala: 18.9 per 1,000 women aged 15-49, 70.5% of respondentsHong Kong SAR, China: 13 per 1,000 women aged 15-49, 53.2% of respondentsCroatia: 16.5 per 1,000 women aged 15-49, 37.2% of respondentsHaiti: 38.1 per 1,000 women aged 15-49, 9.28% of respondentsHungary: 13.6 per 1,000 women aged 15-49, 40.1% of respondentsIndonesia: 25 per 1,000 women aged 15-49, 98.3% of respondentsIndia: 48 per 1,000 women aged 15-49, 89.1% of respondentsIceland: 12.7 per 1,000 women aged 15-49, 47.3% of respondentsItaly: 18.9 per 1,000 women aged 15-49, 52.6% of respondentsJapan: 6 per 1,000 women aged 15-49, 7.91% of respondentsKazakhstan: 47 per 1,000 women aged 15-49, 79% of respondentsKenya: 42.7 per 1,000 women aged 15-49, 79.4% of respondentsKyrgyz Republic: 31.2 per 1,000 women aged 15-49, 77.6% of respondentsKorea, Rep.: 21 per 1,000 women aged 15-49, 51.7% of respondentsLithuania: 7.15 per 1,000 women aged 15-49, 68.1% of respondentsLatvia: 10.3 per 1,000 women aged 15-49, 47.9% of respondentsMoldova: 18.2 per 1,000 women aged 15-49, 77.3% of respondentsMaldives: 42 per 1,000 women aged 15-49, 75.6% of respondentsMexico: 30.6 per 1,000 women aged 15-49, 61.7% of respondentsNorth Macedonia: 14.3 per 1,000 women aged 15-49, 74.4% of respondentsMali: 22.5 per 1,000 women aged 15-49, 90% of respondentsMyanmar: 26 per 1,000 women aged 15-49, 84.1% of respondentsMontenegro: 5.89 per 1,000 women aged 15-49, 79.6% of respondentsMongolia: 21 per 1,000 women aged 15-49, 21.8% of respondentsNigeria: 32.7 per 1,000 women aged 15-49, 88.2% of respondentsNicaragua: 15.3 per 1,000 women aged 15-49, 67.3% of respondentsNetherlands: 7.15 per 1,000 women aged 15-49, 22.1% of respondentsNorway: 10.8 per 1,000 women aged 15-49, 50.2% of respondentsNew Zealand: 12 per 1,000 women aged 15-49, 35.9% of respondentsPakistan: 43.1 per 1,000 women aged 15-49, 97.2% of respondentsPeru: 42.4 per 1,000 women aged 15-49, 60.9% of respondentsPhilippines: 36 per 1,000 women aged 15-49, 92.2% of respondentsPoland: 10.5 per 1,000 women aged 15-49, 55.2% of respondentsPuerto Rico (US): 31.5 per 1,000 women aged 15-49, 68.2% of respondentsPortugal: 6.77 per 1,000 women aged 15-49, 59.6% of respondentsRomania: 31 per 1,000 women aged 15-49, 69.3% of respondentsRussian Federation: 45.7 per 1,000 women aged 15-49, 58.4% of respondentsRwanda: 27.8 per 1,000 women aged 15-49, 60.2% of respondentsSingapore: 5 per 1,000 women aged 15-49, 58.3% of respondentsSerbia: 12.7 per 1,000 women aged 15-49, 55.7% of respondentsSlovak Republic: 7.15 per 1,000 women aged 15-49, 49.8% of respondentsSlovenia: 8.13 per 1,000 women aged 15-49, 22.5% of respondentsSweden: 17.3 per 1,000 women aged 15-49, 47.4% of respondentsThailand: 25 per 1,000 women aged 15-49, 69.9% of respondentsTajikistan: 25.8 per 1,000 women aged 15-49, 76.4% of respondentsTrinidad and Tobago: 48.3 per 1,000 women aged 15-49, 65.3% of respondentsUkraine: 20.5 per 1,000 women aged 15-49, 65.9% of respondentsUruguay: 11.4 per 1,000 women aged 15-49, 37.4% of respondentsUnited States: 11.9 per 1,000 women aged 15-49, 53.1% of respondentsUzbekistan: 22.7 per 1,000 women aged 15-49, 86.7% of respondentsViet Nam: 64 per 1,000 women aged 15-49, 89.3% of respondentsSouth Africa: 29.7 per 1,000 women aged 15-49, 77% of respondentsZambia: 34.6 per 1,000 women aged 15-49, 86.3% of respondentsZimbabwe: 18.2 per 1,000 women aged 15-49, 68.3% of respondentsAZECHNCZEGEOHTIIDNJPNMLIMNENLDVNM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.4638.3e-685
By rank (Spearman), not adjusted+0.5391.0e-785
Standard (Pearson), adjusted for national income+0.2850.00985
By rank (Spearman), adjusted for national income+0.2160.04985

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 85 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: +0.178 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.255 (without VNM) to +0.349 (without CHN). 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: CHN (+0.064).

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 & Pacific13+0.13
Europe & Central Asia42+0.38
Latin America & Caribbean14-0.13

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 third29+0.15
Middle third28+0.28
Richest third28+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
Christians57+0.23
Muslims14+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
Never a European colony13+0.43
United Kingdom17+0.48

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 = +0.261 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 respondents		Years
Georgia GEO80.377.4%2019, 2022
Azerbaijan AZE71.969.6%2019, 2022
Viet Nam VNM6489.3%2019, 2022
China CHN4920%2019, 2022
Trinidad and Tobago TTO48.365.3%2019, 2014
India IND4889.1%2019, 2022
Kazakhstan KAZ4779%2019, 2022
Russian Federation RUS45.758.4%2019, 2022
Pakistan PAK43.197.2%2019, 2022
Armenia ARM42.870.4%2019, 2022
Kenya KEN42.779.4%2019, 2022
Peru PER42.460.9%2019, 2022
Maldives MDV4275.6%2019, 2022
Haiti HTI38.19.28%2019, 2014
Bolivia BOL37.849%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.
Haerpfer, C. et al., World Values Survey; EVS, European Values Study

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.

Confidence in religious institutions

Share with confidence in churches and religious organisations

World Values Survey Association and European Values Study · via Our World in Data · Free for non-commercial use with attribution · updated irregular (survey waves, roughly every 5 years)

"A great deal" or "quite a lot" of confidence, as against "not very much" or "none". Confidence in an institution is not belief in what it teaches. The gap between this and the importance of religion shows how far religious people trust their clergy. No "better" direction is set.

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2022. 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 Confidence in religious institutions

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

More links with Abortion rate (estimate) or Confidence in religious institutions