placestats

Researchers vs. Unintended pregnancy rate

Fades after adjusting for income

Across 106 countries, Researchers and Unintended pregnancy rate rise and fall together at r = -0.60 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.18, which could easily be chance (q = 0.49, 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 unintended pregnancy rate, 31.4 to 79.7 per 1,000 women aged 15-49, researchers is worse by 2,438 per million people at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 708 per million people.

Link before adjusting (r)-0.599p = 1.1e-11 · 106 countries
After adjusting for national income-0.184p = 0.061 · likely range [-0.36, +0.01]
p, allowing for regions0.366standard error 0.188 · 7 regions
Check for luck (q)0.490across 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.

Researchers · per million peoplelink with income +0.85 · proxy
Unintended pregnancy rate · per 1,000 women aged 15-49link 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

Researchers · per million people →Unintended pregnancy rate · per 1,000 women aged 15-49 →1.459,47210.9145Angola: 18.9 per million people, 120 per 1,000 women aged 15-49Albania: 429 per million people, 16 per 1,000 women aged 15-49Argentina: 1,313 per million people, 69 per 1,000 women aged 15-49Armenia: 942 per million people, 52.6 per 1,000 women aged 15-49Australia: 4,569 per million people, 37.4 per 1,000 women aged 15-49Azerbaijan: 1,663 per million people, 92.9 per 1,000 women aged 15-49Burundi: 22.5 per million people, 98.1 per 1,000 women aged 15-49Belgium: 5,990 per million people, 21 per 1,000 women aged 15-49Burkina Faso: 46.6 per million people, 75.2 per 1,000 women aged 15-49Bulgaria: 2,401 per million people, 28.6 per 1,000 women aged 15-49Bosnia and Herzegovina: 705 per million people, 20 per 1,000 women aged 15-49Belarus: 1,568 per million people, 18.7 per 1,000 women aged 15-49Bolivia: 63.1 per million people, 105 per 1,000 women aged 15-49Brazil: 903 per million people, 67.2 per 1,000 women aged 15-49Bhutan: 236 per million people, 47.5 per 1,000 women aged 15-49Botswana: 180 per million people, 96.8 per 1,000 women aged 15-49Canada: 5,624 per million people, 31.5 per 1,000 women aged 15-49Switzerland: 6,108 per million people, 20.3 per 1,000 women aged 15-49Chile: 707 per million people, 70 per 1,000 women aged 15-49China: 2,107 per million people, 64.8 per 1,000 women aged 15-49Congo, Dem. Rep.: 10.1 per million people, 117 per 1,000 women aged 15-49Congo, Rep.: 127 per million people, 106 per 1,000 women aged 15-49Colombia: 90.2 per million people, 62.7 per 1,000 women aged 15-49Cabo Verde: 125 per million people, 102 per 1,000 women aged 15-49Costa Rica: 508 per million people, 51.8 per 1,000 women aged 15-49Czechia: 4,505 per million people, 34.9 per 1,000 women aged 15-49Germany: 5,926 per million people, 21.3 per 1,000 women aged 15-49Denmark: 8,838 per million people, 29.8 per 1,000 women aged 15-49Dominican Republic: 20 per million people, 83.7 per 1,000 women aged 15-49Ecuador: 400 per million people, 79.7 per 1,000 women aged 15-49Spain: 3,654 per million people, 20.3 per 1,000 women aged 15-49Estonia: 4,800 per million people, 38.1 per 1,000 women aged 15-49Ethiopia: 89 per million people, 79.5 per 1,000 women aged 15-49Finland: 8,315 per million people, 32.6 per 1,000 women aged 15-49France: 5,369 per million people, 29 per 1,000 women aged 15-49United Kingdom: 4,473 per million people, 36.2 per 1,000 women aged 15-49Georgia: 1,896 per million people, 93.6 per 1,000 women aged 15-49Ghana: 87.5 per million people, 102 per 1,000 women aged 15-49Gambia, The: 50.9 per million people, 53.7 per 1,000 women aged 15-49Greece: 5,283 per million people, 33 per 1,000 women aged 15-49Guatemala: 1.45 per million people, 62.8 per 1,000 women aged 15-49Hong Kong SAR, China: 5,874 per million people, 27.8 per 1,000 women aged 15-49Honduras: 188 per million people, 67.8 per 1,000 women aged 15-49Croatia: 2,440 per million people, 33.5 per 1,000 women aged 15-49Hungary: 4,567 per million people, 27.3 per 1,000 women aged 15-49Indonesia: 395 per million people, 39.9 per 1,000 women aged 15-49India: 259 per million people, 62.4 per 1,000 women aged 15-49Iceland: 5,953 per million people, 32.6 per 1,000 women aged 15-49Italy: 2,855 per million people, 28.3 per 1,000 women aged 15-49Japan: 5,609 per million people, 21.4 per 1,000 women aged 15-49Kazakhstan: 758 per million people, 57.5 per 1,000 women aged 15-49Kenya: 384 per million people, 113 per 1,000 women aged 15-49Cambodia: 30.4 per million people, 69.2 per 1,000 women aged 15-49Korea, Rep.: 9,472 per million people, 34.5 per 1,000 women aged 15-49Sri Lanka: 94.5 per million people, 38.9 per 1,000 women aged 15-49Lesotho: 32.2 per million people, 98.9 per 1,000 women aged 15-49Lithuania: 3,704 per million people, 25.6 per 1,000 women aged 15-49Latvia: 2,191 per million people, 33.8 per 1,000 women aged 15-49Moldova: 650 per million people, 26.2 per 1,000 women aged 15-49Madagascar: 32.9 per million people, 94.8 per 1,000 women aged 15-49Mexico: 438 per million people, 60.3 per 1,000 women aged 15-49North Macedonia: 888 per million people, 23.2 per 1,000 women aged 15-49Mali: 26 per million people, 67.6 per 1,000 women aged 15-49Myanmar: 28 per million people, 35.5 per 1,000 women aged 15-49Montenegro: 764 per million people, 10.9 per 1,000 women aged 15-49Mongolia: 535 per million people, 31.4 per 1,000 women aged 15-49Mozambique: 44.4 per million people, 88.2 per 1,000 women aged 15-49Malawi: 25.2 per million people, 115 per 1,000 women aged 15-49Namibia: 225 per million people, 104 per 1,000 women aged 15-49Niger: 26.9 per million people, 49.2 per 1,000 women aged 15-49Nigeria: 22.1 per million people, 68.2 per 1,000 women aged 15-49Netherlands: 6,563 per million people, 17.5 per 1,000 women aged 15-49Norway: 7,451 per million people, 34.2 per 1,000 women aged 15-49New Zealand: 5,435 per million people, 40.9 per 1,000 women aged 15-49Pakistan: 474 per million people, 70.9 per 1,000 women aged 15-49Panama: 250 per million people, 73.1 per 1,000 women aged 15-49Philippines: 320 per million people, 70.8 per 1,000 women aged 15-49Papua New Guinea: 33.2 per million people, 79.8 per 1,000 women aged 15-49Poland: 3,675 per million people, 28.7 per 1,000 women aged 15-49Puerto Rico (US): 332 per million people, 54.3 per 1,000 women aged 15-49Portugal: 5,983 per million people, 20.9 per 1,000 women aged 15-49Paraguay: 139 per million people, 67.4 per 1,000 women aged 15-49Romania: 1,082 per million people, 44.4 per 1,000 women aged 15-49Russian Federation: 2,639 per million people, 64.2 per 1,000 women aged 15-49Rwanda: 133 per million people, 97.6 per 1,000 women aged 15-49Senegal: 572 per million people, 61.3 per 1,000 women aged 15-49Singapore: 8,782 per million people, 18.8 per 1,000 women aged 15-49El Salvador: 55.5 per million people, 57.6 per 1,000 women aged 15-49Serbia: 2,688 per million people, 21 per 1,000 women aged 15-49Slovak Republic: 3,507 per million people, 27.3 per 1,000 women aged 15-49Slovenia: 5,616 per million people, 33.2 per 1,000 women aged 15-49Sweden: 8,911 per million people, 35.8 per 1,000 women aged 15-49Eswatini: 138 per million people, 111 per 1,000 women aged 15-49Chad: 56.7 per million people, 59.6 per 1,000 women aged 15-49Togo: 57.8 per million people, 100 per 1,000 women aged 15-49Thailand: 1,592 per million people, 38.3 per 1,000 women aged 15-49Trinidad and Tobago: 493 per million people, 83.9 per 1,000 women aged 15-49Tanzania: 19.3 per million people, 105 per 1,000 women aged 15-49Uganda: 81.3 per million people, 145 per 1,000 women aged 15-49Ukraine: 586 per million people, 27.1 per 1,000 women aged 15-49Uruguay: 938 per million people, 41.5 per 1,000 women aged 15-49United States: 4,937 per million people, 34.7 per 1,000 women aged 15-49Uzbekistan: 640 per million people, 28.6 per 1,000 women aged 15-49Viet Nam: 836 per million people, 85.5 per 1,000 women aged 15-49South Africa: 444 per million people, 81.5 per 1,000 women aged 15-49Zimbabwe: 95.1 per million people, 73.9 per 1,000 women aged 15-49AGOALBBIHCODDNKKORMNESGPSWEUGA

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5991.1e-11106
By rank (Spearman), not adjusted-0.7111.4e-17106
Standard (Pearson), adjusted for national income-0.1840.061106
By rank (Spearman), adjusted for national income-0.2450.012106

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 106 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: +0.416 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.207 (without MNE) to -0.164 (without TTO). 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: MNE (-0.023).

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 & Pacific15-0.10
Europe & Central Asia40-0.05
Latin America & Caribbean17-0.17
Sub-Saharan Africa28-0.16

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 third36-0.26
Middle third35-0.14
Richest third35-0.25

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
Christians75-0.25
Muslims14+0.54

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
Spain15-0.23
United Kingdom25-0.20

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 = -0.192 after dropping 1 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 million people
per 1,000 women aged 15-49		Years
Korea, Rep. KOR9,47234.52023, 2019
Sweden SWE8,91135.82023, 2019
Denmark DNK8,83829.82023, 2019
Singapore SGP8,78218.82022, 2019
Finland FIN8,31532.62023, 2019
Norway NOR7,45134.22023, 2019
Netherlands NLD6,56317.52023, 2019
Switzerland CHE6,10820.32023, 2019
Belgium BEL5,990212023, 2019
Portugal PRT5,98320.92023, 2019
Iceland ISL5,95332.62023, 2019
Germany DEU5,92621.32023, 2019
Hong Kong SAR, China HKG5,87427.82024, 2019
Canada CAN5,62431.52022, 2019
Slovenia SVN5,61633.22023, 2019

World Bank, World Development Indicators
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

Researchers

Researchers in R&D (per million people)

UNESCO Institute for Statistics · CC BY 4.0 · updated quarterly

Researchers counted as full-time equivalents (two half-time researchers count as one), from national research surveys that many countries run only now and then. So coverage is thin outside the OECD.

Unintended pregnancy rate

Unintended pregnancies 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 pregnancies that were not wanted then or not wanted at all, per 1,000 women aged 15 to 49, averaged over 2015-2019. Whether a pregnancy was intended comes from what women say in surveys, so it is an estimate built from those surveys and a statistical model. Each figure has a range: Uganda's is 145, but it could be from 123 to 169.

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2024. 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 Researchers and Unintended pregnancy rate

This page shows that two measures go together. It does not show that Researchers changes Unintended pregnancy rate, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Researchers or Unintended pregnancy rate