placestats

Regulatory quality vs. Unintended pregnancy rate

Fades after adjusting for income

Across 142 countries, Regulatory quality and Unintended pregnancy rate rise and fall together at r = -0.56 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.05, which could easily be chance (q = 0.83, 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. Caution: direction is not consistent across regions.

Comparing countries across the middle half of unintended pregnancy rate, 34.3 to 86.7 per 1,000 women aged 15-49, regulatory quality is worse by 0.835 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0683 points.

Link before adjusting (r)-0.558p = 5.6e-13 · 142 countries
After adjusting for national income-0.055p = 0.518 · likely range [-0.22, +0.11]
p, allowing for regions0.727standard error 0.150 · 7 regions
Check for luck (q)0.831across 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.

Regulatory quality · index (approx. -2.5 to 2.5)link with income +0.83 · 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

Regulatory quality · index (approx. -2.5 to 2.5) →Unintended pregnancy rate · per 1,000 women aged 15-49 →-1.732.1310.9145Angola: -0.773 index (approx. -2.5 to 2.5), 120 per 1,000 women aged 15-49Albania: 0.136 index (approx. -2.5 to 2.5), 16 per 1,000 women aged 15-49Argentina: -0.235 index (approx. -2.5 to 2.5), 69 per 1,000 women aged 15-49Armenia: 0.138 index (approx. -2.5 to 2.5), 52.6 per 1,000 women aged 15-49Australia: 1.72 index (approx. -2.5 to 2.5), 37.4 per 1,000 women aged 15-49Azerbaijan: 0.135 index (approx. -2.5 to 2.5), 92.9 per 1,000 women aged 15-49Burundi: -0.814 index (approx. -2.5 to 2.5), 98.1 per 1,000 women aged 15-49Belgium: 1.24 index (approx. -2.5 to 2.5), 21 per 1,000 women aged 15-49Benin: -0.277 index (approx. -2.5 to 2.5), 85.9 per 1,000 women aged 15-49Burkina Faso: -0.526 index (approx. -2.5 to 2.5), 75.2 per 1,000 women aged 15-49Bangladesh: -0.95 index (approx. -2.5 to 2.5), 58.9 per 1,000 women aged 15-49Bulgaria: 0.288 index (approx. -2.5 to 2.5), 28.6 per 1,000 women aged 15-49Bosnia and Herzegovina: -0.35 index (approx. -2.5 to 2.5), 20 per 1,000 women aged 15-49Belarus: -1.23 index (approx. -2.5 to 2.5), 18.7 per 1,000 women aged 15-49Belize: -0.45 index (approx. -2.5 to 2.5), 70.9 per 1,000 women aged 15-49Bolivia: -1.25 index (approx. -2.5 to 2.5), 105 per 1,000 women aged 15-49Brazil: -0.295 index (approx. -2.5 to 2.5), 67.2 per 1,000 women aged 15-49Barbados: 0.441 index (approx. -2.5 to 2.5), 76.9 per 1,000 women aged 15-49Bhutan: -0.0913 index (approx. -2.5 to 2.5), 47.5 per 1,000 women aged 15-49Botswana: 0.402 index (approx. -2.5 to 2.5), 96.8 per 1,000 women aged 15-49Central African Republic: -1.27 index (approx. -2.5 to 2.5), 90.2 per 1,000 women aged 15-49Canada: 1.36 index (approx. -2.5 to 2.5), 31.5 per 1,000 women aged 15-49Switzerland: 1.77 index (approx. -2.5 to 2.5), 20.3 per 1,000 women aged 15-49Chile: 0.781 index (approx. -2.5 to 2.5), 70 per 1,000 women aged 15-49China: -0.0713 index (approx. -2.5 to 2.5), 64.8 per 1,000 women aged 15-49Cote d'Ivoire: -0.167 index (approx. -2.5 to 2.5), 96.4 per 1,000 women aged 15-49Cameroon: -0.729 index (approx. -2.5 to 2.5), 83.4 per 1,000 women aged 15-49Congo, Dem. Rep.: -1.28 index (approx. -2.5 to 2.5), 117 per 1,000 women aged 15-49Congo, Rep.: -1.15 index (approx. -2.5 to 2.5), 106 per 1,000 women aged 15-49Colombia: 0.0134 index (approx. -2.5 to 2.5), 62.7 per 1,000 women aged 15-49Comoros: -1.25 index (approx. -2.5 to 2.5), 95.2 per 1,000 women aged 15-49Cabo Verde: 0.0451 index (approx. -2.5 to 2.5), 102 per 1,000 women aged 15-49Costa Rica: 0.582 index (approx. -2.5 to 2.5), 51.8 per 1,000 women aged 15-49Czechia: 1.23 index (approx. -2.5 to 2.5), 34.9 per 1,000 women aged 15-49Germany: 1.5 index (approx. -2.5 to 2.5), 21.3 per 1,000 women aged 15-49Djibouti: -0.853 index (approx. -2.5 to 2.5), 50.4 per 1,000 women aged 15-49Denmark: 1.93 index (approx. -2.5 to 2.5), 29.8 per 1,000 women aged 15-49Dominican Republic: 0.207 index (approx. -2.5 to 2.5), 83.7 per 1,000 women aged 15-49Ecuador: -0.646 index (approx. -2.5 to 2.5), 79.7 per 1,000 women aged 15-49Spain: 0.621 index (approx. -2.5 to 2.5), 20.3 per 1,000 women aged 15-49Estonia: 1.4 index (approx. -2.5 to 2.5), 38.1 per 1,000 women aged 15-49Ethiopia: -0.833 index (approx. -2.5 to 2.5), 79.5 per 1,000 women aged 15-49Finland: 1.96 index (approx. -2.5 to 2.5), 32.6 per 1,000 women aged 15-49France: 1.15 index (approx. -2.5 to 2.5), 29 per 1,000 women aged 15-49Gabon: -0.723 index (approx. -2.5 to 2.5), 112 per 1,000 women aged 15-49United Kingdom: 1.51 index (approx. -2.5 to 2.5), 36.2 per 1,000 women aged 15-49Georgia: 0.65 index (approx. -2.5 to 2.5), 93.6 per 1,000 women aged 15-49Ghana: -0.0899 index (approx. -2.5 to 2.5), 102 per 1,000 women aged 15-49Guinea: -0.892 index (approx. -2.5 to 2.5), 69.8 per 1,000 women aged 15-49Gambia, The: -0.664 index (approx. -2.5 to 2.5), 53.7 per 1,000 women aged 15-49Guinea-Bissau: -1.19 index (approx. -2.5 to 2.5), 99.5 per 1,000 women aged 15-49Greece: 0.48 index (approx. -2.5 to 2.5), 33 per 1,000 women aged 15-49Guatemala: -0.309 index (approx. -2.5 to 2.5), 62.8 per 1,000 women aged 15-49Guyana: -0.447 index (approx. -2.5 to 2.5), 76.5 per 1,000 women aged 15-49Hong Kong SAR, China: 1.74 index (approx. -2.5 to 2.5), 27.8 per 1,000 women aged 15-49Honduras: -0.628 index (approx. -2.5 to 2.5), 67.8 per 1,000 women aged 15-49Croatia: 0.286 index (approx. -2.5 to 2.5), 33.5 per 1,000 women aged 15-49Haiti: -1.46 index (approx. -2.5 to 2.5), 107 per 1,000 women aged 15-49Hungary: 0.335 index (approx. -2.5 to 2.5), 27.3 per 1,000 women aged 15-49Indonesia: 0.125 index (approx. -2.5 to 2.5), 39.9 per 1,000 women aged 15-49India: -0.0961 index (approx. -2.5 to 2.5), 62.4 per 1,000 women aged 15-49Iceland: 1.33 index (approx. -2.5 to 2.5), 32.6 per 1,000 women aged 15-49Italy: 0.64 index (approx. -2.5 to 2.5), 28.3 per 1,000 women aged 15-49Jamaica: 0.0909 index (approx. -2.5 to 2.5), 86.9 per 1,000 women aged 15-49Japan: 1.33 index (approx. -2.5 to 2.5), 21.4 per 1,000 women aged 15-49Kazakhstan: 0.0471 index (approx. -2.5 to 2.5), 57.5 per 1,000 women aged 15-49Kenya: -0.334 index (approx. -2.5 to 2.5), 113 per 1,000 women aged 15-49Kyrgyz Republic: -0.517 index (approx. -2.5 to 2.5), 39.7 per 1,000 women aged 15-49Cambodia: -0.631 index (approx. -2.5 to 2.5), 69.2 per 1,000 women aged 15-49Korea, Rep.: 1.01 index (approx. -2.5 to 2.5), 34.5 per 1,000 women aged 15-49Lao PDR: -0.636 index (approx. -2.5 to 2.5), 50.7 per 1,000 women aged 15-49Liberia: -0.842 index (approx. -2.5 to 2.5), 106 per 1,000 women aged 15-49St. Lucia: 0.182 index (approx. -2.5 to 2.5), 68.7 per 1,000 women aged 15-49Sri Lanka: -0.299 index (approx. -2.5 to 2.5), 38.9 per 1,000 women aged 15-49Lesotho: -0.485 index (approx. -2.5 to 2.5), 98.9 per 1,000 women aged 15-49Lithuania: 1.29 index (approx. -2.5 to 2.5), 25.6 per 1,000 women aged 15-49Latvia: 1.1 index (approx. -2.5 to 2.5), 33.8 per 1,000 women aged 15-49Moldova: -0.0467 index (approx. -2.5 to 2.5), 26.2 per 1,000 women aged 15-49Madagascar: -0.749 index (approx. -2.5 to 2.5), 94.8 per 1,000 women aged 15-49Maldives: -0.235 index (approx. -2.5 to 2.5), 59.5 per 1,000 women aged 15-49Mexico: -0.196 index (approx. -2.5 to 2.5), 60.3 per 1,000 women aged 15-49North Macedonia: 0.266 index (approx. -2.5 to 2.5), 23.2 per 1,000 women aged 15-49Mali: -0.762 index (approx. -2.5 to 2.5), 67.6 per 1,000 women aged 15-49Myanmar: -1.42 index (approx. -2.5 to 2.5), 35.5 per 1,000 women aged 15-49Montenegro: 0.127 index (approx. -2.5 to 2.5), 10.9 per 1,000 women aged 15-49Mongolia: -0.0707 index (approx. -2.5 to 2.5), 31.4 per 1,000 women aged 15-49Mozambique: -0.764 index (approx. -2.5 to 2.5), 88.2 per 1,000 women aged 15-49Mauritania: -0.778 index (approx. -2.5 to 2.5), 67.6 per 1,000 women aged 15-49Malawi: -0.585 index (approx. -2.5 to 2.5), 115 per 1,000 women aged 15-49Namibia: 0.135 index (approx. -2.5 to 2.5), 104 per 1,000 women aged 15-49Niger: -0.762 index (approx. -2.5 to 2.5), 49.2 per 1,000 women aged 15-49Nigeria: -0.633 index (approx. -2.5 to 2.5), 68.2 per 1,000 women aged 15-49Nicaragua: -0.991 index (approx. -2.5 to 2.5), 56.3 per 1,000 women aged 15-49Netherlands: 1.72 index (approx. -2.5 to 2.5), 17.5 per 1,000 women aged 15-49Norway: 1.67 index (approx. -2.5 to 2.5), 34.2 per 1,000 women aged 15-49Nepal: -0.552 index (approx. -2.5 to 2.5), 59.7 per 1,000 women aged 15-49New Zealand: 1.84 index (approx. -2.5 to 2.5), 40.9 per 1,000 women aged 15-49Pakistan: -0.793 index (approx. -2.5 to 2.5), 70.9 per 1,000 women aged 15-49Panama: -0.0738 index (approx. -2.5 to 2.5), 73.1 per 1,000 women aged 15-49Peru: 0.0828 index (approx. -2.5 to 2.5), 89.5 per 1,000 women aged 15-49Philippines: 0.0793 index (approx. -2.5 to 2.5), 70.8 per 1,000 women aged 15-49Papua New Guinea: -0.6 index (approx. -2.5 to 2.5), 79.8 per 1,000 women aged 15-49Poland: 0.686 index (approx. -2.5 to 2.5), 28.7 per 1,000 women aged 15-49Puerto Rico (US): 0.653 index (approx. -2.5 to 2.5), 54.3 per 1,000 women aged 15-49Portugal: 0.74 index (approx. -2.5 to 2.5), 20.9 per 1,000 women aged 15-49Paraguay: -0.141 index (approx. -2.5 to 2.5), 67.4 per 1,000 women aged 15-49Romania: 0.383 index (approx. -2.5 to 2.5), 44.4 per 1,000 women aged 15-49Russian Federation: -1.07 index (approx. -2.5 to 2.5), 64.2 per 1,000 women aged 15-49Rwanda: 0.27 index (approx. -2.5 to 2.5), 97.6 per 1,000 women aged 15-49Senegal: -0.242 index (approx. -2.5 to 2.5), 61.3 per 1,000 women aged 15-49Singapore: 2.13 index (approx. -2.5 to 2.5), 18.8 per 1,000 women aged 15-49Solomon Islands: -0.888 index (approx. -2.5 to 2.5), 114 per 1,000 women aged 15-49Sierra Leone: -1.06 index (approx. -2.5 to 2.5), 88.2 per 1,000 women aged 15-49El Salvador: -0.176 index (approx. -2.5 to 2.5), 57.6 per 1,000 women aged 15-49Somalia, Fed. Rep.: -1.73 index (approx. -2.5 to 2.5), 99.6 per 1,000 women aged 15-49Serbia: 0.0784 index (approx. -2.5 to 2.5), 21 per 1,000 women aged 15-49Sao Tome and Principe: -0.891 index (approx. -2.5 to 2.5), 130 per 1,000 women aged 15-49Suriname: -0.919 index (approx. -2.5 to 2.5), 66.9 per 1,000 women aged 15-49Slovak Republic: 0.405 index (approx. -2.5 to 2.5), 27.3 per 1,000 women aged 15-49Slovenia: 0.798 index (approx. -2.5 to 2.5), 33.2 per 1,000 women aged 15-49Sweden: 1.67 index (approx. -2.5 to 2.5), 35.8 per 1,000 women aged 15-49Eswatini: -0.638 index (approx. -2.5 to 2.5), 111 per 1,000 women aged 15-49Chad: -1.09 index (approx. -2.5 to 2.5), 59.6 per 1,000 women aged 15-49Togo: -0.408 index (approx. -2.5 to 2.5), 100 per 1,000 women aged 15-49Thailand: 0.106 index (approx. -2.5 to 2.5), 38.3 per 1,000 women aged 15-49Tajikistan: -0.759 index (approx. -2.5 to 2.5), 36.9 per 1,000 women aged 15-49Turkmenistan: -1.69 index (approx. -2.5 to 2.5), 22.8 per 1,000 women aged 15-49Timor-Leste: -0.734 index (approx. -2.5 to 2.5), 49.6 per 1,000 women aged 15-49Tonga: -0.194 index (approx. -2.5 to 2.5), 49.4 per 1,000 women aged 15-49Trinidad and Tobago: -0.207 index (approx. -2.5 to 2.5), 83.9 per 1,000 women aged 15-49Tanzania: -0.535 index (approx. -2.5 to 2.5), 105 per 1,000 women aged 15-49Uganda: -0.524 index (approx. -2.5 to 2.5), 145 per 1,000 women aged 15-49Ukraine: -0.301 index (approx. -2.5 to 2.5), 27.1 per 1,000 women aged 15-49Uruguay: 0.647 index (approx. -2.5 to 2.5), 41.5 per 1,000 women aged 15-49United States: 1.35 index (approx. -2.5 to 2.5), 34.7 per 1,000 women aged 15-49Uzbekistan: -0.527 index (approx. -2.5 to 2.5), 28.6 per 1,000 women aged 15-49Viet Nam: -0.267 index (approx. -2.5 to 2.5), 85.5 per 1,000 women aged 15-49Vanuatu: -0.325 index (approx. -2.5 to 2.5), 86.9 per 1,000 women aged 15-49Samoa: -0.102 index (approx. -2.5 to 2.5), 66.4 per 1,000 women aged 15-49South Africa: -0.0601 index (approx. -2.5 to 2.5), 81.5 per 1,000 women aged 15-49Zambia: -0.421 index (approx. -2.5 to 2.5), 123 per 1,000 women aged 15-49Zimbabwe: -1.18 index (approx. -2.5 to 2.5), 73.9 per 1,000 women aged 15-49BLRBWACHECODGEOMMRNLDSGPSTPTKMUGA

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5585.6e-13142
By rank (Spearman), not adjusted-0.5481.7e-12142
Standard (Pearson), adjusted for national income-0.0550.518142
By rank (Spearman), adjusted for national income+0.0210.809142

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: +0.503 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.096 (without TKM) to -0.014 (without GUY). 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 (-0.041).

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+0.24
Europe & Central Asia43+0.04
Latin America & Caribbean26-0.36
Sub-Saharan Africa42+0.02

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+0.15
Middle third47+0.15
Richest third47-0.35

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
Christians96-0.19
Muslims27+0.06

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
France21-0.21
Never a European colony16+0.35
Spain17-0.43
United Kingdom38+0.03

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 = -0.054 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


index (approx. -2.5 to 2.5)

per 1,000 women aged 15-49
Years
Singapore SGP2.1318.82024, 2019
Finland FIN1.9632.62024, 2019
Denmark DNK1.9329.82024, 2019
New Zealand NZL1.8440.92024, 2019
Switzerland CHE1.7720.32024, 2019
Hong Kong SAR, China HKG1.7427.82024, 2019
Australia AUS1.7237.42024, 2019
Netherlands NLD1.7217.52024, 2019
Sweden SWE1.6735.82024, 2019
Norway NOR1.6734.22024, 2019
United Kingdom GBR1.5136.22024, 2019
Germany DEU1.521.32024, 2019
Estonia EST1.438.12024, 2019
Canada CAN1.3631.52024, 2019
United States USA1.3534.72024, 2019

Kaufmann, D. and A. Kraay, Worldwide Governance Indicators, World Bank
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

Regulatory quality

Regulatory Quality (estimate)

World Bank · CC BY 4.0 · updated annual

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 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 Regulatory quality and Unintended pregnancy rate

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

More links with Regulatory quality or Unintended pregnancy rate