placestats

Road traffic deaths vs. Unintended pregnancy rate

Holds up after adjusting for income

Across 140 countries, Road traffic deaths and Unintended pregnancy rate rise and fall together at r = +0.69 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.40 (q = 0.012, 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: much weaker within regions than across them (largely a between-region difference).

Comparing countries across the middle half of unintended pregnancy rate, 34.4 to 86.9 per 1,000 women aged 15-49, road traffic deaths is worse by 12.7 per 100,000 population at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 6.9 per 100,000 population.

Link before adjusting (r)+0.688p = 5.6e-21 · 140 countries
After adjusting for national income+0.399p = 1.1e-6 · likely range [+0.25, +0.53]
p, allowing for regions0.038standard error 0.150 · 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.

Road traffic deaths · per 100,000 populationlink with income -0.71 · high
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

Road traffic deaths · per 100,000 population →Unintended pregnancy rate · per 1,000 women aged 15-49 →1.664.610.9145Angola: 26.1 per 100,000 population, 120 per 1,000 women aged 15-49Albania: 11.7 per 100,000 population, 16 per 1,000 women aged 15-49Argentina: 14.1 per 100,000 population, 69 per 1,000 women aged 15-49Armenia: 20 per 100,000 population, 52.6 per 1,000 women aged 15-49Australia: 4.9 per 100,000 population, 37.4 per 1,000 women aged 15-49Azerbaijan: 6.7 per 100,000 population, 92.9 per 1,000 women aged 15-49Burundi: 35.5 per 100,000 population, 98.1 per 1,000 women aged 15-49Belgium: 5.8 per 100,000 population, 21 per 1,000 women aged 15-49Benin: 26.8 per 100,000 population, 85.9 per 1,000 women aged 15-49Burkina Faso: 31 per 100,000 population, 75.2 per 1,000 women aged 15-49Bangladesh: 15.3 per 100,000 population, 58.9 per 1,000 women aged 15-49Bulgaria: 9.2 per 100,000 population, 28.6 per 1,000 women aged 15-49Bosnia and Herzegovina: 13.5 per 100,000 population, 20 per 1,000 women aged 15-49Belarus: 7.6 per 100,000 population, 18.7 per 1,000 women aged 15-49Belize: 22.6 per 100,000 population, 70.9 per 1,000 women aged 15-49Bolivia: 21.1 per 100,000 population, 105 per 1,000 women aged 15-49Brazil: 16 per 100,000 population, 67.2 per 1,000 women aged 15-49Barbados: 8.2 per 100,000 population, 76.9 per 1,000 women aged 15-49Bhutan: 16.2 per 100,000 population, 47.5 per 1,000 women aged 15-49Botswana: 26.4 per 100,000 population, 96.8 per 1,000 women aged 15-49Central African Republic: 37.7 per 100,000 population, 90.2 per 1,000 women aged 15-49Canada: 5.3 per 100,000 population, 31.5 per 1,000 women aged 15-49Switzerland: 2.2 per 100,000 population, 20.3 per 1,000 women aged 15-49Chile: 14.9 per 100,000 population, 70 per 1,000 women aged 15-49China: 17.4 per 100,000 population, 64.8 per 1,000 women aged 15-49Cote d'Ivoire: 24.1 per 100,000 population, 96.4 per 1,000 women aged 15-49Cameroon: 30.2 per 100,000 population, 83.4 per 1,000 women aged 15-49Congo, Dem. Rep.: 34.9 per 100,000 population, 117 per 1,000 women aged 15-49Congo, Rep.: 29.7 per 100,000 population, 106 per 1,000 women aged 15-49Colombia: 15.4 per 100,000 population, 62.7 per 1,000 women aged 15-49Comoros: 26.6 per 100,000 population, 95.2 per 1,000 women aged 15-49Cabo Verde: 26.8 per 100,000 population, 102 per 1,000 women aged 15-49Costa Rica: 14.8 per 100,000 population, 51.8 per 1,000 women aged 15-49Czechia: 5.9 per 100,000 population, 34.9 per 1,000 women aged 15-49Germany: 3.8 per 100,000 population, 21.3 per 1,000 women aged 15-49Djibouti: 23.5 per 100,000 population, 50.4 per 1,000 women aged 15-49Denmark: 3.7 per 100,000 population, 29.8 per 1,000 women aged 15-49Dominican Republic: 64.6 per 100,000 population, 83.7 per 1,000 women aged 15-49Ecuador: 20.1 per 100,000 population, 79.7 per 1,000 women aged 15-49Spain: 3.9 per 100,000 population, 20.3 per 1,000 women aged 15-49Estonia: 4.5 per 100,000 population, 38.1 per 1,000 women aged 15-49Ethiopia: 28.2 per 100,000 population, 79.5 per 1,000 women aged 15-49Finland: 3.9 per 100,000 population, 32.6 per 1,000 women aged 15-49France: 5.1 per 100,000 population, 29 per 1,000 women aged 15-49Gabon: 23.9 per 100,000 population, 112 per 1,000 women aged 15-49United Kingdom: 3.2 per 100,000 population, 36.2 per 1,000 women aged 15-49Georgia: 12.4 per 100,000 population, 93.6 per 1,000 women aged 15-49Ghana: 25.7 per 100,000 population, 102 per 1,000 women aged 15-49Guinea: 29.7 per 100,000 population, 69.8 per 1,000 women aged 15-49Gambia, The: 29.6 per 100,000 population, 53.7 per 1,000 women aged 15-49Guinea-Bissau: 32.2 per 100,000 population, 99.5 per 1,000 women aged 15-49Greece: 8.3 per 100,000 population, 33 per 1,000 women aged 15-49Guatemala: 22.9 per 100,000 population, 62.8 per 1,000 women aged 15-49Guyana: 22.3 per 100,000 population, 76.5 per 1,000 women aged 15-49Honduras: 16.1 per 100,000 population, 67.8 per 1,000 women aged 15-49Croatia: 7.9 per 100,000 population, 33.5 per 1,000 women aged 15-49Haiti: 18.8 per 100,000 population, 107 per 1,000 women aged 15-49Hungary: 7.7 per 100,000 population, 27.3 per 1,000 women aged 15-49Indonesia: 11.3 per 100,000 population, 39.9 per 1,000 women aged 15-49India: 15.6 per 100,000 population, 62.4 per 1,000 women aged 15-49Iceland: 2 per 100,000 population, 32.6 per 1,000 women aged 15-49Italy: 5.3 per 100,000 population, 28.3 per 1,000 women aged 15-49Jamaica: 15.1 per 100,000 population, 86.9 per 1,000 women aged 15-49Japan: 3.6 per 100,000 population, 21.4 per 1,000 women aged 15-49Kazakhstan: 12.7 per 100,000 population, 57.5 per 1,000 women aged 15-49Kenya: 28.3 per 100,000 population, 113 per 1,000 women aged 15-49Kyrgyz Republic: 12.7 per 100,000 population, 39.7 per 1,000 women aged 15-49Cambodia: 19.6 per 100,000 population, 69.2 per 1,000 women aged 15-49Korea, Rep.: 8.6 per 100,000 population, 34.5 per 1,000 women aged 15-49Lao PDR: 17.9 per 100,000 population, 50.7 per 1,000 women aged 15-49Liberia: 38.9 per 100,000 population, 106 per 1,000 women aged 15-49St. Lucia: 29.8 per 100,000 population, 68.7 per 1,000 women aged 15-49Sri Lanka: 19.7 per 100,000 population, 38.9 per 1,000 women aged 15-49Lesotho: 31.9 per 100,000 population, 98.9 per 1,000 women aged 15-49Lithuania: 8.1 per 100,000 population, 25.6 per 1,000 women aged 15-49Latvia: 8.1 per 100,000 population, 33.8 per 1,000 women aged 15-49Moldova: 7.3 per 100,000 population, 26.2 per 1,000 women aged 15-49Madagascar: 29.2 per 100,000 population, 94.8 per 1,000 women aged 15-49Maldives: 1.6 per 100,000 population, 59.5 per 1,000 women aged 15-49Mexico: 12.8 per 100,000 population, 60.3 per 1,000 women aged 15-49North Macedonia: 5.1 per 100,000 population, 23.2 per 1,000 women aged 15-49Mali: 22.7 per 100,000 population, 67.6 per 1,000 women aged 15-49Myanmar: 20.4 per 100,000 population, 35.5 per 1,000 women aged 15-49Montenegro: 7.6 per 100,000 population, 10.9 per 1,000 women aged 15-49Mongolia: 21 per 100,000 population, 31.4 per 1,000 women aged 15-49Mozambique: 30 per 100,000 population, 88.2 per 1,000 women aged 15-49Mauritania: 25.6 per 100,000 population, 67.6 per 1,000 women aged 15-49Malawi: 33.4 per 100,000 population, 115 per 1,000 women aged 15-49Namibia: 34.8 per 100,000 population, 104 per 1,000 women aged 15-49Niger: 25.5 per 100,000 population, 49.2 per 1,000 women aged 15-49Nigeria: 20.7 per 100,000 population, 68.2 per 1,000 women aged 15-49Nicaragua: 16.9 per 100,000 population, 56.3 per 1,000 women aged 15-49Netherlands: 4 per 100,000 population, 17.5 per 1,000 women aged 15-49Norway: 2.1 per 100,000 population, 34.2 per 1,000 women aged 15-49Nepal: 16.3 per 100,000 population, 59.7 per 1,000 women aged 15-49New Zealand: 9.6 per 100,000 population, 40.9 per 1,000 women aged 15-49Pakistan: 13 per 100,000 population, 70.9 per 1,000 women aged 15-49Panama: 13.9 per 100,000 population, 73.1 per 1,000 women aged 15-49Peru: 13.6 per 100,000 population, 89.5 per 1,000 women aged 15-49Philippines: 12 per 100,000 population, 70.8 per 1,000 women aged 15-49Papua New Guinea: 12.6 per 100,000 population, 79.8 per 1,000 women aged 15-49Poland: 9.4 per 100,000 population, 28.7 per 1,000 women aged 15-49Portugal: 8.2 per 100,000 population, 20.9 per 1,000 women aged 15-49Paraguay: 22 per 100,000 population, 67.4 per 1,000 women aged 15-49Romania: 10.3 per 100,000 population, 44.4 per 1,000 women aged 15-49Russian Federation: 12 per 100,000 population, 64.2 per 1,000 women aged 15-49Rwanda: 29.4 per 100,000 population, 97.6 per 1,000 women aged 15-49Senegal: 23.5 per 100,000 population, 61.3 per 1,000 women aged 15-49Singapore: 2.1 per 100,000 population, 18.8 per 1,000 women aged 15-49Solomon Islands: 16.5 per 100,000 population, 114 per 1,000 women aged 15-49Sierra Leone: 33 per 100,000 population, 88.2 per 1,000 women aged 15-49El Salvador: 20.9 per 100,000 population, 57.6 per 1,000 women aged 15-49Somalia, Fed. Rep.: 27.4 per 100,000 population, 99.6 per 1,000 women aged 15-49Serbia: 7.5 per 100,000 population, 21 per 1,000 women aged 15-49Sao Tome and Principe: 27.9 per 100,000 population, 130 per 1,000 women aged 15-49Suriname: 15.3 per 100,000 population, 66.9 per 1,000 women aged 15-49Slovak Republic: 6.1 per 100,000 population, 27.3 per 1,000 women aged 15-49Slovenia: 5.1 per 100,000 population, 33.2 per 1,000 women aged 15-49Sweden: 3.1 per 100,000 population, 35.8 per 1,000 women aged 15-49Eswatini: 33.5 per 100,000 population, 111 per 1,000 women aged 15-49Chad: 32.4 per 100,000 population, 59.6 per 1,000 women aged 15-49Togo: 28.7 per 100,000 population, 100 per 1,000 women aged 15-49Thailand: 32.2 per 100,000 population, 38.3 per 1,000 women aged 15-49Tajikistan: 15.7 per 100,000 population, 36.9 per 1,000 women aged 15-49Turkmenistan: 13.5 per 100,000 population, 22.8 per 1,000 women aged 15-49Timor-Leste: 11.9 per 100,000 population, 49.6 per 1,000 women aged 15-49Tonga: 33 per 100,000 population, 49.4 per 1,000 women aged 15-49Trinidad and Tobago: 9.3 per 100,000 population, 83.9 per 1,000 women aged 15-49Tanzania: 31.1 per 100,000 population, 105 per 1,000 women aged 15-49Uganda: 29.4 per 100,000 population, 145 per 1,000 women aged 15-49Ukraine: 10.2 per 100,000 population, 27.1 per 1,000 women aged 15-49Uruguay: 14.8 per 100,000 population, 41.5 per 1,000 women aged 15-49United States: 12.7 per 100,000 population, 34.7 per 1,000 women aged 15-49Uzbekistan: 11.7 per 100,000 population, 28.6 per 1,000 women aged 15-49Viet Nam: 30.6 per 100,000 population, 85.5 per 1,000 women aged 15-49Vanuatu: 14.9 per 100,000 population, 86.9 per 1,000 women aged 15-49Samoa: 13 per 100,000 population, 66.4 per 1,000 women aged 15-49South Africa: 22.2 per 100,000 population, 81.5 per 1,000 women aged 15-49Zambia: 20.5 per 100,000 population, 123 per 1,000 women aged 15-49Zimbabwe: 41.2 per 100,000 population, 73.9 per 1,000 women aged 15-49AZECHECODDOMNLDSGPSLBTHATONUGAZMB

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.6885.6e-21140
By rank (Spearman), not adjusted+0.7401.5e-25140
Standard (Pearson), adjusted for national income+0.3991.1e-6140
By rank (Spearman), adjusted for national income+0.4483.3e-8140

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 140 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: +0.289 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.378 (without GUY) to +0.420 (without THA). 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: GUY (-0.021).

Fragile: this link may not hold up.
  • much weaker within regions than across them (largely a between-region difference)

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 & Pacific20-0.01
Europe & Central Asia43+0.26
Latin America & Caribbean25+0.17
Sub-Saharan Africa42+0.18

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+0.21
Middle third46+0.43
Richest third47+0.65

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
Christians95+0.45
Muslims27+0.17

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+0.25
Never a European colony16+0.17
Spain17+0.31
United Kingdom38+0.27

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 = +0.407 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 100,000 population
per 1,000 women aged 15-49		Years
Dominican Republic DOM64.683.72019
Zimbabwe ZWE41.273.92019
Liberia LBR38.91062019
Central African Republic CAF37.790.22019
Burundi BDI35.598.12019
Congo, Dem. Rep. COD34.91172019
Namibia NAM34.81042019
Eswatini SWZ33.51112019
Malawi MWI33.41152019
Tonga TON3349.42019
Sierra Leone SLE3388.22019
Chad TCD32.459.62019
Thailand THA32.238.32019
Guinea-Bissau GNB32.299.52019
Lesotho LSO31.998.92019

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

Road traffic deaths

Mortality from road traffic injury (per 100,000 population)

World Health Organization · CC BY 4.0 · updated quarterly

The World Bank's copy stops at 2019.

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. 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 Road traffic deaths and Unintended pregnancy rate

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

More links with Road traffic deaths or Unintended pregnancy rate