placestats

Road traffic deaths vs. Slum share of urban population

Fades after adjusting for income

Across 176 countries, Road traffic deaths and Slum share of urban population rise and fall together at r = +0.63 (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, which could easily be chance (q = 0.19, 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 road traffic deaths, 7.67 to 24.4 per 100,000 population, slum share of urban population is worse by 24.8% of urban population at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 9.89% of urban population.

Link before adjusting (r)+0.628p = 1.1e-20 · 176 countries
After adjusting for national income+0.277p = 0.000 · likely range [+0.13, +0.41]
p, allowing for regions0.052standard error 0.115 · 7 regions
Check for luck (q)0.187across 12,497 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
Slum share of urban population · % of urban populationlink with income -0.78 · 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 →Slum share of urban population · % of urban population →064.60%92.5%Afghanistan: 15.9 per 100,000 population, 71.6% of urban populationAngola: 26.1 per 100,000 population, 62.7% of urban populationAlbania: 11.7 per 100,000 population, 2.7% of urban populationAndorra: 7.6 per 100,000 population, 0% of urban populationUnited Arab Emirates: 8.9 per 100,000 population, 0.113% of urban populationArgentina: 14.1 per 100,000 population, 14.5% of urban populationArmenia: 20 per 100,000 population, 8.39% of urban populationAntigua and Barbuda: 0 per 100,000 population, 2.65% of urban populationAustralia: 4.9 per 100,000 population, 0.035% of urban populationAustria: 4.9 per 100,000 population, 0.0466% of urban populationAzerbaijan: 6.7 per 100,000 population, 26.9% of urban populationBurundi: 35.5 per 100,000 population, 36.8% of urban populationBelgium: 5.8 per 100,000 population, 0% of urban populationBenin: 26.8 per 100,000 population, 64% of urban populationBurkina Faso: 31 per 100,000 population, 87.9% of urban populationBangladesh: 15.3 per 100,000 population, 51.5% of urban populationBulgaria: 9.2 per 100,000 population, 0.197% of urban populationBahrain: 5.2 per 100,000 population, 0% of urban populationBosnia and Herzegovina: 13.5 per 100,000 population, 0.313% of urban populationBelarus: 7.6 per 100,000 population, 0.004% of urban populationBelize: 22.6 per 100,000 population, 15.7% of urban populationBolivia: 21.1 per 100,000 population, 46.6% of urban populationBrazil: 16 per 100,000 population, 14.9% of urban populationBrunei Darussalam: 7.5 per 100,000 population, 21.6% of urban populationBhutan: 16.2 per 100,000 population, 44.7% of urban populationBotswana: 26.4 per 100,000 population, 39.6% of urban populationCentral African Republic: 37.7 per 100,000 population, 68.9% of urban populationCanada: 5.3 per 100,000 population, 1.1% of urban populationSwitzerland: 2.2 per 100,000 population, 0% of urban populationChile: 14.9 per 100,000 population, 7.32% of urban populationChina: 17.4 per 100,000 population, 26.3% of urban populationCote d'Ivoire: 24.1 per 100,000 population, 48.3% of urban populationCameroon: 30.2 per 100,000 population, 32.7% of urban populationCongo, Dem. Rep.: 34.9 per 100,000 population, 78.4% of urban populationCongo, Rep.: 29.7 per 100,000 population, 75.3% of urban populationColombia: 15.4 per 100,000 population, 9.7% of urban populationComoros: 26.6 per 100,000 population, 48.5% of urban populationCabo Verde: 26.8 per 100,000 population, 46.4% of urban populationCosta Rica: 14.8 per 100,000 population, 3.55% of urban populationCyprus: 5.8 per 100,000 population, 0.272% of urban populationCzechia: 5.9 per 100,000 population, 0.0273% of urban populationGermany: 3.8 per 100,000 population, 0% of urban populationDjibouti: 23.5 per 100,000 population, 48.7% of urban populationDenmark: 3.7 per 100,000 population, 0% of urban populationDominican Republic: 64.6 per 100,000 population, 11.2% of urban populationAlgeria: 20.9 per 100,000 population, 13.2% of urban populationEcuador: 20.1 per 100,000 population, 57.8% of urban populationEgypt, Arab Rep.: 10.1 per 100,000 population, 3.84% of urban populationSpain: 3.9 per 100,000 population, 0.046% of urban populationEstonia: 4.5 per 100,000 population, 0.345% of urban populationEthiopia: 28.2 per 100,000 population, 64.3% of urban populationFinland: 3.9 per 100,000 population, 0% of urban populationFiji: 13.5 per 100,000 population, 9.4% of urban populationFrance: 5.1 per 100,000 population, 0% of urban populationGabon: 23.9 per 100,000 population, 38.8% of urban populationUnited Kingdom: 3.2 per 100,000 population, 0.163% of urban populationGeorgia: 12.4 per 100,000 population, 7.08% of urban populationGhana: 25.7 per 100,000 population, 33.5% of urban populationGuinea: 29.7 per 100,000 population, 44% of urban populationGambia, The: 29.6 per 100,000 population, 37.1% of urban populationGuinea-Bissau: 32.2 per 100,000 population, 59% of urban populationEquatorial Guinea: 27.2 per 100,000 population, 64.7% of urban populationGreece: 8.3 per 100,000 population, 0.05% of urban populationGuatemala: 22.9 per 100,000 population, 37.6% of urban populationGuyana: 22.3 per 100,000 population, 11.3% of urban populationHonduras: 16.1 per 100,000 population, 31.5% of urban populationCroatia: 7.9 per 100,000 population, 0.527% of urban populationHaiti: 18.8 per 100,000 population, 51.1% of urban populationHungary: 7.7 per 100,000 population, 7.2% of urban populationIndonesia: 11.3 per 100,000 population, 19.4% of urban populationIndia: 15.6 per 100,000 population, 5.41% of urban populationIreland: 3.1 per 100,000 population, 8.5% of urban populationIran, Islamic Rep.: 21.5 per 100,000 population, 44.7% of urban populationIraq: 27.3 per 100,000 population, 49.3% of urban populationIceland: 2 per 100,000 population, 0% of urban populationItaly: 5.3 per 100,000 population, 0.02% of urban populationJamaica: 15.1 per 100,000 population, 0.883% of urban populationJordan: 17 per 100,000 population, 23.4% of urban populationJapan: 3.6 per 100,000 population, 2% of urban populationKazakhstan: 12.7 per 100,000 population, 0.794% of urban populationKenya: 28.3 per 100,000 population, 40.5% of urban populationKyrgyz Republic: 12.7 per 100,000 population, 2.44% of urban populationCambodia: 19.6 per 100,000 population, 42.3% of urban populationKiribati: 1.9 per 100,000 population, 5.93% of urban populationKorea, Rep.: 8.6 per 100,000 population, 4.5% of urban populationKuwait: 15.4 per 100,000 population, 0% of urban populationLao PDR: 17.9 per 100,000 population, 54.8% of urban populationLebanon: 16.4 per 100,000 population, 4.53% of urban populationLiberia: 38.9 per 100,000 population, 60.5% of urban populationLibya: 21.3 per 100,000 population, 16.6% of urban populationSt. Lucia: 29.8 per 100,000 population, 0.441% of urban populationSri Lanka: 19.7 per 100,000 population, 44.7% of urban populationLesotho: 31.9 per 100,000 population, 25.6% of urban populationLithuania: 8.1 per 100,000 population, 0.509% of urban populationLuxembourg: 4.1 per 100,000 population, 0.0173% of urban populationLatvia: 8.1 per 100,000 population, 0.593% of urban populationMorocco: 17 per 100,000 population, 10.9% of urban populationMoldova: 7.3 per 100,000 population, 6.5% of urban populationMadagascar: 29.2 per 100,000 population, 65.7% of urban populationMaldives: 1.6 per 100,000 population, 34.8% of urban populationMexico: 12.8 per 100,000 population, 17.6% of urban populationMarshall Islands: 5.7 per 100,000 population, 2.38% of urban populationNorth Macedonia: 5.1 per 100,000 population, 0.278% of urban populationMali: 22.7 per 100,000 population, 92.5% of urban populationMalta: 4.1 per 100,000 population, 0.0375% of urban populationMyanmar: 20.4 per 100,000 population, 58.3% of urban populationMontenegro: 7.6 per 100,000 population, 8.77% of urban populationMongolia: 21 per 100,000 population, 17.9% of urban populationMozambique: 30 per 100,000 population, 55% of urban populationMauritania: 25.6 per 100,000 population, 58.6% of urban populationMauritius: 12.2 per 100,000 population, 48.7% of urban populationMalawi: 33.4 per 100,000 population, 38% of urban populationMalaysia: 22.5 per 100,000 population, 0.2% of urban populationNamibia: 34.8 per 100,000 population, 41.4% of urban populationNiger: 25.5 per 100,000 population, 70.4% of urban populationNigeria: 20.7 per 100,000 population, 48.5% of urban populationNicaragua: 16.9 per 100,000 population, 5.52% of urban populationNetherlands: 4 per 100,000 population, 0% of urban populationNorway: 2.1 per 100,000 population, 0% of urban populationNepal: 16.3 per 100,000 population, 40.1% of urban populationNew Zealand: 9.6 per 100,000 population, 0% of urban populationOman: 10.6 per 100,000 population, 0% of urban populationPakistan: 13 per 100,000 population, 56% of urban populationPanama: 13.9 per 100,000 population, 16.3% of urban populationPeru: 13.6 per 100,000 population, 45.1% of urban populationPhilippines: 12 per 100,000 population, 35.9% of urban populationPalau: 4.78 per 100,000 population, 0.618% of urban populationPapua New Guinea: 12.6 per 100,000 population, 22.3% of urban populationPoland: 9.4 per 100,000 population, 4.22% of urban populationPortugal: 8.2 per 100,000 population, 0.059% of urban populationParaguay: 22 per 100,000 population, 15.1% of urban populationWest Bank and Gaza: 5.3 per 100,000 population, 19.5% of urban populationQatar: 7.3 per 100,000 population, 0% of urban populationRomania: 10.3 per 100,000 population, 2.52% of urban populationRussian Federation: 12 per 100,000 population, 2.62% of urban populationRwanda: 29.4 per 100,000 population, 38.3% of urban populationSaudi Arabia: 35.9 per 100,000 population, 0.55% of urban populationSudan: 26.8 per 100,000 population, 73.7% of urban populationSenegal: 23.5 per 100,000 population, 46.4% of urban populationSingapore: 2.1 per 100,000 population, 0% of urban populationSolomon Islands: 16.5 per 100,000 population, 1.95% of urban populationSierra Leone: 33 per 100,000 population, 49.3% of urban populationEl Salvador: 20.9 per 100,000 population, 16.5% of urban populationSomalia, Fed. Rep.: 27.4 per 100,000 population, 48.7% of urban populationSerbia: 7.5 per 100,000 population, 1.42% of urban populationSao Tome and Principe: 27.9 per 100,000 population, 82.4% of urban populationSuriname: 15.3 per 100,000 population, 15.8% of urban populationSlovak Republic: 6.1 per 100,000 population, 0.066% of urban populationSlovenia: 5.1 per 100,000 population, 0.527% of urban populationSweden: 3.1 per 100,000 population, 0.336% of urban populationEswatini: 33.5 per 100,000 population, 17% of urban populationSeychelles: 11.3 per 100,000 population, 48.7% of urban populationSyrian Arab Republic: 14.9 per 100,000 population, 41.1% of urban populationChad: 32.4 per 100,000 population, 82% of urban populationTogo: 28.7 per 100,000 population, 38.5% of urban populationThailand: 32.2 per 100,000 population, 2% of urban populationTajikistan: 15.7 per 100,000 population, 0.05% of urban populationTurkmenistan: 13.5 per 100,000 population, 8.38% of urban populationTimor-Leste: 11.9 per 100,000 population, 33.9% of urban populationTonga: 33 per 100,000 population, 0.308% of urban populationTrinidad and Tobago: 9.3 per 100,000 population, 8.63% of urban populationTunisia: 16.5 per 100,000 population, 7.64% of urban populationTurkiye: 6.7 per 100,000 population, 14.1% of urban populationTanzania: 31.1 per 100,000 population, 70.1% of urban populationUganda: 29.4 per 100,000 population, 52.7% of urban populationUkraine: 10.2 per 100,000 population, 1.1% of urban populationUruguay: 14.8 per 100,000 population, 1.3% of urban populationUnited States: 12.7 per 100,000 population, 0.0932% of urban populationUzbekistan: 11.7 per 100,000 population, 7.1% of urban populationSt. Vincent and the Grenadines: 7.4 per 100,000 population, 2.76% of urban populationViet Nam: 30.6 per 100,000 population, 32.5% of urban populationVanuatu: 14.9 per 100,000 population, 3.06% of urban populationSamoa: 13 per 100,000 population, 34.6% of urban populationSouth Africa: 22.2 per 100,000 population, 24.2% of urban populationZambia: 20.5 per 100,000 population, 48.3% of urban populationZimbabwe: 41.2 per 100,000 population, 54.9% of urban populationAFGATGBFACODDOMISLMDVMLINORSAUTON

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.6281.1e-20176
By rank (Spearman), not adjusted+0.7112.1e-28176
Standard (Pearson), adjusted for national income+0.2770.000176
By rank (Spearman), adjusted for national income+0.3384.6e-6176

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 176 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: +0.351 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.246 (without KIR) to +0.328 (without DOM). 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: DOM (+0.051).

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 & Pacific26+0.18
Europe & Central Asia49+0.04
Latin America & Caribbean26+0.07
Middle East, North Africa, Afghanistan & Pakistan21+0.28
Sub-Saharan Africa46-0.16

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 third59+0.43
Middle third58+0.19
Richest third59+0.12

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
Christians104+0.35
Muslims49+0.24

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
France25+0.26
Never a European colony21+0.14
Spain19+0.06
United Kingdom55+0.22

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 = +0.328 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 19years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

The link shows up within countries over time (r = -0.187) but mostly disappears in year-to-year changes (r = —). That points to slow trends particular to each country, not the two measures moving together from year to year.

Across countries (adjusted)+0.277for comparison
Within countries-0.000each country vs itself
…and vs the same year elsewhere-0.187q = 0.000 · 159 countries
Year-on-year changes—q = —
Read with care.
  • Almost all of the second indicator's variation is between countries, so the within-country estimate rests on a small part of the data.

1,541 country-years (one country in one year), 159 countries, 2000–2018, about 10 years each on average. Share of the variation that happens within countries over time: 11% for Road traffic deaths, 7% for Slum share of urban population. The margins of error allow for each country appearing many times, and for each year’s value being close to the year before.

Year-to-year changes are a cautious test, not a final answer. Looking only at changes from one year to the next removes each country’s own trends. But it also makes measurement mistakes louder, which pulls the results toward zero. A near-zero result here is weak evidence of no link, not proof.

With one measure years behind the other

0.20−0.2-100+10years Slum share of urban population trails Road traffic deaths →lag -10: r = -0.001 (n = 730)lag -9: r = -0.076 (n = 895)lag -8: r = -0.088 (n = 895)lag -7: r = -0.130 (n = 1,059)lag -6: r = -0.130 (n = 1,059)lag -5: r = -0.161 (n = 1,224)lag -4: r = -0.161 (n = 1,224)lag -3: r = -0.188 (n = 1,381)lag -2: r = -0.171 (n = 1,381)lag -1: r = -0.187 (n = 1,541)lag +0: r = -0.187 (n = 1,541)lag +1: r = -0.162 (n = 1,544)lag +2: r = -0.164 (n = 1,544)lag +3: r = -0.114 (n = 1,547)lag +4: r = -0.109 (n = 1,547)lag +5: r = -0.094 (n = 1,387)lag +6: r = -0.097 (n = 1,387)lag +7: r = -0.068 (n = 1,233)lag +8: r = -0.070 (n = 1,233)lag +9: r = -0.012 (n = 1,071)lag +10: r = -0.039 (n = 1,071)

Same year (lag 0): -0.187. A peak away from zero does not show which comes first. These series change slowly — this year’s value is close to last year’s. That makes the curve smooth and nearly symmetric, whatever produced the data. Even a sharp peak at one lag (a gap of some years) would not prove that one measure changes the other.

The data


per 100,000 population
% of urban population		Years
Dominican Republic DOM64.611.2%2019, 2022
Zimbabwe ZWE41.254.9%2019, 2022
Liberia LBR38.960.5%2019, 2022
Central African Republic CAF37.768.9%2019, 2022
Saudi Arabia SAU35.90.55%2019, 2022
Burundi BDI35.536.8%2019, 2022
Congo, Dem. Rep. COD34.978.4%2019, 2022
Namibia NAM34.841.4%2019, 2022
Eswatini SWZ33.517%2019, 2022
Malawi MWI33.438%2019, 2022
Tonga TON330.308%2019, 2022
Sierra Leone SLE3349.3%2019, 2022
Chad TCD32.482%2019, 2022
Thailand THA32.22%2019
Guinea-Bissau GNB32.259%2019, 2022

World Bank, World Development Indicators
World Bank, World Development Indicators

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.

Slum share of urban population

Population living in slums (% of urban population)

UN-Habitat · CC BY 4.0 · updated quarterly

How this was computed

Data used: most recent value in 2010-2025; values come from 2012–2022. 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 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Road traffic deaths and Slum share of urban population

This page shows that two measures go together. It does not show that Road traffic deaths changes Slum share of urban population, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Road traffic deaths or Slum share of urban population