Religion very important vs. Road traffic deaths
Fades 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 103 countries, Religion very important and Road traffic deaths rise and fall together at r = +0.51 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.10, which could easily be chance (q = 0.70, 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 religion very important, 15.7% to 71.4% of respondents, road traffic deaths is worse by 7.55 per 100,000 population at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 1.31 per 100,000 population.
Link before adjusting (r)+0.513p = 3.0e-8 · 103 countries
After adjusting for national income+0.103p = 0.305 · likely range [-0.09, +0.29]
p, allowing for regions0.526standard error 0.152 · 7 regions
Check for luck (q)0.701across 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.
Religion very important · % of respondentslink with income -0.66 · high
Road traffic deaths · per 100,000 populationlink with income -0.71 · 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
best-fit line line after adjusting
Four ways to measure the link
| Method | r | p | Countries |
|---|---|---|---|
| Standard (Pearson), not adjusted | +0.513 | 3.0e-8 | 103 |
| By rank (Spearman), not adjusted | +0.542 | 3.4e-9 | 103 |
| Standard (Pearson), adjusted for national income | +0.103 | 0.305 | 103 |
| By rank (Spearman), adjusted for national income | +0.058 | 0.566 | 103 |
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 103 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: +0.411 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from +0.069 (without HTI) to +0.158 (without VNM). 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: VNM (+0.055).
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.
| n | r | ||
|---|---|---|---|
| East Asia & Pacific | 13 | -0.28 | |
| Europe & Central Asia | 48 | +0.27 | |
| Latin America & Caribbean | 13 | -0.09 | |
| Middle East, North Africa, Afghanistan & Pakistan | 14 | +0.10 |
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.
| n | r | ||
|---|---|---|---|
| Poorest third | 35 | +0.00 | |
| Middle third | 34 | -0.12 | |
| Richest third | 34 | +0.59 |
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.
| n | r | ||
|---|---|---|---|
| Christians | 61 | +0.32 | |
| Muslims | 28 | +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.
| n | r | ||
|---|---|---|---|
| Never a European colony | 15 | +0.11 | |
| Spain | 12 | -0.49 | |
| United Kingdom | 25 | +0.07 |
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 = +0.090 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
% of respondents | per 100,000 population | Years | |
|---|---|---|---|
| Qatar QAT | 98.9% | 7.3 | 2014, 2019 |
| Indonesia IDN | 98.1% | 11.3 | 2022, 2019 |
| Libya LBY | 97.9% | 21.3 | 2022, 2019 |
| Egypt, Arab Rep. EGY | 97.3% | 10.1 | 2022, 2019 |
| Maldives MDV | 95.7% | 1.6 | 2022, 2019 |
| Jordan JOR | 95.4% | 17 | 2022, 2019 |
| Bangladesh BGD | 94.2% | 15.3 | 2022, 2019 |
| Nigeria NGA | 93.4% | 20.7 | 2022, 2019 |
| Ethiopia ETH | 92.8% | 28.2 | 2022, 2019 |
| Ghana GHA | 91.1% | 25.7 | 2014, 2019 |
| Algeria DZA | 90.7% | 20.9 | 2014, 2019 |
| Tunisia TUN | 90.6% | 16.5 | 2022, 2019 |
| Pakistan PAK | 89.6% | 13 | 2022, 2019 |
| Morocco MAR | 89% | 17 | 2022, 2019 |
| Philippines PHL | 88.9% | 12 | 2022, 2019 |
Haerpfer, C. et al., World Values Survey; EVS, European Values Study
World Bank, World Development Indicators
Sources
Religion very important
Share saying religion is very important in their life
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)
The strongest of four answers. The others are "rather", "not very" and "not at all" important. Thinking religion is important is different from attending services, and the gap between them is the interesting part. The United States reports high importance while attendance falls. Several Catholic countries show the reverse. No "better" direction is set, for the same reason as attendance. The survey runs in waves, not every year.
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.
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 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Religion very important and Road traffic deaths
This page shows that two measures go together. It does not show that Religion very important changes Road traffic deaths, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with Religion very important or Road traffic deaths
- Religion very important vs Religiously unaffiliated before -0.70 → after adjusting -0.58
- Population 65+ vs Religion very important before -0.75 → after adjusting -0.54
- One-person households vs Religion very important before -0.74 → after adjusting -0.53
- Muslim share vs Religion very important before +0.62 → after adjusting +0.53
- Family benefits spending vs Religion very important before -0.53 → after adjusting -0.45
- PISA maths vs Road traffic deaths before -0.60 → after adjusting -0.44
- Interpersonal trust vs Religion very important before -0.64 → after adjusting -0.43
- Redistribution vs Road traffic deaths before -0.71 → after adjusting -0.42