placestats

Frequent prayer vs. HDI

Holds up 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 76 countries, Frequent prayer and HDI rise and fall together at r = -0.70 (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 (q = 0.047, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a weak negative link remains.

Comparing countries across the middle half of frequent prayer, 29.3% to 82.7% of respondents, hdi is worse by 0.151 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0246 points.

Link before adjusting (r)-0.698p = 2.4e-12 · 76 countries
After adjusting for national income-0.279p = 0.015 · likely range [-0.48, -0.06]
p, allowing for regions0.005standard error 0.064 · 7 regions
Check for luck (q)0.047across 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.

Frequent prayer · % of respondentslink with income -0.68 · high
HDI · index, 0 to 1link with income +0.96 · proxy

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

Frequent prayer · % of respondents →HDI · index, 0 to 1 →0.838%98.4%0.4970.959Andorra: 27.5% of respondents, 0.913 index, 0 to 1Argentina: 54% of respondents, 0.865 index, 0 to 1Armenia: 71.7% of respondents, 0.811 index, 0 to 1Australia: 28.6% of respondents, 0.958 index, 0 to 1Azerbaijan: 17.9% of respondents, 0.789 index, 0 to 1Bangladesh: 78% of respondents, 0.685 index, 0 to 1Belarus: 27.4% of respondents, 0.824 index, 0 to 1Bolivia: 82.7% of respondents, 0.733 index, 0 to 1Brazil: 77.4% of respondents, 0.786 index, 0 to 1Canada: 35.5% of respondents, 0.939 index, 0 to 1Chile: 37.4% of respondents, 0.878 index, 0 to 1China: 0.838% of respondents, 0.797 index, 0 to 1Colombia: 87.9% of respondents, 0.788 index, 0 to 1Cyprus: 69.4% of respondents, 0.913 index, 0 to 1Czechia: 13.8% of respondents, 0.915 index, 0 to 1Germany: 30.2% of respondents, 0.959 index, 0 to 1Algeria: 81.8% of respondents, 0.763 index, 0 to 1Ecuador: 82.9% of respondents, 0.777 index, 0 to 1Egypt, Arab Rep.: 96.6% of respondents, 0.754 index, 0 to 1Spain: 20.2% of respondents, 0.918 index, 0 to 1Estonia: 12.4% of respondents, 0.905 index, 0 to 1Ethiopia: 94.9% of respondents, 0.497 index, 0 to 1United Kingdom: 24.1% of respondents, 0.946 index, 0 to 1Georgia: 60.6% of respondents, 0.844 index, 0 to 1Ghana: 95.5% of respondents, 0.628 index, 0 to 1Greece: 66.4% of respondents, 0.908 index, 0 to 1Guatemala: 73.2% of respondents, 0.662 index, 0 to 1Hong Kong SAR, China: 18.6% of respondents, 0.955 index, 0 to 1Haiti: 95.4% of respondents, 0.554 index, 0 to 1Indonesia: 95.3% of respondents, 0.728 index, 0 to 1India: 68.4% of respondents, 0.685 index, 0 to 1Iran, Islamic Rep.: 80.9% of respondents, 0.799 index, 0 to 1Iraq: 84.1% of respondents, 0.695 index, 0 to 1Jordan: 86.9% of respondents, 0.754 index, 0 to 1Japan: 25% of respondents, 0.925 index, 0 to 1Kazakhstan: 35.2% of respondents, 0.837 index, 0 to 1Kenya: 93.3% of respondents, 0.628 index, 0 to 1Kyrgyz Republic: 68.3% of respondents, 0.72 index, 0 to 1Korea, Rep.: 19% of respondents, 0.937 index, 0 to 1Lebanon: 80.9% of respondents, 0.752 index, 0 to 1Libya: 97.6% of respondents, 0.721 index, 0 to 1Morocco: 80.9% of respondents, 0.71 index, 0 to 1Maldives: 93.5% of respondents, 0.766 index, 0 to 1Mexico: 71.9% of respondents, 0.789 index, 0 to 1Myanmar: 83.3% of respondents, 0.609 index, 0 to 1Mongolia: 17.8% of respondents, 0.747 index, 0 to 1Malaysia: 79.7% of respondents, 0.819 index, 0 to 1Nigeria: 98.4% of respondents, 0.56 index, 0 to 1Nicaragua: 76.3% of respondents, 0.706 index, 0 to 1Netherlands: 23% of respondents, 0.955 index, 0 to 1New Zealand: 29.6% of respondents, 0.938 index, 0 to 1Pakistan: 89.8% of respondents, 0.544 index, 0 to 1Peru: 66.6% of respondents, 0.794 index, 0 to 1Philippines: 92.4% of respondents, 0.72 index, 0 to 1Poland: 63.2% of respondents, 0.906 index, 0 to 1West Bank and Gaza: 90.5% of respondents, 0.674 index, 0 to 1Romania: 65.2% of respondents, 0.845 index, 0 to 1Russian Federation: 27% of respondents, 0.832 index, 0 to 1Rwanda: 73.7% of respondents, 0.578 index, 0 to 1Singapore: 53.1% of respondents, 0.946 index, 0 to 1Serbia: 28.7% of respondents, 0.833 index, 0 to 1Slovak Republic: 41.5% of respondents, 0.88 index, 0 to 1Slovenia: 22.5% of respondents, 0.931 index, 0 to 1Sweden: 18.3% of respondents, 0.959 index, 0 to 1Thailand: 41.4% of respondents, 0.798 index, 0 to 1Tajikistan: 67.6% of respondents, 0.691 index, 0 to 1Trinidad and Tobago: 96.8% of respondents, 0.807 index, 0 to 1Tunisia: 76.5% of respondents, 0.746 index, 0 to 1Turkiye: 71% of respondents, 0.853 index, 0 to 1Ukraine: 39% of respondents, 0.779 index, 0 to 1Uruguay: 40.6% of respondents, 0.862 index, 0 to 1United States: 62.3% of respondents, 0.938 index, 0 to 1Uzbekistan: 72.6% of respondents, 0.74 index, 0 to 1Viet Nam: 11.6% of respondents, 0.766 index, 0 to 1South Africa: 73.6% of respondents, 0.741 index, 0 to 1Zimbabwe: 94.2% of respondents, 0.598 index, 0 to 1CHNCYPETHHKGHTIMNGNGANLDSWETTOUSAVNM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.6982.4e-1276
By rank (Spearman), not adjusted-0.7231.7e-1376
Standard (Pearson), adjusted for national income-0.2790.01576
By rank (Spearman), adjusted for national income-0.2730.01876

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 76 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: +0.419 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.314 (without CHN) to -0.235 (without SGP). 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: SGP (+0.044).

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 & Pacific14-0.40
Europe & Central Asia26-0.04
Latin America & Caribbean13-0.45

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 third26-0.44
Middle third25-0.18
Richest third25-0.42

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
Christians39-0.27
Muslims22-0.31

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
Never a European colony15+0.21
Spain12-0.18
United Kingdom22-0.53

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 = -0.279 after dropping 0 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

index, 0 to 1
Years
Nigeria NGA98.4%0.562022, 2023
Libya LBY97.6%0.7212022, 2023
Trinidad and Tobago TTO96.8%0.8072014, 2023
Egypt, Arab Rep. EGY96.6%0.7542022, 2023
Ghana GHA95.5%0.6282014, 2023
Haiti HTI95.4%0.5542014, 2023
Indonesia IDN95.3%0.7282022, 2023
Ethiopia ETH94.9%0.4972022, 2023
Zimbabwe ZWE94.2%0.5982022, 2023
Maldives MDV93.5%0.7662022, 2023
Kenya KEN93.3%0.6282022, 2023
Philippines PHL92.4%0.722022, 2023
West Bank and Gaza PSE90.5%0.6742014, 2023
Pakistan PAK89.8%0.5442022, 2023
Colombia COL87.9%0.7882022, 2023

Haerpfer, C. et al., World Values Survey; EVS, European Values Study
United Nations Development Programme, Human Development Report 2025

Sources

Frequent prayer

Share praying at least several times a week

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)

Private practice. Attendance is public practice, and importance is belief. The three can differ: a country can pray often and attend rarely. Asked only from the 2014 wave on, so it covers about eighty countries. No "better" direction is set, for the same reason as attendance.

HDI

Human Development Index

United Nations Development Programme, Human Development Report Office · via Our World in Data · CC BY 3.0 IGO · updated annual

The geometric mean (a kind of average that multiplies the parts together) of three parts: income per person (GNI per capita), life expectancy, and schooling (expected years and average years). All four inputs are on this site, and each is flagged. So a link between the HDI and any of them is shown for what it is: the index matching a part of itself. For the same reason it is kept out of this site's own topic scores. Those already contain its parts, and adding it would count each twice. It is the most-cited development index there is. It is here mostly so its parts can be read separately.

How this was computed

Data used: most recent value in 2010-2025; values come from 2014–2023. 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 Frequent prayer and HDI

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

More links with Frequent prayer or HDI