placestats

Fertility rate vs. Frequent prayer

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 78 countries, Fertility rate and Frequent prayer rise and fall together at r = +0.61 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.18, which could easily be chance (q = 0.27, 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.

Comparing countries across the middle half of frequent prayer, 28.9% to 82.8% of respondents, fertility rate is 0.945 births per woman higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.225 births per woman.

Link before adjusting (r)+0.611p = 2.9e-9 · 78 countries
After adjusting for national income+0.181p = 0.115 · likely range [-0.04, +0.39]
p, allowing for regions0.091standard error 0.090 · 7 regions
Check for luck (q)0.266across 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.

Fertility rate · births per womanlink with income -0.81 · proxy
Frequent prayer · % of respondentslink with income -0.68 · 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

Fertility rate · births per woman →Frequent prayer · % of respondents →0.5824.380.838%98.4%Andorra: 1.09 births per woman, 27.5% of respondentsArgentina: 1.5 births per woman, 54% of respondentsArmenia: 1.7 births per woman, 71.7% of respondentsAustralia: 1.48 births per woman, 28.6% of respondentsAzerbaijan: 1.43 births per woman, 17.9% of respondentsBangladesh: 2.14 births per woman, 78% of respondentsBelarus: 1.22 births per woman, 27.4% of respondentsBolivia: 2.52 births per woman, 82.7% of respondentsBrazil: 1.61 births per woman, 77.4% of respondentsCanada: 1.25 births per woman, 35.5% of respondentsChile: 1.14 births per woman, 37.4% of respondentsChina: 1.01 births per woman, 0.838% of respondentsColombia: 1.63 births per woman, 87.9% of respondentsCyprus: 1.38 births per woman, 69.4% of respondentsCzechia: 1.36 births per woman, 13.8% of respondentsGermany: 1.36 births per woman, 30.2% of respondentsAlgeria: 2.72 births per woman, 81.8% of respondentsEcuador: 1.81 births per woman, 82.9% of respondentsEgypt, Arab Rep.: 2.73 births per woman, 96.6% of respondentsSpain: 1.1 births per woman, 20.2% of respondentsEstonia: 1.18 births per woman, 12.4% of respondentsEthiopia: 3.91 births per woman, 94.9% of respondentsUnited Kingdom: 1.55 births per woman, 24.1% of respondentsGeorgia: 1.8 births per woman, 60.6% of respondentsGhana: 3.34 births per woman, 95.5% of respondentsGreece: 1.24 births per woman, 66.4% of respondentsGuatemala: 2.29 births per woman, 73.2% of respondentsHong Kong SAR, China: 0.841 births per woman, 18.6% of respondentsHaiti: 2.63 births per woman, 95.4% of respondentsIndonesia: 2.12 births per woman, 95.3% of respondentsIndia: 1.96 births per woman, 68.4% of respondentsIran, Islamic Rep.: 1.68 births per woman, 80.9% of respondentsIraq: 3.22 births per woman, 84.1% of respondentsJordan: 2.6 births per woman, 86.9% of respondentsJapan: 1.15 births per woman, 25% of respondentsKazakhstan: 2.98 births per woman, 35.2% of respondentsKenya: 3.17 births per woman, 93.3% of respondentsKyrgyz Republic: 2.6 births per woman, 68.3% of respondentsKorea, Rep.: 0.748 births per woman, 19% of respondentsLebanon: 2.23 births per woman, 80.9% of respondentsLibya: 2.3 births per woman, 97.6% of respondentsMacao SAR, China: 0.582 births per woman, 15.8% of respondentsMorocco: 2.21 births per woman, 80.9% of respondentsMaldives: 1.56 births per woman, 93.5% of respondentsMexico: 1.89 births per woman, 71.9% of respondentsMyanmar: 2.1 births per woman, 83.3% of respondentsMongolia: 2.5 births per woman, 17.8% of respondentsMalaysia: 1.54 births per woman, 79.7% of respondentsNigeria: 4.38 births per woman, 98.4% of respondentsNicaragua: 2.21 births per woman, 76.3% of respondentsNetherlands: 1.43 births per woman, 23% of respondentsNew Zealand: 1.57 births per woman, 29.6% of respondentsPakistan: 3.55 births per woman, 89.8% of respondentsPeru: 1.97 births per woman, 66.6% of respondentsPhilippines: 1.89 births per woman, 92.4% of respondentsPoland: 1.14 births per woman, 63.2% of respondentsPuerto Rico (US): 0.92 births per woman, 85.7% of respondentsWest Bank and Gaza: 3.25 births per woman, 90.5% of respondentsRomania: 1.39 births per woman, 65.2% of respondentsRussian Federation: 1.42 births per woman, 27% of respondentsRwanda: 3.65 births per woman, 73.7% of respondentsSingapore: 0.97 births per woman, 53.1% of respondentsSerbia: 1.64 births per woman, 28.7% of respondentsSlovak Republic: 1.46 births per woman, 41.5% of respondentsSlovenia: 1.52 births per woman, 22.5% of respondentsSweden: 1.43 births per woman, 18.3% of respondentsThailand: 1.2 births per woman, 41.4% of respondentsTajikistan: 3.04 births per woman, 67.6% of respondentsTrinidad and Tobago: 1.54 births per woman, 96.8% of respondentsTunisia: 1.82 births per woman, 76.5% of respondentsTurkiye: 1.48 births per woman, 71% of respondentsUkraine: 0.988 births per woman, 39% of respondentsUruguay: 1.4 births per woman, 40.6% of respondentsUnited States: 1.63 births per woman, 62.3% of respondentsUzbekistan: 3.49 births per woman, 72.6% of respondentsViet Nam: 1.9 births per woman, 11.6% of respondentsSouth Africa: 2.21 births per woman, 73.6% of respondentsZimbabwe: 3.67 births per woman, 94.2% of respondentsCHNETHKAZKORMACMDVMNGNGAPRITTOVNMZWE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.6112.9e-978
By rank (Spearman), not adjusted+0.6643.5e-1178
Standard (Pearson), adjusted for national income+0.1810.11578
By rank (Spearman), adjusted for national income+0.2370.03878

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 78 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: +0.429 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.136 (without CHN) to +0.216 (without KAZ). 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: CHN (-0.045).

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 & Pacific15+0.19
Europe & Central Asia26+0.13
Latin America & Caribbean14+0.06

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+0.32
Middle third26+0.38
Richest third26-0.02

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
Christians40+0.05
Muslims22+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
Never a European colony15+0.19
Spain12+0.04
United Kingdom22+0.20

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 = +0.158 after dropping 3 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


births per woman
% of respondents		Years
Nigeria NGA4.3898.4%2024, 2022
Ethiopia ETH3.9194.9%2024, 2022
Zimbabwe ZWE3.6794.2%2024, 2022
Rwanda RWA3.6573.7%2024, 2014
Pakistan PAK3.5589.8%2024, 2022
Uzbekistan UZB3.4972.6%2024, 2022
Ghana GHA3.3495.5%2024, 2014
West Bank and Gaza PSE3.2590.5%2024, 2014
Iraq IRQ3.2284.1%2024, 2022
Kenya KEN3.1793.3%2024, 2022
Tajikistan TJK3.0467.6%2024, 2022
Kazakhstan KAZ2.9835.2%2024, 2022
Egypt, Arab Rep. EGY2.7396.6%2024, 2022
Algeria DZA2.7281.8%2024, 2014
Haiti HTI2.6395.4%2024, 2014

World Bank, World Development Indicators
Haerpfer, C. et al., World Values Survey; EVS, European Values Study

Sources

Fertility rate

Fertility rate, total (births per woman)

World Bank · CC BY 4.0 · updated quarterly

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.

How this was computed

Data used: most recent value in 2010-2025; values come from 2014–2024. 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 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Fertility rate and Frequent prayer

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

More links with Fertility rate or Frequent prayer