Do Contraceptive use (any method) and PISA reading go together across countries?

Across 61 countries the link before adjusting for anything is r = +0.44, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives +0.49.

Does the link hold within countries over time, not just across countries?

There are not enough years of data within countries to check this over time.

Does Contraceptive use (any method) cause PISA reading?

This analysis cannot answer that. It shows only that the two go together. A link between two country measures, adjusted or not, does not show that either one changes the other. Country figures also say nothing about individual people.

Contraceptive use (any method) vs. PISA reading

Holds up after adjusting for income

Across 61 countries, Contraceptive use (any method) and PISA reading rise and fall together at r = +0.44 (on a scale from −1 to +1, where 0 means no link). It holds up almost unchanged when only countries with similar income (GDP per person) are compared (r = +0.51, q = 0.027, allowing for the many pairs tested).

Comparing countries across the middle half of pisa reading, 374 to 479 PISA points, contraceptive use (any method) is 10.6% higher at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 19.1%.

Link before adjusting (r)+0.443p = 0.000 · 61 countries

After adjusting for national income+0.507p = 3.6e-5 · likely range [+0.29, +0.67]

p, allowing for regions0.027standard error 0.148 · 5 regions

Check for luck (q)0.027across 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.

Contraceptive use (any method) · %link with income +0.56 · moderate

PISA reading · PISA pointslink with income +0.77 · high

“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	+0.443	0.000	61
By rank (Spearman), not adjusted	+0.494	5.3e-5	61
Standard (Pearson), adjusted for national income	+0.507	3.6e-5	61
By rank (Spearman), adjusted for national income	+0.482	9.6e-5	61

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 61 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: -0.064 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.452 (without QAT) to +0.537 (without BLR). 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: QAT (-0.055).

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
Europe & Central Asia	28	+0.36
Latin America & Caribbean	14	+0.30

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	21	+0.38
Middle third	20	+0.37
Richest third	20	+0.69

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	38	+0.34
Muslims	15	+0.29

By last european coloniser

	n	r
Spain	13	+0.66

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 = +0.531 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

	%	PISA points	Years
Finland FIN	85.5%	490	2015, 2022
Korea, Rep. KOR	84.2%	515	2021, 2022
Colombia COL	81%	409	2015, 2022
Germany DEU	80.3%	480	2011, 2022
Brazil BRA	80.2%	410	2013, 2022
France FRA	78.4%	474	2010, 2022
Peru PER	77.3%	408	2023, 2022
Chile CHL	76.3%	448	2016, 2022
United Kingdom GBR	76.1%	494	2012, 2022
Estonia EST	75.1%	511	2014, 2022
United States USA	73.9%	504	2019, 2022
Portugal PRT	73.9%	477	2014, 2022
Ireland IRL	73.3%	516	2010, 2022
Netherlands NLD	73%	459	2013, 2022
Viet Nam VNM	72.8%	462	2021, 2022

World Bank, World Development Indicators
OECD databases as named on each indicator: PISA, Social Expenditure Database (SOCX), Income Distribution Database, Development Assistance Committee statistics, Family Database, Government at a Glance, Corporate Tax Statistics, employment and environment statistics

Sources

Contraceptive use (any method)

Contraceptive prevalence, any method (% of married women ages 15-49)

World Bank · CC BY 4.0 · updated quarterly

The share of married women aged 15 to 49 who use any form of birth control, including traditional ones such as withdrawal, from national surveys. Only married women (and women living with a partner) are counted. Most countries have a survey only every few years.

PISA reading

PISA mean reading score

OECD · via Our World in Data · CC BY 4.0 (OECD terms and conditions) · updated annual, except the snapshots noted per indicator

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2023. 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 5 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 Contraceptive use (any method) and PISA reading

This page shows that two measures go together. It does not show that Contraceptive use (any method) changes PISA reading, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.