Do Health coverage index and Religiously unaffiliated go together across countries?

Across 177 countries the link before adjusting for anything is r = +0.45, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives +0.52.

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 Health coverage index cause Religiously unaffiliated?

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.

Health coverage index vs. Religiously unaffiliated

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 177 countries, Health coverage index and Religiously unaffiliated rise and fall together at r = +0.45 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.17 (q = 0.049, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a very weak positive link remains.

Comparing countries across the middle half of religiously unaffiliated, 0.32% to 13.8% of population, health coverage index is better by 6.03 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 1.21 points.

Link before adjusting (r)+0.451p = 2.9e-10 · 177 countries

After adjusting for national income+0.167p = 0.027 · likely range [+0.02, +0.31]

p, allowing for regions0.126standard error 0.094 · 7 regions

Check for luck (q)0.049across 13,797 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.

Health coverage index · index, 0 to 100link with income +0.88 · proxy

Religiously unaffiliated · % of populationlink with income +0.51 · moderate

“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	+0.451	2.9e-10	177
By rank (Spearman), not adjusted	+0.520	1.2e-13	177
Standard (Pearson), adjusted for national income	+0.167	0.027	177
By rank (Spearman), adjusted for national income	+0.201	0.008	177

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 177 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: +0.284 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.137 (without CHN) to +0.183 (without MDG). 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 (-0.030).

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	25	+0.28
Europe & Central Asia	48	+0.43
Latin America & Caribbean	28	+0.33
Middle East, North Africa, Afghanistan & Pakistan	22	+0.09
Sub-Saharan Africa	46	+0.00

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	59	-0.07
Middle third	59	+0.18
Richest third	59	+0.55

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	108	+0.20
Muslims	49	-0.21

By last european coloniser

	n	r
France	25	+0.05
Never a European colony	21	+0.17
Spain	20	+0.23
United Kingdom	58	+0.31

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 = +0.086 after dropping 16 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

	index, 0 to 100	% of population	Years
Canada CAN	92	34.6%	2023, 2020
Iceland ISL	90	19.8%	2023, 2020
New Zealand NZL	89	51.4%	2023, 2020
Norway NOR	89	22.5%	2023, 2020
Australia AUS	89	42.3%	2023, 2020
United States USA	88	29.7%	2023, 2020
Singapore SGP	88	19.9%	2023, 2020
Korea, Rep. KOR	88	48.3%	2023, 2020
United Kingdom GBR	88	40.2%	2023, 2020
Germany DEU	87	36.1%	2023, 2020
Switzerland CHE	87	30.8%	2023, 2020
Japan JPN	86	57.5%	2023, 2020
Finland FIN	86	25%	2023, 2020
Belgium BEL	86	39%	2023, 2020
Uruguay URY	85	52.4%	2023, 2020

World Health Organization, Global Health Observatory
Pew Research Center, Religious Composition by Country, 2010-2020. Pew Research Center bears no responsibility for the analyses or interpretations of the data presented here.
One of these measures is published under a licence that forbids changes. Values are shown exactly as published and must not be republished in a changed or rescaled form.

Sources

Health coverage index

Universal health coverage service coverage index

World Health Organization · via Our World in Data · CC BY-NC-SA 4.0 · updated annual

Fourteen "tracer" measures of basic health services, combined by WHO into one index. They include vaccination, care during pregnancy, treatment of tuberculosis and HIV, and hospital beds and staff. Several of those measures are on the site on their own. So a link with any of them is partly the index matching a part of itself.

Religiously unaffiliated

Share of the population religiously unaffiliated

Pew Research Center · via Our World in Data · Pew Research Center terms of use, excerpts with attribution · updated decennial · comparable from 2010 only

People who belong to no religion: atheists, agnostics and those who say "nothing in particular". Pew estimated it from censuses and surveys for 2010 and 2020. Belonging is a third thing, beside the attendance and importance measures already here. A country can be almost all affiliated and rarely attend, as much of Europe is. With only two years, nothing here shows a trend. No "better" direction is set.

How this was computed

Data used: most recent value in 2010-2025; values come from 2020–2023. 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 13,797 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Health coverage index and Religiously unaffiliated

This page shows that two measures go together. It does not show that Health coverage index changes Religiously unaffiliated, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.