Do Health score and Public social spending go together across countries?

Across 42 countries the link before adjusting for anything is r = +0.52, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives +0.47.

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 score cause Public social spending?

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 score vs. Public social spending

Fades after adjusting for income

Across 42 countries, Health score and Public social spending rise and fall together at r = +0.52 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.37, which could easily be chance (q = 0.065, 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: leave-one-out range spans 0.18 in r.

Comparing countries across the middle half of public social spending, 17% to 24.5% of GDP, health score is better by 0.262 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.181 typical gaps.

Link before adjusting (r)+0.521p = 0.000 · 42 countries

After adjusting for national income+0.370p = 0.017 · likely range [+0.07, +0.61]

p, allowing for regions0.092standard error 0.168 · 5 regions

Check for luck (q)0.065across 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.

Health score · typical gaps (standard deviations)link with income +0.32 · moderate

Public social spending · % of GDPlink with income +0.44 · 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	+0.521	0.000	42
By rank (Spearman), not adjusted	+0.474	0.002	42
Standard (Pearson), adjusted for national income	+0.370	0.017	42
By rank (Spearman), adjusted for national income	+0.312	0.047	42

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 42 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: +0.151 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.253 (without IRL) to +0.430 (without CHE). 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: IRL (-0.117).

Fragile: this link may not hold up.

leave-one-out range spans 0.18 in r

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	30	+0.44

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	14	+0.23
Middle third	14	+0.06
Richest third	14	+0.29

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	35	+0.58

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 = +0.370 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

	typical gaps (standard deviations)	% of GDP	Years
Japan JPN	0.971	24.7%	2023, 2022
Switzerland CHE	0.82	16%	2023, 2024
Norway NOR	0.746	24.1%	2023, 2024
France FRA	0.734	30.6%	2023, 2024
Austria AUT	0.731	31.6%	2023, 2024
Korea, Rep. KOR	0.724	15.3%	2024
Sweden SWE	0.696	26.1%	2023, 2024
Spain ESP	0.665	25.9%	2023, 2024
Canada CAN	0.62	19.3%	2023, 2022
Israel ISR	0.604	16.3%	2023
Finland FIN	0.577	31.4%	2023, 2024
Denmark DNK	0.495	26.4%	2024
Netherlands NLD	0.491	18.9%	2024
Italy ITA	0.463	27.6%	2024
Slovak Republic SVK	0.319	19.3%	2023

wdi; who_gho
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

Health score

PlaceStats · via PlaceStats · Derived work; each member keeps its own licence · updated recomputed with the panel

The average of 23 measures from 2 publishers. Each measure is first put on a common scale: 0 is the average country in an average year, and 1 is a typical gap between countries (a standard deviation). Each is turned so that higher is better. Measures are averaged within each publisher first, so a publisher with many measures does not count for more. Members: Anaemia in women, HIV prevalence, Under-5 mortality, Premature NCD mortality, Basic water access, DTP3 immunisation, Physicians, Tobacco use, Basic sanitation, Skilled birth attendance, Maternal mortality, Child stunting, Suicide rate, Road traffic deaths, Tuberculosis incidence, Out-of-pocket health spending, Undernourishment, Food insecurity, Adolescent fertility, Infant mortality, Life expectancy, Adult obesity, Health coverage index.

Public social spending

Public social expenditure

OECD · via Our World in Data · CC BY 4.0 (OECD terms and conditions) · updated annual, except the snapshots noted per indicator · comparable from 1980 only

All public social spending, as a share of GDP: pensions, health, family, unemployment, housing and the rest. The figures before 1980 are stitched together from older OECD tables and from Lindert's historical estimates, so they are left out. The OECD's social spending database (SOCX) itself starts in 1980. The four spending areas below are parts of this total and are flagged as such.

How this was computed

Data used: most recent value in 2010-2025; values come from 2021–2024. 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 5 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 Health score and Public social spending

This page shows that two measures go together. It does not show that Health score changes Public social spending, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.