Across 186 countries, Health score and Population 65+ rise and fall together at r = +0.45 (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 = +0.36, q = 0.047, allowing for the many pairs tested).
Comparing countries across the middle half of population 65+, 3.9% to 16.2% of population, health score is better by 0.34 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.37 typical gaps.
Link before adjusting (r)+0.455p = 7.1e-11 · 186 countries
After adjusting for national income+0.356p = 6.5e-7 · likely range [+0.22, +0.48]
p, allowing for regions0.024standard error 0.118 · 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.
Health score · typical gaps (standard deviations)link with income +0.32 · moderate
Population 65+ · % of populationlink with income +0.76 · 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
+0.455
7.1e-11
186
By rank (Spearman), not adjusted
+0.404
1.1e-8
186
Standard (Pearson), adjusted for national income
+0.356
6.5e-7
186
By rank (Spearman), adjusted for national income
+0.265
0.000
186
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 186 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: +0.098 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from +0.332 (without QAT) to +0.380 (without TUV). 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 (-0.025).
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
29
+0.30
Europe & Central Asia
50
+0.01
Latin America & Caribbean
31
+0.50
Middle East, North Africa, Afghanistan & Pakistan
22
+0.34
Sub-Saharan Africa
46
+0.18
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
62
-0.14
Middle third
62
+0.30
Richest third
62
+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
+0.39
Muslims
49
+0.24
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.
n
r
France
25
+0.09
Never a European colony
21
+0.59
Spain
20
+0.24
United Kingdom
63
+0.29
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 = +0.380 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.
Loading…
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 population
Years
Japan JPN
0.971
30%
2023, 2025
Switzerland CHE
0.82
20.4%
2023, 2025
San Marino SMR
0.819
23.1%
2023, 2025
China CHN
0.798
14.9%
2023, 2025
Viet Nam VNM
0.794
9.49%
2024, 2025
Norway NOR
0.746
19.1%
2023, 2025
France FRA
0.734
22.5%
2023, 2025
Austria AUT
0.731
21.1%
2023, 2025
Korea, Rep. KOR
0.724
20.3%
2024, 2025
Sweden SWE
0.696
20.9%
2023, 2025
Spain ESP
0.665
21.6%
2023, 2025
Canada CAN
0.62
20.3%
2023, 2025
Israel ISR
0.604
12.7%
2023, 2025
Andorra AND
0.584
16.6%
2023, 2025
Finland FIN
0.577
24.2%
2023, 2025
wdi; who_gho World Bank, World Development Indicators
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.
Data used: most recent value in 2010-2025; values come from 2021–2025. 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 Health score and Population 65+
This page shows that two measures go together. It does not show that Health score changes Population 65+, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.