Across 181 countries, Health coverage index and Labour score rise and fall together at r = +0.67 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.15, which could easily be chance (q = 0.17, 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 health coverage index, 57 to 81 points, labour score is better by 0.693 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.217 typical gaps.
Link before adjusting (r)+0.673p = 3.4e-25 · 181 countries
After adjusting for national income+0.147p = 0.049 · likely range [+0.00, +0.29]
p, allowing for regions0.043standard error 0.057 · 7 regions
Check for luck (q)0.166across 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 coverage index · index, 0 to 100link with income +0.88 · proxy
Labour score · typical gaps (standard deviations)link with income +0.79 · 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
best-fit line line after adjusting
Four ways to measure the link
Method
r
p
Countries
Standard (Pearson), not adjusted
+0.673
3.4e-25
181
By rank (Spearman), not adjusted
+0.752
3.5e-34
181
Standard (Pearson), adjusted for national income
+0.147
0.049
181
By rank (Spearman), adjusted for national income
+0.193
0.010
181
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 181 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: +0.526 (a minus sign means it grew).
How solid is it?
Leaving out one country at a time, r ranges from +0.113 (without GAB) to +0.179 (without SWZ). 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: GAB (-0.034).
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
28
+0.08
Europe & Central Asia
48
+0.51
Latin America & Caribbean
29
+0.24
Middle East, North Africa, Afghanistan & Pakistan
22
+0.47
Sub-Saharan Africa
46
-0.02
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
61
+0.25
Middle third
60
+0.20
Richest third
60
+0.12
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
107
+0.17
Muslims
49
+0.11
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
+0.36
Never a European colony
21
+0.47
Spain
19
-0.12
United Kingdom
61
-0.00
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 = +0.123 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
index, 0 to 100
typical gaps (standard deviations)
Years
Canada CAN
92
0.581
2023, 2025
Iceland ISL
90
0.919
2023, 2025
New Zealand NZL
89
0.721
2023, 2025
Norway NOR
89
0.915
2023, 2025
Australia AUS
89
0.867
2023, 2025
United States USA
88
0.862
2023, 2025
Singapore SGP
88
1.05
2023, 2025
Korea, Rep. KOR
88
0.822
2023, 2025
United Kingdom GBR
88
0.635
2023, 2025
Germany DEU
87
0.988
2023, 2025
Switzerland CHE
87
0.916
2023, 2025
Japan JPN
86
1.03
2023, 2025
Finland FIN
86
0.419
2023, 2025
Belgium BEL
86
0.682
2023, 2025
Uruguay URY
85
0.298
2023, 2025
World Health Organization, Global Health Observatory un_sdg; wdi
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.
PlaceStats · via PlaceStats · Derived work; each member keeps its own licence · updated recomputed with the panel
The average of 4 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: Informal employment, Vulnerable employment, Youth not in work or study, Unemployment.
How this was computed
Data used: most recent value in 2010-2025; values come from 2018–2025. 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 coverage index and Labour score
This page shows that two measures go together. It does not show that Health coverage index changes Labour score, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.
More links with Health coverage index or Labour score