placestats

Under-5 mortality vs. Wellbeing score

Fades after adjusting for income

Across 104 countries, Under-5 mortality and Wellbeing score rise and fall together at r = -0.56 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.01, which could easily be chance (q = 0.92, 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: sign flips when a single country is removed.

Comparing countries across the middle half of under-5 mortality, 3.88 to 17.4 per 1,000 live births, wellbeing score is worse by 0.311 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap reverses, to 0.00728 typical gaps the other way.

Link before adjusting (r)-0.556p = 9.0e-10 · 104 countries
After adjusting for national income+0.012p = 0.901 · likely range [-0.18, +0.21]
p, allowing for regions0.861standard error 0.068 · 7 regions
Check for luck (q)0.922across 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.

Under-5 mortality · per 1,000 live birthslink with income -0.86 · proxy
Wellbeing score · typical gaps (standard deviations)link with income +0.80 · 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

Under-5 mortality · per 1,000 live births →Wellbeing score · typical gaps (standard deviations) →2116-1.981.89Albania: 9.2 per 1,000 live births, -0.617 typical gaps (standard deviations)Andorra: 2.5 per 1,000 live births, 0.512 typical gaps (standard deviations)Argentina: 9.5 per 1,000 live births, 0.216 typical gaps (standard deviations)Armenia: 9.6 per 1,000 live births, -0.118 typical gaps (standard deviations)Australia: 3.6 per 1,000 live births, 1.25 typical gaps (standard deviations)Austria: 3.3 per 1,000 live births, 1.26 typical gaps (standard deviations)Azerbaijan: 17.9 per 1,000 live births, -0.0603 typical gaps (standard deviations)Belgium: 3.7 per 1,000 live births, 0.818 typical gaps (standard deviations)Burkina Faso: 74.9 per 1,000 live births, -0.476 typical gaps (standard deviations)Bangladesh: 30.5 per 1,000 live births, -0.561 typical gaps (standard deviations)Bulgaria: 5.7 per 1,000 live births, -0.572 typical gaps (standard deviations)Bosnia and Herzegovina: 6.9 per 1,000 live births, -0.087 typical gaps (standard deviations)Belarus: 2.3 per 1,000 live births, 0.732 typical gaps (standard deviations)Bolivia: 15.7 per 1,000 live births, -0.361 typical gaps (standard deviations)Brazil: 14.2 per 1,000 live births, 0.123 typical gaps (standard deviations)Canada: 5.4 per 1,000 live births, 1.06 typical gaps (standard deviations)Switzerland: 3.9 per 1,000 live births, 1.55 typical gaps (standard deviations)Chile: 6.8 per 1,000 live births, 0.19 typical gaps (standard deviations)China: 5.7 per 1,000 live births, 0.913 typical gaps (standard deviations)Colombia: 11.5 per 1,000 live births, -0.125 typical gaps (standard deviations)Cyprus: 5 per 1,000 live births, -0.0176 typical gaps (standard deviations)Czechia: 2.6 per 1,000 live births, 0.726 typical gaps (standard deviations)Germany: 3.7 per 1,000 live births, 0.981 typical gaps (standard deviations)Denmark: 4 per 1,000 live births, 1.89 typical gaps (standard deviations)Algeria: 21.6 per 1,000 live births, -0.205 typical gaps (standard deviations)Ecuador: 12.9 per 1,000 live births, -0.164 typical gaps (standard deviations)Egypt, Arab Rep.: 22.4 per 1,000 live births, -1.08 typical gaps (standard deviations)Spain: 3.2 per 1,000 live births, 0.816 typical gaps (standard deviations)Estonia: 2 per 1,000 live births, 0.622 typical gaps (standard deviations)Ethiopia: 44.5 per 1,000 live births, -0.726 typical gaps (standard deviations)Finland: 2.4 per 1,000 live births, 1.87 typical gaps (standard deviations)France: 4.3 per 1,000 live births, 0.717 typical gaps (standard deviations)United Kingdom: 4.7 per 1,000 live births, 1.07 typical gaps (standard deviations)Georgia: 8.6 per 1,000 live births, -0.493 typical gaps (standard deviations)Ghana: 35.9 per 1,000 live births, -0.73 typical gaps (standard deviations)Greece: 3.8 per 1,000 live births, -0.284 typical gaps (standard deviations)Guatemala: 20.5 per 1,000 live births, 0.352 typical gaps (standard deviations)Croatia: 5.6 per 1,000 live births, 0.0883 typical gaps (standard deviations)Haiti: 52.8 per 1,000 live births, -0.461 typical gaps (standard deviations)Hungary: 3.7 per 1,000 live births, 0.266 typical gaps (standard deviations)Indonesia: 17.7 per 1,000 live births, -0.192 typical gaps (standard deviations)India: 26.6 per 1,000 live births, -0.736 typical gaps (standard deviations)Ireland: 3.9 per 1,000 live births, 0.894 typical gaps (standard deviations)Iran, Islamic Rep.: 11.3 per 1,000 live births, -0.684 typical gaps (standard deviations)Iraq: 21.8 per 1,000 live births, -0.726 typical gaps (standard deviations)Iceland: 2.8 per 1,000 live births, 1.78 typical gaps (standard deviations)Italy: 2.7 per 1,000 live births, 0.438 typical gaps (standard deviations)Jordan: 12.9 per 1,000 live births, -0.666 typical gaps (standard deviations)Japan: 2.4 per 1,000 live births, 0.552 typical gaps (standard deviations)Kazakhstan: 9.4 per 1,000 live births, 0.304 typical gaps (standard deviations)Kenya: 38.8 per 1,000 live births, -0.678 typical gaps (standard deviations)Kyrgyz Republic: 16.8 per 1,000 live births, 0.225 typical gaps (standard deviations)Korea, Rep.: 2.8 per 1,000 live births, 0.475 typical gaps (standard deviations)Kuwait: 8.1 per 1,000 live births, 0.607 typical gaps (standard deviations)Lebanon: 17.6 per 1,000 live births, -1.54 typical gaps (standard deviations)Libya: 9.8 per 1,000 live births, -0.158 typical gaps (standard deviations)Lithuania: 3.4 per 1,000 live births, 0.51 typical gaps (standard deviations)Luxembourg: 2.2 per 1,000 live births, 0.652 typical gaps (standard deviations)Latvia: 2.5 per 1,000 live births, 0.212 typical gaps (standard deviations)Morocco: 15.7 per 1,000 live births, -0.382 typical gaps (standard deviations)Moldova: 16.5 per 1,000 live births, -1.29 typical gaps (standard deviations)Maldives: 5.4 per 1,000 live births, 0.0845 typical gaps (standard deviations)Mexico: 13.1 per 1,000 live births, 0.335 typical gaps (standard deviations)North Macedonia: 2.8 per 1,000 live births, -0.171 typical gaps (standard deviations)Mali: 73 per 1,000 live births, -0.328 typical gaps (standard deviations)Malta: 5.3 per 1,000 live births, 0.15 typical gaps (standard deviations)Myanmar: 36.9 per 1,000 live births, -0.547 typical gaps (standard deviations)Montenegro: 2.4 per 1,000 live births, 0.239 typical gaps (standard deviations)Mongolia: 13.4 per 1,000 live births, 0.000193 typical gaps (standard deviations)Malaysia: 8.3 per 1,000 live births, 0.215 typical gaps (standard deviations)Nigeria: 116 per 1,000 live births, -0.611 typical gaps (standard deviations)Nicaragua: 11.2 per 1,000 live births, 0.0736 typical gaps (standard deviations)Netherlands: 3.9 per 1,000 live births, 1.54 typical gaps (standard deviations)Norway: 2.5 per 1,000 live births, 1.82 typical gaps (standard deviations)New Zealand: 4.7 per 1,000 live births, 1.46 typical gaps (standard deviations)Pakistan: 56 per 1,000 live births, -0.299 typical gaps (standard deviations)Peru: 12.9 per 1,000 live births, -0.348 typical gaps (standard deviations)Philippines: 26.5 per 1,000 live births, -0.119 typical gaps (standard deviations)Poland: 4.2 per 1,000 live births, 0.505 typical gaps (standard deviations)Portugal: 3.2 per 1,000 live births, 0.195 typical gaps (standard deviations)West Bank and Gaza: 37.9 per 1,000 live births, -0.644 typical gaps (standard deviations)Qatar: 5.9 per 1,000 live births, 0.756 typical gaps (standard deviations)Romania: 7.3 per 1,000 live births, 0.197 typical gaps (standard deviations)Russian Federation: 5.2 per 1,000 live births, -0.00878 typical gaps (standard deviations)Rwanda: 37.7 per 1,000 live births, -0.867 typical gaps (standard deviations)Singapore: 2.7 per 1,000 live births, 0.779 typical gaps (standard deviations)Serbia: 5.4 per 1,000 live births, 0.105 typical gaps (standard deviations)Slovak Republic: 6.3 per 1,000 live births, 0.318 typical gaps (standard deviations)Slovenia: 2.3 per 1,000 live births, 0.55 typical gaps (standard deviations)Sweden: 2.4 per 1,000 live births, 1.7 typical gaps (standard deviations)Thailand: 9 per 1,000 live births, 0.256 typical gaps (standard deviations)Tajikistan: 28.1 per 1,000 live births, 0.104 typical gaps (standard deviations)Trinidad and Tobago: 18.8 per 1,000 live births, 0.0637 typical gaps (standard deviations)Tunisia: 12.1 per 1,000 live births, -0.73 typical gaps (standard deviations)Turkiye: 9.6 per 1,000 live births, -0.508 typical gaps (standard deviations)Ukraine: 7.9 per 1,000 live births, -0.244 typical gaps (standard deviations)Uruguay: 7.4 per 1,000 live births, 0.449 typical gaps (standard deviations)United States: 6.5 per 1,000 live births, 0.943 typical gaps (standard deviations)Uzbekistan: 13.4 per 1,000 live births, 0.617 typical gaps (standard deviations)Viet Nam: 17.3 per 1,000 live births, 0.469 typical gaps (standard deviations)Kosovo: 8.7 per 1,000 live births, -0.288 typical gaps (standard deviations)South Africa: 35.1 per 1,000 live births, -0.515 typical gaps (standard deviations)Zambia: 48.4 per 1,000 live births, -1.67 typical gaps (standard deviations)Zimbabwe: 64.7 per 1,000 live births, -1.98 typical gaps (standard deviations)BFABGRDNKFINLBNMDAMLINGANORZMBZWE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5569.0e-10104
By rank (Spearman), not adjusted-0.7487.6e-20104
Standard (Pearson), adjusted for national income+0.0120.901104
By rank (Spearman), adjusted for national income-0.1690.088104

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 104 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: +0.544 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.023 (without MLI) to +0.074 (without ZWE). 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: ZWE (+0.062).

Fragile: this link may not hold up.
  • sign flips when a single country is removed
  • sign flips once outliers are trimmed
  • direction is not consistent across regions

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.

nr
East Asia & Pacific13-0.36
Europe & Central Asia49+0.05
Latin America & Caribbean13-0.00
Middle East, North Africa, Afghanistan & Pakistan14+0.39

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.

nr
Poorest third35-0.19
Middle third34-0.32
Richest third35-0.21

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.

nr
Christians61-0.11
Muslims29+0.03

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.

nr
Never a European colony15-0.44
Spain12+0.13
United Kingdom25-0.08

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 = -0.077 after dropping 11 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


per 1,000 live births

typical gaps (standard deviations)
Years
Nigeria NGA116-0.6112024, 2022
Burkina Faso BFA74.9-0.4762024, 2010
Mali MLI73-0.3282024, 2010
Zimbabwe ZWE64.7-1.982024, 2022
Pakistan PAK56-0.2992024, 2022
Haiti HTI52.8-0.4612024, 2014
Zambia ZMB48.4-1.672024, 2010
Ethiopia ETH44.5-0.7262024, 2022
Kenya KEN38.8-0.6782024, 2022
West Bank and Gaza PSE37.9-0.6442024, 2014
Rwanda RWA37.7-0.8672024, 2014
Myanmar MMR36.9-0.5472024, 2022
Ghana GHA35.9-0.732024, 2014
South Africa ZAF35.1-0.5152024, 2014
Bangladesh BGD30.5-0.5612024, 2022

World Bank, World Development Indicators
ivs; whr

Sources

Under-5 mortality

Mortality rate, under-5 (per 1,000 live births)

World Bank · CC BY 4.0 · updated quarterly

Wellbeing score

Wellbeing score

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

The average of 3 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: Self-reported happiness, Interpersonal trust, Life satisfaction.

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2024. 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 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 Under-5 mortality and Wellbeing score

This page shows that two measures go together. It does not show that Under-5 mortality changes Wellbeing score, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Under-5 mortality or Wellbeing score