placestats

Premature NCD mortality vs. Under-5 mortality

Fades after adjusting for income

Across 178 countries, Premature NCD mortality and Under-5 mortality 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 -0.01, which could easily be chance (q = 0.97, 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, 5.9 to 37 per 1,000 live births, premature ncd mortality is worse by 4.64% probability, ages 30-70 at the top of that range than the bottom. Comparing only countries with similar national income, the gap reverses, to 0.106% probability, ages 30-70 the other way.

Link before adjusting (r)+0.519p = 1.2e-13 · 178 countries
After adjusting for national income-0.010p = 0.897 · likely range [-0.16, +0.14]
p, allowing for regions0.952standard error 0.157 · 7 regions
Check for luck (q)0.975across 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.

Premature NCD mortality · % probability, ages 30-70link with income -0.70 · high
Under-5 mortality · per 1,000 live birthslink with income -0.86 · proxy

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

Premature NCD mortality · % probability, ages 30-70 →Under-5 mortality · per 1,000 live births →6.9%44.1%2116Afghanistan: 32.7% probability, ages 30-70, 53 per 1,000 live birthsAngola: 24.7% probability, ages 30-70, 49 per 1,000 live birthsAlbania: 10% probability, ages 30-70, 9.2 per 1,000 live birthsUnited Arab Emirates: 11.6% probability, ages 30-70, 4.8 per 1,000 live birthsArgentina: 13.4% probability, ages 30-70, 9.5 per 1,000 live birthsArmenia: 20.6% probability, ages 30-70, 9.6 per 1,000 live birthsAntigua and Barbuda: 12.1% probability, ages 30-70, 9.1 per 1,000 live birthsAustralia: 8.3% probability, ages 30-70, 3.6 per 1,000 live birthsAustria: 9.9% probability, ages 30-70, 3.3 per 1,000 live birthsAzerbaijan: 17.4% probability, ages 30-70, 17.9 per 1,000 live birthsBurundi: 24.8% probability, ages 30-70, 47.1 per 1,000 live birthsBelgium: 9.2% probability, ages 30-70, 3.7 per 1,000 live birthsBenin: 20.8% probability, ages 30-70, 74.7 per 1,000 live birthsBurkina Faso: 23.4% probability, ages 30-70, 74.9 per 1,000 live birthsBangladesh: 18.1% probability, ages 30-70, 30.5 per 1,000 live birthsBulgaria: 25.6% probability, ages 30-70, 5.7 per 1,000 live birthsBahrain: 14.8% probability, ages 30-70, 8.8 per 1,000 live birthsBahamas, The: 20.4% probability, ages 30-70, 12.4 per 1,000 live birthsBosnia and Herzegovina: 17.2% probability, ages 30-70, 6.9 per 1,000 live birthsBelarus: 23.8% probability, ages 30-70, 2.3 per 1,000 live birthsBelize: 15.4% probability, ages 30-70, 12.7 per 1,000 live birthsBolivia: 19.9% probability, ages 30-70, 15.7 per 1,000 live birthsBrazil: 14.5% probability, ages 30-70, 14.2 per 1,000 live birthsBarbados: 14% probability, ages 30-70, 9.8 per 1,000 live birthsBrunei Darussalam: 14.9% probability, ages 30-70, 9.9 per 1,000 live birthsBhutan: 15.9% probability, ages 30-70, 17.2 per 1,000 live birthsBotswana: 19% probability, ages 30-70, 33.3 per 1,000 live birthsCentral African Republic: 30.8% probability, ages 30-70, 89.7 per 1,000 live birthsCanada: 9.7% probability, ages 30-70, 5.4 per 1,000 live birthsSwitzerland: 7.5% probability, ages 30-70, 3.9 per 1,000 live birthsChile: 9.4% probability, ages 30-70, 6.8 per 1,000 live birthsChina: 15.9% probability, ages 30-70, 5.7 per 1,000 live birthsCote d'Ivoire: 22.7% probability, ages 30-70, 64.5 per 1,000 live birthsCameroon: 24.3% probability, ages 30-70, 64.8 per 1,000 live birthsCongo, Dem. Rep.: 25.1% probability, ages 30-70, 89.7 per 1,000 live birthsCongo, Rep.: 21.2% probability, ages 30-70, 39.1 per 1,000 live birthsColombia: 10.3% probability, ages 30-70, 11.5 per 1,000 live birthsComoros: 20.2% probability, ages 30-70, 39 per 1,000 live birthsCabo Verde: 17.2% probability, ages 30-70, 11.1 per 1,000 live birthsCosta Rica: 9.9% probability, ages 30-70, 10.4 per 1,000 live birthsCyprus: 8.5% probability, ages 30-70, 5 per 1,000 live birthsCzechia: 14.2% probability, ages 30-70, 2.6 per 1,000 live birthsGermany: 11.6% probability, ages 30-70, 3.7 per 1,000 live birthsDjibouti: 20.6% probability, ages 30-70, 48.9 per 1,000 live birthsDenmark: 10.7% probability, ages 30-70, 4 per 1,000 live birthsDominican Republic: 17.4% probability, ages 30-70, 30.6 per 1,000 live birthsAlgeria: 13.3% probability, ages 30-70, 21.6 per 1,000 live birthsEcuador: 13.2% probability, ages 30-70, 12.9 per 1,000 live birthsEgypt, Arab Rep.: 26% probability, ages 30-70, 22.4 per 1,000 live birthsSpain: 9.3% probability, ages 30-70, 3.2 per 1,000 live birthsEstonia: 15.5% probability, ages 30-70, 2 per 1,000 live birthsEthiopia: 16.8% probability, ages 30-70, 44.5 per 1,000 live birthsFinland: 9.6% probability, ages 30-70, 2.4 per 1,000 live birthsFiji: 37.9% probability, ages 30-70, 29.1 per 1,000 live birthsFrance: 10.2% probability, ages 30-70, 4.3 per 1,000 live birthsMicronesia, Fed. Sts.: 40.5% probability, ages 30-70, 22.4 per 1,000 live birthsGabon: 18.1% probability, ages 30-70, 32.6 per 1,000 live birthsUnited Kingdom: 11% probability, ages 30-70, 4.7 per 1,000 live birthsGeorgia: 22.1% probability, ages 30-70, 8.6 per 1,000 live birthsGhana: 22.2% probability, ages 30-70, 35.9 per 1,000 live birthsGuinea: 23.6% probability, ages 30-70, 92.1 per 1,000 live birthsGambia, The: 21.8% probability, ages 30-70, 42.4 per 1,000 live birthsGuinea-Bissau: 25.3% probability, ages 30-70, 67.3 per 1,000 live birthsEquatorial Guinea: 20.3% probability, ages 30-70, 68 per 1,000 live birthsGreece: 12% probability, ages 30-70, 3.8 per 1,000 live birthsGrenada: 17.1% probability, ages 30-70, 18 per 1,000 live birthsGuatemala: 14.6% probability, ages 30-70, 20.5 per 1,000 live birthsGuyana: 25.4% probability, ages 30-70, 25.2 per 1,000 live birthsHonduras: 17.8% probability, ages 30-70, 15 per 1,000 live birthsCroatia: 15.9% probability, ages 30-70, 5.6 per 1,000 live birthsHaiti: 31.6% probability, ages 30-70, 52.8 per 1,000 live birthsHungary: 21.7% probability, ages 30-70, 3.7 per 1,000 live birthsIndonesia: 21.9% probability, ages 30-70, 17.7 per 1,000 live birthsIndia: 23.6% probability, ages 30-70, 26.6 per 1,000 live birthsIreland: 9.6% probability, ages 30-70, 3.9 per 1,000 live birthsIran, Islamic Rep.: 13.9% probability, ages 30-70, 11.3 per 1,000 live birthsIraq: 22.7% probability, ages 30-70, 21.8 per 1,000 live birthsIceland: 8.5% probability, ages 30-70, 2.8 per 1,000 live birthsIsrael: 7.6% probability, ages 30-70, 3.3 per 1,000 live birthsItaly: 9.1% probability, ages 30-70, 2.7 per 1,000 live birthsJamaica: 20.2% probability, ages 30-70, 17.8 per 1,000 live birthsJordan: 11.6% probability, ages 30-70, 12.9 per 1,000 live birthsJapan: 8% probability, ages 30-70, 2.4 per 1,000 live birthsKazakhstan: 21.2% probability, ages 30-70, 9.4 per 1,000 live birthsKenya: 18% probability, ages 30-70, 38.8 per 1,000 live birthsKyrgyz Republic: 18.8% probability, ages 30-70, 16.8 per 1,000 live birthsCambodia: 22.6% probability, ages 30-70, 18.4 per 1,000 live birthsKiribati: 44.1% probability, ages 30-70, 53.1 per 1,000 live birthsKorea, Rep.: 6.9% probability, ages 30-70, 2.8 per 1,000 live birthsKuwait: 9.3% probability, ages 30-70, 8.1 per 1,000 live birthsLao PDR: 26.5% probability, ages 30-70, 29.4 per 1,000 live birthsLebanon: 11.9% probability, ages 30-70, 17.6 per 1,000 live birthsLiberia: 22% probability, ages 30-70, 86.4 per 1,000 live birthsLibya: 19.8% probability, ages 30-70, 9.8 per 1,000 live birthsSt. Lucia: 15.5% probability, ages 30-70, 17.2 per 1,000 live birthsSri Lanka: 13.9% probability, ages 30-70, 5.9 per 1,000 live birthsLesotho: 36.3% probability, ages 30-70, 60 per 1,000 live birthsLithuania: 19.8% probability, ages 30-70, 3.4 per 1,000 live birthsLuxembourg: 7.8% probability, ages 30-70, 2.2 per 1,000 live birthsLatvia: 22.7% probability, ages 30-70, 2.5 per 1,000 live birthsMorocco: 22% probability, ages 30-70, 15.7 per 1,000 live birthsMoldova: 24.7% probability, ages 30-70, 16.5 per 1,000 live birthsMadagascar: 25.9% probability, ages 30-70, 62.4 per 1,000 live birthsMaldives: 9% probability, ages 30-70, 5.4 per 1,000 live birthsMexico: 16.3% probability, ages 30-70, 13.1 per 1,000 live birthsNorth Macedonia: 19.6% probability, ages 30-70, 2.8 per 1,000 live birthsMali: 23% probability, ages 30-70, 73 per 1,000 live birthsMalta: 9.8% probability, ages 30-70, 5.3 per 1,000 live birthsMyanmar: 24% probability, ages 30-70, 36.9 per 1,000 live birthsMontenegro: 18% probability, ages 30-70, 2.4 per 1,000 live birthsMongolia: 26.3% probability, ages 30-70, 13.4 per 1,000 live birthsMozambique: 26.6% probability, ages 30-70, 59.4 per 1,000 live birthsMauritania: 18.7% probability, ages 30-70, 36.9 per 1,000 live birthsMauritius: 21.7% probability, ages 30-70, 15.4 per 1,000 live birthsMalawi: 24.9% probability, ages 30-70, 48.8 per 1,000 live birthsMalaysia: 19.9% probability, ages 30-70, 8.3 per 1,000 live birthsNamibia: 23.1% probability, ages 30-70, 39.5 per 1,000 live birthsNiger: 20.2% probability, ages 30-70, 111 per 1,000 live birthsNigeria: 17.7% probability, ages 30-70, 116 per 1,000 live birthsNicaragua: 12.6% probability, ages 30-70, 11.2 per 1,000 live birthsNetherlands: 9.9% probability, ages 30-70, 3.9 per 1,000 live birthsNorway: 7.8% probability, ages 30-70, 2.5 per 1,000 live birthsNepal: 19.4% probability, ages 30-70, 25.1 per 1,000 live birthsNew Zealand: 10.3% probability, ages 30-70, 4.7 per 1,000 live birthsOman: 14.6% probability, ages 30-70, 10.3 per 1,000 live birthsPakistan: 25.5% probability, ages 30-70, 56 per 1,000 live birthsPanama: 10.9% probability, ages 30-70, 15.3 per 1,000 live birthsPeru: 12.3% probability, ages 30-70, 12.9 per 1,000 live birthsPhilippines: 31.9% probability, ages 30-70, 26.5 per 1,000 live birthsPapua New Guinea: 28.5% probability, ages 30-70, 39.4 per 1,000 live birthsPoland: 17% probability, ages 30-70, 4.2 per 1,000 live birthsPortugal: 10.5% probability, ages 30-70, 3.2 per 1,000 live birthsParaguay: 16.1% probability, ages 30-70, 16.3 per 1,000 live birthsWest Bank and Gaza: 18.3% probability, ages 30-70, 37.9 per 1,000 live birthsQatar: 12.1% probability, ages 30-70, 5.9 per 1,000 live birthsRomania: 21.5% probability, ages 30-70, 7.3 per 1,000 live birthsRussian Federation: 22.4% probability, ages 30-70, 5.2 per 1,000 live birthsRwanda: 20% probability, ages 30-70, 37.7 per 1,000 live birthsSaudi Arabia: 13.6% probability, ages 30-70, 6 per 1,000 live birthsSudan: 21.2% probability, ages 30-70, 61.6 per 1,000 live birthsSenegal: 21.4% probability, ages 30-70, 36.5 per 1,000 live birthsSingapore: 10.3% probability, ages 30-70, 2.7 per 1,000 live birthsSolomon Islands: 40.6% probability, ages 30-70, 20 per 1,000 live birthsSierra Leone: 23.9% probability, ages 30-70, 90.5 per 1,000 live birthsEl Salvador: 12.6% probability, ages 30-70, 10 per 1,000 live birthsSomalia, Fed. Rep.: 27.6% probability, ages 30-70, 101 per 1,000 live birthsSerbia: 20.7% probability, ages 30-70, 5.4 per 1,000 live birthsSao Tome and Principe: 19.5% probability, ages 30-70, 13.6 per 1,000 live birthsSuriname: 18.7% probability, ages 30-70, 15.8 per 1,000 live birthsSlovak Republic: 16.6% probability, ages 30-70, 6.3 per 1,000 live birthsSlovenia: 11.6% probability, ages 30-70, 2.3 per 1,000 live birthsSweden: 7.9% probability, ages 30-70, 2.4 per 1,000 live birthsEswatini: 32.3% probability, ages 30-70, 45.1 per 1,000 live birthsSeychelles: 15.6% probability, ages 30-70, 14 per 1,000 live birthsSyrian Arab Republic: 21.3% probability, ages 30-70, 18.4 per 1,000 live birthsChad: 23.4% probability, ages 30-70, 97.3 per 1,000 live birthsTogo: 25.4% probability, ages 30-70, 56.1 per 1,000 live birthsThailand: 14.5% probability, ages 30-70, 9 per 1,000 live birthsTajikistan: 18.1% probability, ages 30-70, 28.1 per 1,000 live birthsTurkmenistan: 25.7% probability, ages 30-70, 39 per 1,000 live birthsTimor-Leste: 20.1% probability, ages 30-70, 47.6 per 1,000 live birthsTonga: 26.9% probability, ages 30-70, 9.5 per 1,000 live birthsTrinidad and Tobago: 20.3% probability, ages 30-70, 18.8 per 1,000 live birthsTunisia: 13% probability, ages 30-70, 12.1 per 1,000 live birthsTurkiye: 15.4% probability, ages 30-70, 9.6 per 1,000 live birthsTanzania: 18.8% probability, ages 30-70, 37 per 1,000 live birthsUganda: 21.5% probability, ages 30-70, 48.7 per 1,000 live birthsUkraine: 24.8% probability, ages 30-70, 7.9 per 1,000 live birthsUruguay: 17.4% probability, ages 30-70, 7.4 per 1,000 live birthsUnited States: 13.7% probability, ages 30-70, 6.5 per 1,000 live birthsUzbekistan: 24.6% probability, ages 30-70, 13.4 per 1,000 live birthsSt. Vincent and the Grenadines: 23.6% probability, ages 30-70, 11.3 per 1,000 live birthsViet Nam: 20.1% probability, ages 30-70, 17.3 per 1,000 live birthsVanuatu: 36.8% probability, ages 30-70, 17.1 per 1,000 live birthsSamoa: 32.3% probability, ages 30-70, 14.9 per 1,000 live birthsSouth Africa: 22.7% probability, ages 30-70, 35.1 per 1,000 live birthsZambia: 23.6% probability, ages 30-70, 48.4 per 1,000 live birthsZimbabwe: 31.2% probability, ages 30-70, 64.7 per 1,000 live birthsCAFFSMKIRKORLUXNERNGANORSLBSOMTCDVUT

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5191.2e-13178
By rank (Spearman), not adjusted+0.6811.2e-25178
Standard (Pearson), adjusted for national income-0.0100.897178
By rank (Spearman), adjusted for national income+0.2210.003178

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 178 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: +0.509 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.039 (without GUY) to +0.026 (without SLB). 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: SLB (+0.036).

Fragile: this link may not hold up.
  • sign flips when a single country is removed
  • correlation moves sharply once outliers are trimmed
  • sign flips once outliers are trimmed

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 & Pacific25+0.05
Europe & Central Asia48+0.00
Latin America & Caribbean29+0.70
Middle East, North Africa, Afghanistan & Pakistan22+0.44
Sub-Saharan Africa46+0.14

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 third60-0.17
Middle third59+0.37
Richest third59+0.39

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
Christians108+0.00
Muslims49+0.13

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
France25-0.05
Never a European colony21+0.07
Spain20+0.32
United Kingdom59+0.05

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 = +0.171 after dropping 13 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 22years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Within countries over time, there is no link that is clearly more than chance (r = -0.066, comparing each country only with itself over the years, and each year only with the same year elsewhere). Whatever the cross-country picture shows, countries whose premature ncd mortality moved did not tend to see their under-5 mortality move with it.

Across countries (adjusted)-0.010for comparison
Within countries+0.307each country vs itself
…and vs the same year elsewhere-0.066q = 0.456 · 184 countries
Year-on-year changes+0.007q = 0.885
The direction flips. Comparing each country only with itself gives +0.31. Also taking out what happened to the whole world each year gives -0.07. So the first figure was picking up a trend both measures share with worldwide progress, not a link between them.
Read with care.
  • Almost all of the second indicator's variation is between countries, so the within-country estimate rests on a small part of the data.
  • Much of the within-country association disappears once shared global year effects are removed, which points to a common worldwide trend rather than a country-level relationship.

4,048 country-years (one country in one year), 184 countries, 2000–2021, about 22 years each on average. Share of the variation that happens within countries over time: 14% for Premature NCD mortality, 9% for Under-5 mortality. The margins of error allow for each country appearing many times, and for each year’s value being close to the year before.

Year-to-year changes are a cautious test, not a final answer. Looking only at changes from one year to the next removes each country’s own trends. But it also makes measurement mistakes louder, which pulls the results toward zero. A near-zero result here is weak evidence of no link, not proof.

With one measure years behind the other

0.20−0.2-100+10years Under-5 mortality trails Premature NCD mortality →lag -10: r = -0.072 (n = 4,048)lag -9: r = -0.065 (n = 4,048)lag -8: r = -0.059 (n = 4,048)lag -7: r = -0.047 (n = 4,048)lag -6: r = -0.035 (n = 4,048)lag -5: r = -0.046 (n = 4,048)lag -4: r = -0.041 (n = 4,048)lag -3: r = -0.043 (n = 4,048)lag -2: r = -0.039 (n = 4,048)lag -1: r = -0.056 (n = 4,048)lag +0: r = -0.066 (n = 4,048)lag +1: r = -0.077 (n = 4,048)lag +2: r = -0.081 (n = 4,048)lag +3: r = -0.087 (n = 4,048)lag +4: r = -0.108 (n = 3,864)lag +5: r = -0.100 (n = 3,680)lag +6: r = -0.099 (n = 3,496)lag +7: r = -0.089 (n = 3,312)lag +8: r = -0.080 (n = 3,128)lag +9: r = -0.081 (n = 2,944)lag +10: r = -0.081 (n = 2,760)

Same year (lag 0): -0.066. A peak away from zero does not show which comes first. These series change slowly — this year’s value is close to last year’s. That makes the curve smooth and nearly symmetric, whatever produced the data. Even a sharp peak at one lag (a gap of some years) would not prove that one measure changes the other.

The data


% probability, ages 30-70

per 1,000 live births
Years
Kiribati KIR44.1%53.12021, 2024
Solomon Islands SLB40.6%202021, 2024
Micronesia, Fed. Sts. FSM40.5%22.42021, 2024
Fiji FJI37.9%29.12021, 2024
Vanuatu VUT36.8%17.12021, 2024
Lesotho LSO36.3%602021, 2024
Afghanistan AFG32.7%532021, 2024
Samoa WSM32.3%14.92021, 2024
Eswatini SWZ32.3%45.12021, 2024
Philippines PHL31.9%26.52021, 2024
Haiti HTI31.6%52.82021, 2024
Zimbabwe ZWE31.2%64.72021, 2024
Central African Republic CAF30.8%89.72021, 2024
Papua New Guinea PNG28.5%39.42021, 2024
Somalia, Fed. Rep. SOM27.6%1012021, 2024

World Bank, World Development Indicators
World Bank, World Development Indicators

Sources

Premature NCD mortality

Mortality from cardiovascular disease, cancer, diabetes or chronic respiratory disease between ages 30 and 70 (%)

World Health Organization · CC BY 4.0 · updated quarterly

The series ends in 2021.

Under-5 mortality

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

World Bank · CC BY 4.0 · updated quarterly

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 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 Premature NCD mortality and Under-5 mortality

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

More links with Premature NCD mortality or Under-5 mortality