placestats

Adolescent fertility vs. Undernourishment

Fades after adjusting for income

Across 163 countries, Adolescent fertility and Undernourishment rise and fall together at r = +0.66 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.22, which could easily be chance (q = 0.28, 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: direction is not consistent across regions.

Comparing countries across the middle half of adolescent fertility, 8.38 to 63 births per 1,000 women aged 15-19, undernourishment is worse by 9.81% of population at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 3.67% of population.

Link before adjusting (r)+0.664p = 4.8e-22 · 163 countries
After adjusting for national income+0.220p = 0.005 · likely range [+0.07, +0.36]
p, allowing for regions0.108standard error 0.116 · 7 regions
Check for luck (q)0.282across 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.

Adolescent fertility · births per 1,000 women aged 15-19link with income -0.81 · proxy
Undernourishment · % of populationlink with income -0.83 · 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

Adolescent fertility · births per 1,000 women aged 15-19 →Undernourishment · % of population →0.4781612.5%54.2%Afghanistan: 61.5 births per 1,000 women aged 15-19, 28.1% of populationAngola: 139 births per 1,000 women aged 15-19, 22.5% of populationAlbania: 12.4 births per 1,000 women aged 15-19, 5.4% of populationUnited Arab Emirates: 2.82 births per 1,000 women aged 15-19, 2.5% of populationArgentina: 25.6 births per 1,000 women aged 15-19, 3.4% of populationArmenia: 12.8 births per 1,000 women aged 15-19, 2.5% of populationAustralia: 6.42 births per 1,000 women aged 15-19, 2.5% of populationAustria: 3.6 births per 1,000 women aged 15-19, 2.5% of populationAzerbaijan: 34.9 births per 1,000 women aged 15-19, 2.5% of populationBelgium: 3.5 births per 1,000 women aged 15-19, 2.5% of populationBenin: 76.4 births per 1,000 women aged 15-19, 14.3% of populationBurkina Faso: 85.5 births per 1,000 women aged 15-19, 13.1% of populationBangladesh: 70.8 births per 1,000 women aged 15-19, 10.4% of populationBulgaria: 38 births per 1,000 women aged 15-19, 2.5% of populationBosnia and Herzegovina: 10.8 births per 1,000 women aged 15-19, 2.5% of populationBelarus: 8.17 births per 1,000 women aged 15-19, 2.5% of populationBelize: 55.6 births per 1,000 women aged 15-19, 7% of populationBolivia: 64.4 births per 1,000 women aged 15-19, 21.8% of populationBrazil: 41.5 births per 1,000 women aged 15-19, 2.5% of populationBarbados: 45 births per 1,000 women aged 15-19, 4.4% of populationBotswana: 53.5 births per 1,000 women aged 15-19, 24% of populationCentral African Republic: 161 births per 1,000 women aged 15-19, 29.8% of populationCanada: 4.5 births per 1,000 women aged 15-19, 2.5% of populationSwitzerland: 1.48 births per 1,000 women aged 15-19, 2.5% of populationChile: 5.61 births per 1,000 women aged 15-19, 2.5% of populationChina: 5.2 births per 1,000 women aged 15-19, 2.5% of populationCote d'Ivoire: 90.6 births per 1,000 women aged 15-19, 11.1% of populationCameroon: 105 births per 1,000 women aged 15-19, 4.8% of populationCongo, Dem. Rep.: 105 births per 1,000 women aged 15-19, 38.5% of populationCongo, Rep.: 108 births per 1,000 women aged 15-19, 26.4% of populationColombia: 58.4 births per 1,000 women aged 15-19, 3.9% of populationComoros: 53.8 births per 1,000 women aged 15-19, 15.4% of populationCabo Verde: 37.9 births per 1,000 women aged 15-19, 13.5% of populationCosta Rica: 24.8 births per 1,000 women aged 15-19, 2.5% of populationCyprus: 6.98 births per 1,000 women aged 15-19, 2.5% of populationCzechia: 5.75 births per 1,000 women aged 15-19, 2.5% of populationGermany: 5.24 births per 1,000 women aged 15-19, 2.5% of populationDjibouti: 19.1 births per 1,000 women aged 15-19, 12.9% of populationDominica: 34 births per 1,000 women aged 15-19, 3.6% of populationDenmark: 1.06 births per 1,000 women aged 15-19, 2.5% of populationDominican Republic: 50.2 births per 1,000 women aged 15-19, 3.6% of populationAlgeria: 8.58 births per 1,000 women aged 15-19, 2.5% of populationEcuador: 54.3 births per 1,000 women aged 15-19, 12.1% of populationEgypt, Arab Rep.: 41.1 births per 1,000 women aged 15-19, 9.4% of populationSpain: 4.85 births per 1,000 women aged 15-19, 2.5% of populationEstonia: 4.67 births per 1,000 women aged 15-19, 2.5% of populationEthiopia: 68.2 births per 1,000 women aged 15-19, 19.7% of populationFinland: 2.99 births per 1,000 women aged 15-19, 2.5% of populationFiji: 20.9 births per 1,000 women aged 15-19, 6.8% of populationFrance: 3.3 births per 1,000 women aged 15-19, 2.5% of populationGabon: 89.5 births per 1,000 women aged 15-19, 25.3% of populationUnited Kingdom: 7.82 births per 1,000 women aged 15-19, 2.5% of populationGeorgia: 19.4 births per 1,000 women aged 15-19, 2.5% of populationGhana: 57.4 births per 1,000 women aged 15-19, 6.3% of populationGuinea: 117 births per 1,000 women aged 15-19, 11.4% of populationGambia, The: 56.1 births per 1,000 women aged 15-19, 16.8% of populationGuinea-Bissau: 80.3 births per 1,000 women aged 15-19, 22.1% of populationGreece: 6.85 births per 1,000 women aged 15-19, 2.5% of populationGuatemala: 67.9 births per 1,000 women aged 15-19, 11.8% of populationGuyana: 68.5 births per 1,000 women aged 15-19, 2.5% of populationHong Kong SAR, China: 1.15 births per 1,000 women aged 15-19, 3.1% of populationHonduras: 81.3 births per 1,000 women aged 15-19, 14.8% of populationCroatia: 6.31 births per 1,000 women aged 15-19, 2.5% of populationHaiti: 49.3 births per 1,000 women aged 15-19, 54.2% of populationHungary: 17.4 births per 1,000 women aged 15-19, 2.5% of populationIndonesia: 25.6 births per 1,000 women aged 15-19, 6.3% of populationIndia: 13 births per 1,000 women aged 15-19, 12% of populationIreland: 4.01 births per 1,000 women aged 15-19, 2.5% of populationIran, Islamic Rep.: 25.8 births per 1,000 women aged 15-19, 6.8% of populationIraq: 57.3 births per 1,000 women aged 15-19, 14.9% of populationIceland: 3.07 births per 1,000 women aged 15-19, 2.5% of populationIsrael: 5.7 births per 1,000 women aged 15-19, 2.5% of populationItaly: 2.87 births per 1,000 women aged 15-19, 2.5% of populationJamaica: 36.1 births per 1,000 women aged 15-19, 7.7% of populationJordan: 17.7 births per 1,000 women aged 15-19, 14.3% of populationKazakhstan: 17.4 births per 1,000 women aged 15-19, 2.5% of populationKenya: 54.5 births per 1,000 women aged 15-19, 36.8% of populationKyrgyz Republic: 27.5 births per 1,000 women aged 15-19, 5.1% of populationCambodia: 47.3 births per 1,000 women aged 15-19, 5.2% of populationKiribati: 44 births per 1,000 women aged 15-19, 4.1% of populationKorea, Rep.: 0.532 births per 1,000 women aged 15-19, 2.5% of populationKuwait: 1.43 births per 1,000 women aged 15-19, 2.5% of populationLebanon: 20.7 births per 1,000 women aged 15-19, 8.7% of populationLiberia: 125 births per 1,000 women aged 15-19, 35.5% of populationLibya: 5.83 births per 1,000 women aged 15-19, 16.5% of populationSri Lanka: 14.7 births per 1,000 women aged 15-19, 7.4% of populationLithuania: 5.52 births per 1,000 women aged 15-19, 2.5% of populationLuxembourg: 4 births per 1,000 women aged 15-19, 2.5% of populationLatvia: 7.25 births per 1,000 women aged 15-19, 2.5% of populationMacao SAR, China: 0.478 births per 1,000 women aged 15-19, 11.2% of populationMorocco: 24.8 births per 1,000 women aged 15-19, 7% of populationMoldova: 22.7 births per 1,000 women aged 15-19, 2.5% of populationMadagascar: 129 births per 1,000 women aged 15-19, 39.5% of populationMexico: 59.3 births per 1,000 women aged 15-19, 2.7% of populationNorth Macedonia: 12.4 births per 1,000 women aged 15-19, 2.5% of populationMali: 136 births per 1,000 women aged 15-19, 12.3% of populationMalta: 10 births per 1,000 women aged 15-19, 2.5% of populationMyanmar: 33.2 births per 1,000 women aged 15-19, 5.4% of populationMontenegro: 8.71 births per 1,000 women aged 15-19, 2.5% of populationMongolia: 19 births per 1,000 women aged 15-19, 2.5% of populationMozambique: 152 births per 1,000 women aged 15-19, 21.8% of populationMauritania: 87.6 births per 1,000 women aged 15-19, 8.7% of populationMauritius: 19.2 births per 1,000 women aged 15-19, 8.7% of populationMalawi: 113 births per 1,000 women aged 15-19, 21.4% of populationMalaysia: 5.72 births per 1,000 women aged 15-19, 2.5% of populationNamibia: 65.9 births per 1,000 women aged 15-19, 18.1% of populationNiger: 142 births per 1,000 women aged 15-19, 12.9% of populationNigeria: 84 births per 1,000 women aged 15-19, 19.9% of populationNicaragua: 93.2 births per 1,000 women aged 15-19, 17.3% of populationNetherlands: 1.75 births per 1,000 women aged 15-19, 2.5% of populationNorway: 1.28 births per 1,000 women aged 15-19, 2.5% of populationNepal: 66.5 births per 1,000 women aged 15-19, 5.3% of populationNew Zealand: 10.3 births per 1,000 women aged 15-19, 2.5% of populationOman: 5.65 births per 1,000 women aged 15-19, 5.9% of populationPakistan: 39.9 births per 1,000 women aged 15-19, 16.5% of populationPanama: 55.9 births per 1,000 women aged 15-19, 5.7% of populationPeru: 42.9 births per 1,000 women aged 15-19, 6.9% of populationPhilippines: 31.3 births per 1,000 women aged 15-19, 3% of populationPapua New Guinea: 53.5 births per 1,000 women aged 15-19, 28.7% of populationPoland: 5.85 births per 1,000 women aged 15-19, 2.5% of populationPortugal: 6.57 births per 1,000 women aged 15-19, 2.5% of populationParaguay: 70.2 births per 1,000 women aged 15-19, 5.2% of populationRomania: 32.8 births per 1,000 women aged 15-19, 2.5% of populationRussian Federation: 12.2 births per 1,000 women aged 15-19, 2.5% of populationRwanda: 30.6 births per 1,000 women aged 15-19, 24.4% of populationSaudi Arabia: 11.1 births per 1,000 women aged 15-19, 2.5% of populationSudan: 64.5 births per 1,000 women aged 15-19, 11% of populationSenegal: 59.1 births per 1,000 women aged 15-19, 5.1% of populationSolomon Islands: 49.4 births per 1,000 women aged 15-19, 20% of populationSierra Leone: 91.2 births per 1,000 women aged 15-19, 24.1% of populationEl Salvador: 53.5 births per 1,000 women aged 15-19, 6.7% of populationSomalia, Fed. Rep.: 115 births per 1,000 women aged 15-19, 53.2% of populationSerbia: 13.1 births per 1,000 women aged 15-19, 2.5% of populationSao Tome and Principe: 85.2 births per 1,000 women aged 15-19, 17.4% of populationSuriname: 46.9 births per 1,000 women aged 15-19, 9.7% of populationSlovak Republic: 24.5 births per 1,000 women aged 15-19, 3.1% of populationSlovenia: 3.38 births per 1,000 women aged 15-19, 2.5% of populationSweden: 1.7 births per 1,000 women aged 15-19, 2.5% of populationEswatini: 68.2 births per 1,000 women aged 15-19, 14.7% of populationSeychelles: 53.5 births per 1,000 women aged 15-19, 2.5% of populationSyrian Arab Republic: 38.6 births per 1,000 women aged 15-19, 39% of populationChad: 132 births per 1,000 women aged 15-19, 32% of populationTogo: 76.4 births per 1,000 women aged 15-19, 9.1% of populationThailand: 25 births per 1,000 women aged 15-19, 4.6% of populationTajikistan: 39.4 births per 1,000 women aged 15-19, 8.4% of populationTurkmenistan: 20.1 births per 1,000 women aged 15-19, 4.3% of populationTimor-Leste: 26.8 births per 1,000 women aged 15-19, 18.7% of populationTrinidad and Tobago: 36 births per 1,000 women aged 15-19, 11.2% of populationTunisia: 4.21 births per 1,000 women aged 15-19, 3% of populationTurkiye: 11.2 births per 1,000 women aged 15-19, 2.5% of populationTanzania: 113 births per 1,000 women aged 15-19, 20.2% of populationUganda: 105 births per 1,000 women aged 15-19, 22% of populationUkraine: 10.9 births per 1,000 women aged 15-19, 6.9% of populationUruguay: 25.1 births per 1,000 women aged 15-19, 2.5% of populationUnited States: 12.4 births per 1,000 women aged 15-19, 2.5% of populationUzbekistan: 34.1 births per 1,000 women aged 15-19, 2.5% of populationSt. Vincent and the Grenadines: 40.8 births per 1,000 women aged 15-19, 6.1% of populationViet Nam: 33.9 births per 1,000 women aged 15-19, 5.3% of populationVanuatu: 65.8 births per 1,000 women aged 15-19, 7.2% of populationSamoa: 43.5 births per 1,000 women aged 15-19, 3.6% of populationSouth Africa: 51.8 births per 1,000 women aged 15-19, 10% of populationZambia: 115 births per 1,000 women aged 15-19, 37.2% of populationZimbabwe: 95.5 births per 1,000 women aged 15-19, 19.7% of populationCAFCMRDNKHTIKENKORMDGMLINERNORSOMSYR

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.6644.8e-22163
By rank (Spearman), not adjusted+0.7607.0e-32163
Standard (Pearson), adjusted for national income+0.2200.005163
By rank (Spearman), adjusted for national income+0.2400.002163

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 163 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: +0.444 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.192 (without GAB) to +0.289 (without HTI). 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: HTI (+0.069).

Fragile: this link may not hold up.
  • 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 & Pacific21+0.01
Europe & Central Asia48-0.13
Latin America & Caribbean26-0.02
Middle East, North Africa, Afghanistan & Pakistan19+0.28
Sub-Saharan Africa43+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.

nr
Poorest third55+0.10
Middle third54+0.46
Richest third54+0.20

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
Christians100+0.22
Muslims44+0.04

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
France24-0.07
Never a European colony20+0.50
Spain18+0.47
United Kingdom48+0.38

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 = +0.297 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.

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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 23years. 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 = +0.050, 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 adolescent fertility moved did not tend to see their undernourishment move with it.

Across countries (adjusted)+0.220for comparison
Within countries+0.224each country vs itself
…and vs the same year elsewhere+0.050q = 0.661 · 168 countries
Year-on-year changes+0.025q = 0.737
Read with care.
  • Almost all of this indicator's variation is between countries, not within them, so the within-country estimate rests on a small part of the data.

3,827 country-years (one country in one year), 168 countries, 2001–2023, about 23 years each on average. Share of the variation that happens within countries over time: 5% for Adolescent fertility, 13% for Undernourishment. 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 Undernourishment trails Adolescent fertility →lag -10: r = 0.123 (n = 2,330)lag -9: r = 0.114 (n = 2,496)lag -8: r = 0.102 (n = 2,662)lag -7: r = 0.091 (n = 2,833)lag -6: r = 0.082 (n = 3,000)lag -5: r = 0.075 (n = 3,166)lag -4: r = 0.069 (n = 3,332)lag -3: r = 0.062 (n = 3,498)lag -2: r = 0.054 (n = 3,663)lag -1: r = 0.050 (n = 3,827)lag +0: r = 0.050 (n = 3,827)lag +1: r = 0.048 (n = 3,827)lag +2: r = 0.047 (n = 3,827)lag +3: r = 0.046 (n = 3,827)lag +4: r = 0.046 (n = 3,827)lag +5: r = 0.048 (n = 3,827)lag +6: r = 0.048 (n = 3,827)lag +7: r = 0.049 (n = 3,827)lag +8: r = 0.049 (n = 3,827)lag +9: r = 0.045 (n = 3,827)lag +10: r = 0.038 (n = 3,827)

Same year (lag 0): +0.050. 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.

This curve peaks at the edge of the window (lag -10), so it is still drifting where the search stops. That pattern usually reflects a slow trend left over in the data, not a link with real timing. The peak value should not be read as the “true” link at the right lag.

The data


births per 1,000 women aged 15-19
% of population		Years
Central African Republic CAF16129.8%2024, 2023
Mozambique MOZ15221.8%2024, 2023
Niger NER14212.9%2024, 2023
Angola AGO13922.5%2024, 2023
Mali MLI13612.3%2024, 2023
Chad TCD13232%2024, 2023
Madagascar MDG12939.5%2024, 2023
Liberia LBR12535.5%2024, 2023
Guinea GIN11711.4%2024, 2023
Zambia ZMB11537.2%2024, 2023
Somalia, Fed. Rep. SOM11553.2%2024, 2023
Malawi MWI11321.4%2024, 2023
Tanzania TZA11320.2%2024, 2023
Congo, Rep. COG10826.4%2024, 2023
Cameroon CMR1054.8%2024, 2023

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

Sources

Adolescent fertility

Adolescent fertility rate (births per 1,000 women ages 15-19)

UN Population Division, World Population Prospects · CC BY 4.0 · updated quarterly

Undernourishment

Prevalence of undernourishment (% of population)

Food and Agriculture Organization · CC BY 4.0 · updated quarterly

Estimated from the food supply and how it is shared out, not by asking anyone. It is the FAO's model of how many people get less food energy than they need. The survey-based food insecurity measure below is treated as measuring the same thing. So their pair reads as two tools agreeing, not as a finding.

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 Adolescent fertility and Undernourishment

This page shows that two measures go together. It does not show that Adolescent fertility changes Undernourishment, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Adolescent fertility or Undernourishment