placestats

Fixed broadband vs. Undernourishment

Fades after adjusting for income

Across 163 countries, Fixed broadband and Undernourishment rise and fall together at r = -0.62 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.02, which could easily be chance (q = 0.71, 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 undernourishment, 2.5% to 13.9% of population, fixed broadband is worse by 10.9 per 100 people at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.323 per 100 people.

Link before adjusting (r)-0.625p = 5.2e-19 · 163 countries
After adjusting for national income-0.025p = 0.755 · likely range [-0.18, +0.13]
p, allowing for regions0.543standard error 0.038 · 7 regions
Check for luck (q)0.705across 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.

Fixed broadband · per 100 peoplelink with income +0.88 · 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

Fixed broadband · per 100 people →Undernourishment · % of population →048.92.5%54.2%Afghanistan: 0.0801 per 100 people, 28.1% of populationAngola: 0.363 per 100 people, 22.5% of populationAlbania: 24.9 per 100 people, 5.4% of populationUnited Arab Emirates: 40.8 per 100 people, 2.5% of populationArgentina: 26.1 per 100 people, 3.4% of populationArmenia: 20.3 per 100 people, 2.5% of populationAustralia: 36.5 per 100 people, 2.5% of populationAustria: 30.1 per 100 people, 2.5% of populationAzerbaijan: 21.8 per 100 people, 2.5% of populationBelgium: 44.2 per 100 people, 2.5% of populationBenin: 0.277 per 100 people, 14.3% of populationBurkina Faso: 0.851 per 100 people, 13.1% of populationBangladesh: 8.09 per 100 people, 10.4% of populationBulgaria: 37 per 100 people, 2.5% of populationBosnia and Herzegovina: 29.4 per 100 people, 2.5% of populationBelarus: 36.3 per 100 people, 2.5% of populationBelize: 9.75 per 100 people, 7% of populationBolivia: 12.1 per 100 people, 21.8% of populationBrazil: 24.1 per 100 people, 2.5% of populationBarbados: 37.5 per 100 people, 4.4% of populationBotswana: 7.44 per 100 people, 24% of populationCentral African Republic: 0.0161 per 100 people, 29.8% of populationCanada: 42.5 per 100 people, 2.5% of populationSwitzerland: 47 per 100 people, 2.5% of populationChile: 23.7 per 100 people, 2.5% of populationChina: 47.2 per 100 people, 2.5% of populationCote d'Ivoire: 1.6 per 100 people, 11.1% of populationCameroon: 2.13 per 100 people, 4.8% of populationCongo, Dem. Rep.: 0.032 per 100 people, 38.5% of populationCongo, Rep.: 1.27 per 100 people, 26.4% of populationColombia: 17.2 per 100 people, 3.9% of populationComoros: 0.388 per 100 people, 15.4% of populationCabo Verde: 8.31 per 100 people, 13.5% of populationCosta Rica: 23.3 per 100 people, 2.5% of populationCyprus: 37.6 per 100 people, 2.5% of populationCzechia: 38.9 per 100 people, 2.5% of populationGermany: 45.6 per 100 people, 2.5% of populationDjibouti: 1.47 per 100 people, 12.9% of populationDominica: 20.9 per 100 people, 3.6% of populationDenmark: 43.4 per 100 people, 2.5% of populationDominican Republic: 11.2 per 100 people, 3.6% of populationAlgeria: 13.3 per 100 people, 2.5% of populationEcuador: 17.2 per 100 people, 12.1% of populationEgypt, Arab Rep.: 11.7 per 100 people, 9.4% of populationSpain: 39.2 per 100 people, 2.5% of populationEstonia: 35.4 per 100 people, 2.5% of populationEthiopia: 0.594 per 100 people, 19.7% of populationFinland: 36.5 per 100 people, 2.5% of populationFiji: 1.8 per 100 people, 6.8% of populationFrance: 48.9 per 100 people, 2.5% of populationGabon: 4.69 per 100 people, 25.3% of populationUnited Kingdom: 42.2 per 100 people, 2.5% of populationGeorgia: 30.4 per 100 people, 2.5% of populationGhana: 0.665 per 100 people, 6.3% of populationGuinea: 0.00628 per 100 people, 11.4% of populationGambia, The: 0.519 per 100 people, 16.8% of populationGuinea-Bissau: 0.386 per 100 people, 22.1% of populationGreece: 44.7 per 100 people, 2.5% of populationGuatemala: 5.34 per 100 people, 11.8% of populationGuyana: 12.9 per 100 people, 2.5% of populationHong Kong SAR, China: 40.3 per 100 people, 3.1% of populationHonduras: 4.58 per 100 people, 14.8% of populationCroatia: 29.6 per 100 people, 2.5% of populationHaiti: 0.307 per 100 people, 54.2% of populationHungary: 37.5 per 100 people, 2.5% of populationIndonesia: 4.92 per 100 people, 6.3% of populationIndia: 3.15 per 100 people, 12% of populationIreland: 32.3 per 100 people, 2.5% of populationIran, Islamic Rep.: 12.1 per 100 people, 6.8% of populationIraq: 17.6 per 100 people, 14.9% of populationIceland: 37.5 per 100 people, 2.5% of populationIsrael: 29.2 per 100 people, 2.5% of populationItaly: 31.8 per 100 people, 2.5% of populationJamaica: 16 per 100 people, 7.7% of populationJordan: 7.02 per 100 people, 14.3% of populationKazakhstan: 15.3 per 100 people, 2.5% of populationKenya: 3.04 per 100 people, 36.8% of populationKyrgyz Republic: 7.8 per 100 people, 5.1% of populationCambodia: 4.15 per 100 people, 5.2% of populationKiribati: 0.0349 per 100 people, 4.1% of populationKorea, Rep.: 47.8 per 100 people, 2.5% of populationKuwait: 1.01 per 100 people, 2.5% of populationLebanon: 7.29 per 100 people, 8.7% of populationLiberia: 0.275 per 100 people, 35.5% of populationLibya: 4.52 per 100 people, 16.5% of populationSri Lanka: 8.47 per 100 people, 7.4% of populationLithuania: 27.8 per 100 people, 2.5% of populationLuxembourg: 40.3 per 100 people, 2.5% of populationLatvia: 25.8 per 100 people, 2.5% of populationMacao SAR, China: 29.9 per 100 people, 11.2% of populationMorocco: 7.3 per 100 people, 7% of populationMoldova: 29.6 per 100 people, 2.5% of populationMadagascar: 0.124 per 100 people, 39.5% of populationMexico: 21.7 per 100 people, 2.7% of populationNorth Macedonia: 29.9 per 100 people, 2.5% of populationMali: 0.774 per 100 people, 12.3% of populationMalta: 44.5 per 100 people, 2.5% of populationMyanmar: 2.87 per 100 people, 5.4% of populationMontenegro: 32.3 per 100 people, 2.5% of populationMongolia: 15.8 per 100 people, 2.5% of populationMozambique: 0.142 per 100 people, 21.8% of populationMauritania: 0.947 per 100 people, 8.7% of populationMauritius: 28 per 100 people, 8.7% of populationMalawi: 0.0864 per 100 people, 21.4% of populationMalaysia: 13.5 per 100 people, 2.5% of populationNamibia: 2.83 per 100 people, 18.1% of populationNiger: 0.111 per 100 people, 12.9% of populationNigeria: 0.0787 per 100 people, 19.9% of populationNicaragua: 5.78 per 100 people, 17.3% of populationNetherlands: 43 per 100 people, 2.5% of populationNorway: 45.2 per 100 people, 2.5% of populationNepal: 10.1 per 100 people, 5.3% of populationNew Zealand: 38 per 100 people, 2.5% of populationOman: 11.1 per 100 people, 5.9% of populationPakistan: 1.47 per 100 people, 16.5% of populationPanama: 18.1 per 100 people, 5.7% of populationPeru: 11.7 per 100 people, 6.9% of populationPhilippines: 7.14 per 100 people, 3% of populationPapua New Guinea: 0.233 per 100 people, 28.7% of populationPoland: 25.4 per 100 people, 2.5% of populationPortugal: 45.2 per 100 people, 2.5% of populationParaguay: 12.9 per 100 people, 5.2% of populationRomania: 35.8 per 100 people, 2.5% of populationRussian Federation: 27.1 per 100 people, 2.5% of populationRwanda: 0.596 per 100 people, 24.4% of populationSaudi Arabia: 44.1 per 100 people, 2.5% of populationSudan: 0.0604 per 100 people, 11% of populationSenegal: 4.04 per 100 people, 5.1% of populationSolomon Islands: 0.107 per 100 people, 20% of populationSierra Leone: 0.00227 per 100 people, 24.1% of populationEl Salvador: 12.5 per 100 people, 6.7% of populationSomalia, Fed. Rep.: 0.723 per 100 people, 53.2% of populationSerbia: 33.4 per 100 people, 2.5% of populationSao Tome and Principe: 2.99 per 100 people, 17.4% of populationSuriname: 18.8 per 100 people, 9.7% of populationSlovak Republic: 33.8 per 100 people, 3.1% of populationSlovenia: 34.2 per 100 people, 2.5% of populationSweden: 40.6 per 100 people, 2.5% of populationEswatini: 2.51 per 100 people, 14.7% of populationSeychelles: 31.6 per 100 people, 2.5% of populationSyrian Arab Republic: 6.86 per 100 people, 39% of populationChad: 0 per 100 people, 32% of populationTogo: 1.42 per 100 people, 9.1% of populationThailand: 14.9 per 100 people, 4.6% of populationTajikistan: 0.984 per 100 people, 8.4% of populationTurkmenistan: 5.22 per 100 people, 4.3% of populationTimor-Leste: 0.006 per 100 people, 18.7% of populationTrinidad and Tobago: 27 per 100 people, 11.2% of populationTunisia: 15 per 100 people, 3% of populationTurkiye: 23.4 per 100 people, 2.5% of populationTanzania: 0.246 per 100 people, 20.2% of populationUganda: 0.208 per 100 people, 22% of populationUkraine: 21.7 per 100 people, 6.9% of populationUruguay: 33 per 100 people, 2.5% of populationUnited States: 38.9 per 100 people, 2.5% of populationUzbekistan: 34.7 per 100 people, 2.5% of populationSt. Vincent and the Grenadines: 29.5 per 100 people, 6.1% of populationViet Nam: 23.7 per 100 people, 5.3% of populationVanuatu: 1.16 per 100 people, 7.2% of populationSamoa: 0.878 per 100 people, 3.6% of populationSouth Africa: 5.35 per 100 people, 10% of populationZambia: 0.79 per 100 people, 37.2% of populationZimbabwe: 1.94 per 100 people, 19.7% of populationCHNFRAHTIKIRKORKWTMDGSOMSYRWSM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.6255.2e-19163
By rank (Spearman), not adjusted-0.8282.5e-42163
Standard (Pearson), adjusted for national income-0.0250.755163
By rank (Spearman), adjusted for national income-0.3223.0e-5163

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: +0.600 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.061 (without SOM) to +0.003 (without GAB). 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: SOM (-0.037).

Fragile: this link may not hold up.
  • sign flips when a single country is removed
  • correlation moves sharply 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 & Pacific21-0.07
Europe & Central Asia48-0.31
Latin America & Caribbean26-0.18
Middle East, North Africa, Afghanistan & Pakistan19+0.20
Sub-Saharan Africa43-0.05

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 third55-0.03
Middle third54-0.37
Richest third54-0.25

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
Christians100-0.07
Muslims44+0.01

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
France24-0.05
Never a European colony20+0.01
Spain18+0.05
United Kingdom48-0.01

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 = -0.195 after dropping 9 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.

The link also shows up within countries over time (r = +0.185). It holds even when looking only at changes from one year to the next (r = +0.086). This is the strongest kind of evidence available here: it holds when each country is compared only with itself, and it is not just a product of shared trends.

Across countries (adjusted)-0.025for comparison
Within countries-0.164each country vs itself
…and vs the same year elsewhere+0.185q = 0.015 · 165 countries
Year-on-year changes+0.086q = 0.017
The direction flips. Comparing each country only with itself gives -0.16. Also taking out what happened to the whole world each year gives +0.19. So the first figure was picking up a trend both measures share with worldwide progress, not a link between them.

3,356 country-years (one country in one year), 165 countries, 2001–2023, about 20 years each on average. Share of the variation that happens within countries over time: 12% for Fixed broadband, 33% 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 Fixed broadband →lag -10: r = 0.096 (n = 2,204)lag -9: r = 0.096 (n = 2,363)lag -8: r = 0.101 (n = 2,520)lag -7: r = 0.106 (n = 2,675)lag -6: r = 0.119 (n = 2,824)lag -5: r = 0.137 (n = 2,967)lag -4: r = 0.147 (n = 3,102)lag -3: r = 0.158 (n = 3,221)lag -2: r = 0.170 (n = 3,329)lag -1: r = 0.175 (n = 3,421)lag +0: r = 0.185 (n = 3,356)lag +1: r = 0.193 (n = 3,249)lag +2: r = 0.191 (n = 3,098)lag +3: r = 0.178 (n = 2,943)lag +4: r = 0.154 (n = 2,780)lag +5: r = 0.129 (n = 2,617)lag +6: r = 0.106 (n = 2,467)lag +7: r = 0.089 (n = 2,304)lag +8: r = 0.076 (n = 2,134)lag +9: r = 0.064 (n = 1,977)lag +10: r = 0.046 (n = 1,808)

Same year (lag 0): +0.185. 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


per 100 people
% of population		Years
France FRA48.92.5%2024, 2023
Korea, Rep. KOR47.82.5%2024, 2023
China CHN47.22.5%2024, 2023
Switzerland CHE472.5%2024, 2023
Germany DEU45.62.5%2024, 2023
Portugal PRT45.22.5%2024, 2023
Norway NOR45.22.5%2024, 2023
Greece GRC44.72.5%2024, 2023
Malta MLT44.52.5%2024, 2023
Belgium BEL44.22.5%2024, 2023
Saudi Arabia SAU44.12.5%2024, 2023
Denmark DNK43.42.5%2024, 2023
Netherlands NLD432.5%2024, 2023
Canada CAN42.52.5%2024, 2023
United Kingdom GBR42.22.5%2024, 2023

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

Sources

Fixed broadband

Fixed broadband subscriptions (per 100 people)

International Telecommunication Union · CC BY 4.0 · updated quarterly

Subscriptions, not people. A household line counts once, however many people use it. A country that went straight to mobile data can be well connected with few of these lines. Internet users, already on the site, is the measure of people.

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 Fixed broadband and Undernourishment

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

More links with Fixed broadband or Undernourishment