placestats

Undernourishment vs. Vulnerable employment

Fades after adjusting for income

Across 160 countries, Undernourishment and Vulnerable employment rise and fall together at r = +0.64 (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 = 0.87, 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 14.3% of population, vulnerable employment is worse by 18.4% of employment at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.503% of employment.

Link before adjusting (r)+0.641p = 7.4e-20 · 160 countries
After adjusting for national income+0.024p = 0.764 · likely range [-0.13, +0.18]
p, allowing for regions0.779standard error 0.082 · 7 regions
Check for luck (q)0.873across 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.

Undernourishment · % of populationlink with income -0.83 · proxy
Vulnerable employment · % of employmentlink with income -0.87 · 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

Undernourishment · % of population →Vulnerable employment · % of employment →2.5%54.2%1.5%90.2%Afghanistan: 28.1% of population, 81.8% of employmentAngola: 22.5% of population, 66.3% of employmentAlbania: 5.4% of population, 46% of employmentUnited Arab Emirates: 2.5% of population, 1.5% of employmentArgentina: 3.4% of population, 22.3% of employmentArmenia: 2.5% of population, 32.8% of employmentAustralia: 2.5% of population, 9.12% of employmentAustria: 2.5% of population, 7.85% of employmentAzerbaijan: 2.5% of population, 53.8% of employmentBelgium: 2.5% of population, 11% of employmentBenin: 14.3% of population, 78.5% of employmentBurkina Faso: 13.1% of population, 80.6% of employmentBangladesh: 10.4% of population, 57.3% of employmentBulgaria: 2.5% of population, 6.92% of employmentBosnia and Herzegovina: 2.5% of population, 18.1% of employmentBelarus: 2.5% of population, 6.33% of employmentBelize: 7% of population, 29.8% of employmentBolivia: 21.8% of population, 62.7% of employmentBrazil: 2.5% of population, 26.1% of employmentBarbados: 4.4% of population, 18.8% of employmentBotswana: 24% of population, 25.6% of employmentCentral African Republic: 29.8% of population, 79.4% of employmentCanada: 2.5% of population, 9.56% of employmentSwitzerland: 2.5% of population, 9.6% of employmentChile: 2.5% of population, 20.9% of employmentChina: 2.5% of population, 33.4% of employmentCote d'Ivoire: 11.1% of population, 69.4% of employmentCameroon: 4.8% of population, 67.6% of employmentCongo, Dem. Rep.: 38.5% of population, 81.5% of employmentCongo, Rep.: 26.4% of population, 75.9% of employmentColombia: 3.9% of population, 43% of employmentComoros: 15.4% of population, 56.8% of employmentCabo Verde: 13.5% of population, 34.3% of employmentCosta Rica: 2.5% of population, 23.4% of employmentCyprus: 2.5% of population, 8.38% of employmentCzechia: 2.5% of population, 13.5% of employmentGermany: 2.5% of population, 4.34% of employmentDjibouti: 12.9% of population, 30.3% of employmentDenmark: 2.5% of population, 5.4% of employmentDominican Republic: 3.6% of population, 38% of employmentAlgeria: 2.5% of population, 25.6% of employmentEcuador: 12.1% of population, 50.1% of employmentEgypt, Arab Rep.: 9.4% of population, 23.9% of employmentSpain: 2.5% of population, 10.1% of employmentEstonia: 2.5% of population, 7.09% of employmentEthiopia: 19.7% of population, 84.1% of employmentFinland: 2.5% of population, 9.46% of employmentFiji: 6.8% of population, 32.8% of employmentFrance: 2.5% of population, 8.5% of employmentGabon: 25.3% of population, 29.8% of employmentUnited Kingdom: 2.5% of population, 11.5% of employmentGeorgia: 2.5% of population, 42.4% of employmentGhana: 6.3% of population, 60% of employmentGuinea: 11.4% of population, 79.2% of employmentGambia, The: 16.8% of population, 63.5% of employmentGuinea-Bissau: 22.1% of population, 74.9% of employmentGreece: 2.5% of population, 23.1% of employmentGuatemala: 11.8% of population, 36.2% of employmentGuyana: 2.5% of population, 25.3% of employmentHong Kong SAR, China: 3.1% of population, 5.76% of employmentHonduras: 14.8% of population, 33.9% of employmentCroatia: 2.5% of population, 6.35% of employmentHaiti: 54.2% of population, 76% of employmentHungary: 2.5% of population, 7.83% of employmentIndonesia: 6.3% of population, 50% of employmentIndia: 12% of population, 71.6% of employmentIreland: 2.5% of population, 9.64% of employmentIran, Islamic Rep.: 6.8% of population, 39.5% of employmentIraq: 14.9% of population, 27.1% of employmentIceland: 2.5% of population, 8.4% of employmentIsrael: 2.5% of population, 7.7% of employmentItaly: 2.5% of population, 14.3% of employmentJamaica: 7.7% of population, 31.6% of employmentJordan: 14.3% of population, 7.86% of employmentKazakhstan: 2.5% of population, 24.8% of employmentKenya: 36.8% of population, 63.8% of employmentKyrgyz Republic: 5.1% of population, 29% of employmentCambodia: 5.2% of population, 52.3% of employmentKorea, Rep.: 2.5% of population, 17.7% of employmentKuwait: 2.5% of population, 2.4% of employmentLebanon: 8.7% of population, 19.4% of employmentLiberia: 35.5% of population, 76.9% of employmentLibya: 16.5% of population, 21.6% of employmentSri Lanka: 7.4% of population, 39.2% of employmentLithuania: 2.5% of population, 10.4% of employmentLuxembourg: 2.5% of population, 6.95% of employmentLatvia: 2.5% of population, 8.62% of employmentMacao SAR, China: 11.2% of population, 3.33% of employmentMorocco: 7% of population, 35.5% of employmentMoldova: 2.5% of population, 58.6% of employmentMadagascar: 39.5% of population, 84.4% of employmentMexico: 2.7% of population, 25.3% of employmentNorth Macedonia: 2.5% of population, 12.3% of employmentMali: 12.3% of population, 75.8% of employmentMalta: 2.5% of population, 10.1% of employmentMyanmar: 5.4% of population, 62.9% of employmentMontenegro: 2.5% of population, 14.3% of employmentMongolia: 2.5% of population, 38.4% of employmentMozambique: 21.8% of population, 83.7% of employmentMauritania: 8.7% of population, 53.3% of employmentMauritius: 8.7% of population, 14.9% of employmentMalawi: 21.4% of population, 59.9% of employmentMalaysia: 2.5% of population, 21.9% of employmentNamibia: 18.1% of population, 29.9% of employmentNiger: 12.9% of population, 83.7% of employmentNigeria: 19.9% of population, 66.5% of employmentNicaragua: 17.3% of population, 38.9% of employmentNetherlands: 2.5% of population, 13.4% of employmentNorway: 2.5% of population, 4.17% of employmentNepal: 5.3% of population, 77% of employmentNew Zealand: 2.5% of population, 12.6% of employmentOman: 5.9% of population, 3.81% of employmentPakistan: 16.5% of population, 55.5% of employmentPanama: 5.7% of population, 37.9% of employmentPeru: 6.9% of population, 47.5% of employmentPhilippines: 3% of population, 33.6% of employmentPapua New Guinea: 28.7% of population, 71.2% of employmentPoland: 2.5% of population, 15% of employmentPortugal: 2.5% of population, 9.66% of employmentParaguay: 5.2% of population, 36.1% of employmentRomania: 2.5% of population, 13% of employmentRussian Federation: 2.5% of population, 4.93% of employmentRwanda: 24.4% of population, 39.4% of employmentSaudi Arabia: 2.5% of population, 1.66% of employmentSudan: 11% of population, 39.7% of employmentSenegal: 5.1% of population, 63% of employmentSolomon Islands: 20% of population, 68.7% of employmentSierra Leone: 24.1% of population, 86% of employmentEl Salvador: 6.7% of population, 30.8% of employmentSomalia, Fed. Rep.: 53.2% of population, 46% of employmentSerbia: 2.5% of population, 23.9% of employmentSao Tome and Principe: 17.4% of population, 35% of employmentSuriname: 9.7% of population, 18.4% of employmentSlovak Republic: 3.1% of population, 11.8% of employmentSlovenia: 2.5% of population, 10.6% of employmentSweden: 2.5% of population, 6.87% of employmentEswatini: 14.7% of population, 28.4% of employmentSyrian Arab Republic: 39% of population, 38.9% of employmentChad: 32% of population, 90.2% of employmentTogo: 9.1% of population, 75% of employmentThailand: 4.6% of population, 48% of employmentTajikistan: 8.4% of population, 28% of employmentTurkmenistan: 4.3% of population, 28.3% of employmentTimor-Leste: 18.7% of population, 58.6% of employmentTrinidad and Tobago: 11.2% of population, 21.2% of employmentTunisia: 3% of population, 17.9% of employmentTurkiye: 2.5% of population, 23.9% of employmentTanzania: 20.2% of population, 83.7% of employmentUganda: 22% of population, 74.4% of employmentUkraine: 6.9% of population, 19% of employmentUruguay: 2.5% of population, 24.4% of employmentUnited States: 2.5% of population, 3.81% of employmentUzbekistan: 2.5% of population, 33.3% of employmentSt. Vincent and the Grenadines: 6.1% of population, 22% of employmentViet Nam: 5.3% of population, 51.4% of employmentVanuatu: 7.2% of population, 58% of employmentSamoa: 3.6% of population, 41.6% of employmentSouth Africa: 10% of population, 11.7% of employmentZambia: 37.2% of population, 70.2% of employmentZimbabwe: 19.7% of population, 68.2% of employmentARECMRHTIKWTMDGNPLSAUSOMSYRTGO

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.6417.4e-20160
By rank (Spearman), not adjusted+0.7261.7e-27160
Standard (Pearson), adjusted for national income+0.0240.764160
By rank (Spearman), adjusted for national income-0.0200.798160

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 160 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: +0.617 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.009 (without SDN) to +0.101 (without SOM). 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 (+0.077).

Fragile: this link may not hold up.
  • sign flips when a single country is removed
  • 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 & Pacific20+0.21
Europe & Central Asia48-0.19
Latin America & Caribbean25+0.55
Middle East, North Africa, Afghanistan & Pakistan19-0.04
Sub-Saharan Africa42-0.10

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 third54+0.03
Middle third53-0.06
Richest third53+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.

nr
Christians98+0.19
Muslims44-0.14

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
France24-0.10
Never a European colony20+0.06
Spain18+0.60
United Kingdom45+0.02

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 = +0.116 after dropping 8 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 = +0.172, 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 undernourishment moved did not tend to see their vulnerable employment move with it.

Across countries (adjusted)+0.024for comparison
Within countries+0.315each country vs itself
…and vs the same year elsewhere+0.172q = 0.165 · 165 countries
Year-on-year changes+0.045q = 0.176
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.

3,756 country-years (one country in one year), 165 countries, 2001–2023, about 23 years each on average. Share of the variation that happens within countries over time: 13% for Undernourishment, 1% for Vulnerable employment. 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

0.30−0.3-100+10years Vulnerable employment trails Undernourishment →lag -10: r = -0.110 (n = 3,758)lag -9: r = -0.085 (n = 3,758)lag -8: r = -0.056 (n = 3,758)lag -7: r = -0.023 (n = 3,758)lag -6: r = 0.009 (n = 3,758)lag -5: r = 0.040 (n = 3,758)lag -4: r = 0.071 (n = 3,758)lag -3: r = 0.102 (n = 3,758)lag -2: r = 0.130 (n = 3,758)lag -1: r = 0.153 (n = 3,757)lag +0: r = 0.172 (n = 3,756)lag +1: r = 0.189 (n = 3,754)lag +2: r = 0.202 (n = 3,751)lag +3: r = 0.209 (n = 3,589)lag +4: r = 0.212 (n = 3,426)lag +5: r = 0.209 (n = 3,263)lag +6: r = 0.198 (n = 3,096)lag +7: r = 0.182 (n = 2,934)lag +8: r = 0.163 (n = 2,771)lag +9: r = 0.136 (n = 2,608)lag +10: r = 0.105 (n = 2,445)

Same year (lag 0): +0.172. 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


% of population
% of employment		Years
Haiti HTI54.2%76%2023, 2025
Somalia, Fed. Rep. SOM53.2%46%2023, 2025
Madagascar MDG39.5%84.4%2023, 2025
Syrian Arab Republic SYR39%38.9%2023, 2025
Congo, Dem. Rep. COD38.5%81.5%2023, 2025
Zambia ZMB37.2%70.2%2023, 2025
Kenya KEN36.8%63.8%2023, 2025
Liberia LBR35.5%76.9%2023, 2025
Chad TCD32%90.2%2023, 2025
Central African Republic CAF29.8%79.4%2023, 2025
Papua New Guinea PNG28.7%71.2%2023, 2025
Afghanistan AFG28.1%81.8%2023, 2025
Congo, Rep. COG26.4%75.9%2023, 2025
Gabon GAB25.3%29.8%2023, 2025
Rwanda RWA24.4%39.4%2023, 2025

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

Sources

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.

Vulnerable employment

Vulnerable employment, total (% of total employment)

International Labour Organization · CC BY 4.0 · updated quarterly

Self-employed workers and unpaid family workers, who have no employer and usually no protection. The ILO estimates it with a model for every country and year, which is why it is complete where surveys are not.

How this was computed

Data used: most recent value in 2010-2025; values come from 2021–2025. 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 Undernourishment and Vulnerable employment

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

More links with Undernourishment or Vulnerable employment